02335nas a2200301 4500008004100000022001300041245011500054210006900169260001600238300001100254490000700265520135700272100002001629700001901649700003201668700001801700700002101718700002701739700002401766700003301790700001301823700001801836700002701854700002201881700001801903700002401921856008801945 2020 eng d a2214629600aCulture, conformity, and carbon? A multi-country analysis of heating and cooling practices in office buildings0 aCulture conformity and carbon A multicountry analysis of heating cJan-03-2020 a1013440 v613 a

This study investigates human-building interaction in office spaces across multiple countries including Brazil, Italy, Poland, Switzerland, the United States, and Taiwan. We analyze social-psychological, contextual, and demographic factors to explain cross-country differences in adaptive thermal actions (i.e. cooling and heating behaviors) and conformity to the norms of sharing indoor environmental control features, an indicator of energy consumption. Specifically, personal adjustments such as putting on extra clothes are generally preferred over technological solutions such as adjusting thermostats in reaction to thermal discomfort. Social-psychological factors including attitudes, perceived behavioral control, injunctive norms, and perceived impact of indoor environmental quality on work productivity influence occupants’ intention to conform to the norms of sharing environmental control features. Lastly, accessibility to environmental control features, office type, gender, and age are also important factors. These findings demonstrate the roles of social-psychological and certain contextual factors in occupants’
interactions with building design as well as their behavior of sharing environmental control features, both of which significantly influence building energy consumption, and thus, broader decarbonization.

1 aChen, Chien-fei1 aHong, Tianzhen1 ade Rubens, Gerardo, Zarazua1 aYilmaz, Selin1 aBandurski, Karol1 aBélafi, Zsófia, Deme1 aDe Simone, Marilena1 aBavaresco, Mateus, Vinícius1 aWang, Yu1 aLiu, Pei-ling1 aBarthelmes, Verena, M.1 aAdams, Jacqueline1 aD'Oca, Simona1 aPrzybylski, Łukasz uhttps://simulationresearch.lbl.gov/publications/culture-conformity-and-carbon-multi02294nas a2200193 4500008004100000022001300041245005200054210005200106260001600158300001100174490000800185520173700193100001901930700001701949700001401966700001201980700002001992856008802012 2020 eng d a0360132300aTen questions on urban building energy modeling0 aTen questions on urban building energy modeling cJan-01-2020 a1065080 v1683 a

Buildings in cities consume up to 70% of all primary energy. To achieve cities’ energy and climate goals, it is necessary to reduce energy use and associated greenhouse gas emissions in buildings through energy conservation and efficiency improvements. Computational tools empowered with rich urban datasets can model performance of buildings at the urban scale to provide quantitative insights for stakeholders and inform their decision making on urban energy planning, as well as building energy retrofits at scale, to achieve efficiency, sustainability, and resilience of urban buildings.
Designing and operating urban buildings as a group (from a city block to a district to an entire city) rather than as single individuals requires simulation and optimization to account for interactions among buildings and between buildings and their surrounding urban environment, and for district energy systems serving multiple buildings with diverse thermal loads across space and time. When hundreds or more buildings are involved in typical urban building energy modeling (UBEM) to estimate annual energy demand, evaluate design or retrofit options, and quantify impacts of extreme weather events or climate change, it is crucial to integrate urban datasets and UBEM tools in a seamless automatic workflow with cloud or high-performance computing for users including urban planners, designers and researchers.
This paper presents ten questions that highlight significant UBEM research and applications. The proposed answers aim to stimulate discussion and provide insights into the current and future research on UBEM, and more importantly, to inspire new and important questions from young researchers in the field.

1 aHong, Tianzhen1 aChen, Yixing1 aLuo, Xuan1 aLuo, Na1 aLee, Sang, Hoon uhttps://simulationresearch.lbl.gov/publications/ten-questions-urban-building-energy01791nas a2200229 4500008004100000245007800041210006900119260001200188520103000200653003101230653002001261653002001281653001401301653001801315653002701333653002701360653002801387100002001415700002301435700002101458856008201479 2019 eng d00aAssessing the Potential to Reduce U.S. Building CO2 Emissions 80% by 20500 aAssessing the Potential to Reduce US Building CO2 Emissions 80 b c08/20193 a

Buildings are responsible for 36% of CO2 emissions in the United States and will thus be integral to climate change mitigation; yet, no studies have comprehensively assessed the potential long-term CO2 emissions reductions from the U.S. buildings sector against national goals in a way that can be regularly updated in the future. We use Scout, a reproducible and granular model of U.S. building energy use, to investigate the potential for the U.S. buildings sector to reduce CO2 emissions 80% by 2050, consistent with the U.S. Mid-Century Strategy. We find that a combination of aggressive efficiency measures, electrification, and high renewable energy penetration can reduce CO2 emissions by 72%–78% relative to 2005 levels, just short of the target. Results are sufficiently disaggregated by technology and end use to inform targeted building energy policy approaches and establish a foundation for continual reassessment of technology development pathways that drive significant long-term emissions reductions.

10aBuilding energy efficiency10adecarbonization10aelectrification10aemissions10aenergy models10aenergy policy analysis10anational climate goals10apathways building stock1 aLangevin, Jared1 aHarris, Chioke, B.1 aReyna, Janet, L. uhttps://simulationresearch.lbl.gov/publications/assessing-potential-reduce-us02298nas a2200277 4500008004100000022001300041245016000054210006900214260001600283300001600299490000800315520136500323653004401688653002401732653002301756653001801779653002201797653002301819100001201842700001701854700001501871700001901886700001301905700001501918856008701933 2019 eng d a0048969700aAssessment of occupant-behavior-based indoor air quality and its impacts on human exposure risk: A case study based on the wildfires in Northern California0 aAssessment of occupantbehaviorbased indoor air quality and its i cJan-10-2019 a1251 - 12610 v6863 a

The recent wildfires in California, U.S., have caused not only significant losses to human life and property, but also serious environmental and health issues. Ambient air pollution from combustion during the fires could increase indoor exposure risks to toxic gases and particles, further exacerbating respiratory conditions. This work aims at addressing existing knowledge gaps in understanding how indoor air quality is affected by outdoor air pollutants during wildfires—by taking into account occupant behaviors (e.g., movement, operation of windows and air-conditioning) which strongly influence building performance and occupant comfort. A novel modeling framework was developed to simulate the indoor exposure risks considering the impact of occupant behaviours by integrating building energy and occupant behaviour modeling with computational fluid dynamics simulation. Occupant behaviors were found to exert significant impacts on indoor air flow patterns and pollutant concentrations, based on which, certain behaviors are recommended during wildfires. Further, the actual respiratory injury level under such outdoor conditions was predicted. The modeling framework and the findings enable a deeper understanding of the actual health impacts of wildfires, as well as informing strategies for mitigating occupant health risk during wildfires

10acomputational fluid dynamics siumlation10ahuman exposure risk10aindoor air quality10aNAPA wildfire10aoccupant behavior10arespiratory injury1 aLuo, Na1 aWeng, Wenguo1 aXu, Xiaoyu1 aHong, Tianzhen1 aFu, Ming1 aSun, Kaiyu uhttps://simulationresearch.lbl.gov/publications/assessment-occupant-behavior-based01863nas a2200205 4500008004100000245009300041210006900134260000900203520116400212653002401376653001801400653003501418653001601453653002301469100002401492700001701516700001601533700001901549856008901568 2019 eng d00aComparison of MPC Formulations for Building Control under Commercial Time-of-Use Tariffs0 aComparison of MPC Formulations for Building Control under Commer c20193 a

Most medium and large commercial buildings in the U.S. are subject to complex electricity tariffs that combine both Time-of-Use (TOU) energy and demand charges. This study analyses the performances of different economic Model Predictive Control (MPC) formulations, from the standpoints of monthly bill reduction, load shifting, and peak demand reduction. Simulations are performed on many simplified commercial building models, with multiple TOU demand charges, and under various summer conditions. Results show that compared to energy-only MPC, the traditional method for dealing with demand charges significantly
reduces peak demand and owner bill, however, highlight a lack of load shifting capability. A proposed incremental approach
is presented, which better balances the bill components in the objective function. In the case study presented, this method
can improve monthly bill savings and increase load shifting during demand response events, while keeping a similarly low
peak demand, compared to traditional MPC methods taking into account demand charges.

10acommercial building10ademand charge10aModel predictive control (MPC)10apeak demand10atime-of-use tarrif1 aVan Cutsem, Olivier1 aKayal, Maher1 aBlum, David1 aPritoni, Marco uhttps://simulationresearch.lbl.gov/publications/comparison-mpc-formulations-building01804nas a2200265 4500008004100000022001300041245010900054210006900163260001600232300001100248490000800259520098000267653001601247653002201263653002101285653002501306653002401331100001401355700001901369700001301388700001701401700001601418700001901434856008501453 2019 eng d a0360132300aCross-source sensing data fusion for building occupancy prediction with adaptive lasso feature filtering0 aCrosssource sensing data fusion for building occupancy predictio cJan-09-2019 a1062800 v1623 a

Fusing various sensing data sources can significantly improve the accuracy and reliability of building occupancy detection. Fusing environmental sensors and wireless network signals are seldom studied for its computational and technical complexity. This study aims to propose an integrated adaptive lasso model that is able to extract critical data features for environmental and Wi-Fi probe dual sensing sources. Through rapid feature extraction and process simplification, the proposed method aims to improve the computational efficiency of occupancy detecting models. To validate the proposed model, an onsite experiment was conducted to examine two occupancy data resolutions, (real-time and four-level occupancy resolutions). The results suggested that, among all twelve features, eight features are most relevant. The mean absolute error of the real-time occupancy can be reduced to 2.18 and F1_accuracy is about 84.36% for the four-level occupancy.

10adata fusion10aFeature selection10aMachine learning10aoccupancy prediction10aPhysics-based model1 aWang, Wei1 aHong, Tianzhen1 aXu, Ning1 aXu, Xiaodong1 aChen, Jiayu1 aShan, Xiaofang uhttps://simulationresearch.lbl.gov/publications/cross-source-sensing-data-fusion02297nas a2200241 4500008004100000022001300041245010400054210006900158260001200227300001400239490000800253520153900261653001601800653001801816653002401834653003301858653001901891653002301910100001401933700001901947700002201966856006701988 2019 eng d a0306261900aData fusion in predicting internal heat gains for office buildings through a deep learning approach0 aData fusion in predicting internal heat gains for office buildin c02/2019 a386 - 3980 v2403 a

Heating, Ventilation, and Air Conditioning (HVAC) is a major energy consumer in buildings. The predictive control has demonstrated a potential to reduce HVAC energy use. To facilitate predictive HVAC control, internal heat gains prediction is required. In this study, we applied Long Short-Term Memory Networks, a special form of deep neural network, to predict miscellaneous electric loads, lighting loads, occupant counts and internal heat gains in two United States office buildings. Compared with the predetermined schedules used in American Society of Heating, Refrigerating and Air-Conditioning Engineers (ASHRAE) standard 90.1, the Long Short-Term Memory Networks method could reduce the prediction errors of internal heat gains from 12% to 8% in Building A, and from 26% to 16% in Building B. It was also found that for internal heat gains prediction, miscellaneous electric loads is a more important feature than occupant counts for two reasons. First, miscellaneous electric loads is the best proxy variable for internal heat gains, as it is the major component of and has the highest correlation coefficient with the internal heat gains. Second, miscellaneous electric loads contain valuable information to predict occupant count, while occupant count could not help improve miscellaneous electric loads prediction. These findings could help researchers and practitioners select the most relevant features to more accurately predict internal heat gains for the implementation of predictive HVAC control in buildings.

10adata fusion10adeep learning10aInternal heat gains10aMiscellaneous electric loads10aOccupant count10aPredictive control1 aWang, Zhe1 aHong, Tianzhen1 aPiette, Mary, Ann uhttps://linkinghub.elsevier.com/retrieve/pii/S030626191930363002341nas a2200241 4500008004100000022001300041245007700054210006900131260001200200300001400212490000800226520145500234653002601689653001201715653001701727653001901744653003501763100001701798700001901815700001401834700001801848856023301866 2019 eng d a0378778800aDevelopment of city buildings dataset for urban building energy modeling0 aDevelopment of city buildings dataset for urban building energy  c11/2018 a252 - 2650 v1833 a

Urban building energy modeling (UBEM) is becoming a proven tool to support energy efficiency programs for buildings in cities. Development of a city-scale dataset of the existing building stock is a critical step of UBEM to automatically generate energy models of urban buildings and simulate their performance. This study introduces data needs, data standards, and data sources to develop city building datasets for UBEM. First, a literature review of data needs for UBEM was conducted. Then, the capabilities of the current data standards for city building datasets were reviewed. Moreover, the existing public data sources from several pioneer cites were studied to evaluate whether they are adequate to support UBEM. The results show that most cities have adequate public data to support UBEM; however, the data are represented in different formats without standardization, and there is a lack of common keys to make the data mapping easier. Finally, a case study is presented to integrate the diverse data sources from multiple city departments of San Francisco. The data mapping process is introduced and discussed. It is recommended to use the unique building identifiers as the common keys in the data sources to simplify the data mapping process. The integration methods and workflow are applied to other U.S. cities for developing the city-scale datasets of their existing building stock, including San Jose, Los Angeles, and Boston.

10aCity building dataset10aCityGML10aData mapping10aData standards10aUrban Building Energy Modeling1 aChen, Yixing1 aHong, Tianzhen1 aLuo, Xuan1 aHooper, Barry uhttps://linkinghub.elsevier.com/retrieve/pii/S0378778818316852https://api.elsevier.com/content/article/PII:S0378778818316852?httpAccept=text/xmlhttps://api.elsevier.com/content/article/PII:S0378778818316852?httpAccept=text/plain02259nas a2200265 4500008004100000022001300041245013000054210006900184260001200253300001400265490000800279520141300287653002901700653002101729653002701750653001901777653003601796100001401832700001901846700001701865700001601882700001501898700001301913856006701926 2019 eng d a0306261900aForecasting district-scale energy dynamics through integrating building network and long short-term memory learning algorithm0 aForecasting districtscale energy dynamics through integrating bu c04/2019 a217 - 2300 v2483 a

With the development of data-driven techniques, district-scale building energy prediction has attracted increasing attention in recent years for revealing energy use patterns and reduction potentials. However, data acquisition in large building groups is difficult and adjacent buildings also interact with each other. To reduce data cost and incorporate the inter-building impact with the data-driven building energy model, this study proposes a deep learning predictive approach that fuses the building network model with a long short-term memory learning model for district-scale building energy modeling. The building network was constructed based on correlations between the energy use intensity of buildings, which can significantly reduce the computational complexity of the deep learning models for energy dynamic prediction. Five typical building groups with energy use data from 2015 to 2018 on two institutional campuses were selected to perform the validation experiment with TensorFlow. Based on the prediction error assessments, the results suggest that for total building energy use intensity prediction, the proposed model can achieve a mean absolute percentage error of 6.66% and a root mean square error of 0.36 kWh/m2, compared to 12.05% and 0.63 kWh/m2 of the conventional artificial neural network model and to 11.06% and 0.89 kWh/m2 for the support vector regression model.

10aBuilding Energy Modeling10aBuilding network10aData-driven prediction10aDistrict-scale10aLong short-term memory networks1 aWang, Wei1 aHong, Tianzhen1 aXu, Xiaodong1 aChen, Jiayu1 aLiu, Ziang1 aXu, Ning uhttps://linkinghub.elsevier.com/retrieve/pii/S030626191930749402515nas a2200241 4500008004100000022001300041245010300054210006900157260001200226300001200238490000800250520174400258653003102002653002102033653003902054653002602093653002102119100001702140700001402157700001902171700001602190856006702206 2019 eng d a0378778800aIncorporating machine learning with building network analysis to predict multi-building energy use0 aIncorporating machine learning with building network analysis to c06/2019 a80 - 970 v1863 a

Predicting multi-building energy use at campus or city district scale has recently gained more attention; and more researchers have started to define reference buildings and study inter-impact between building groups. However, how to integrate the relationship to define reference buildings and predict multi-building energy use, using significantly less amount of building data and reducing complexity of prediction models, remains an open research question. To resolve this, this study proposed a novel method to predict multi-building energy use by integrating a social network analysis (SNA) with an Artificial Neural Network (ANN) technique. The SNA method was used to establish a building network (BN) by identifying reference buildings and determine correlations between reference buildings and non-reference buildings. The ANN technique was applied to learn correlations and historical building energy use, and then used to predict multi-building energy use. To validate the SNA-ANN method, 17 buildings in the Southeast University campus, located in Nanjing, China, were studied. These buildings have three years of actual monthly electricity use data and were grouped into four types: office, educational, laboratory, and residential. The results showed the integrated SNA-ANN method achieved average prediction accuracies of 90.67% for the office group, 90.79% for the educational group, 92.34% for the laboratory group, and 83.32% for the residential group. The results demonstrated the proposed SNA-ANN method achieved an accuracy of 90.28% for the predicted energy use for all building groups. Finally, this study provides insights into advancing the interdisciplinary research on multi-building energy use prediction.

10aArtificial neural networks10aBuilding network10acold winter and hot summer climate10aEnergy use prediction10aMachine learning1 aXu, Xiaodong1 aWang, Wei1 aHong, Tianzhen1 aChen, Jiayu uhttps://linkinghub.elsevier.com/retrieve/pii/S037877881831976502420nas a2200253 4500008004100000022001300041245008400054210006900138260001200207300001400219490000800233520166500241653002101906653002101927653002501948653001901973653001801992653001502010100001402025700001902039700002202058700001902080856006702099 2019 eng d a0360132300aInferring occupant counts from Wi-Fi data in buildings through machine learning0 aInferring occupant counts from WiFi data in buildings through ma c05/2019 a281 - 2940 v1583 a

An important approach to curtail building energy consumption is to optimize building control based on occupancy information. Various studies proposed to estimate occupant counts through different approaches and sensors. However, high cost and privacy concerns remain as major barriers, restricting the practice of occupant count detection. In this study, we propose a novel method utilizing data from widely deployed Wi-Fi infrastructure to infer occupant counts through machine learning. Compared with the current indirect measurement methods, our method improves the performance of estimating people count: (1) we avoid privacy concerns by anonymizing and reshuffling the MAC addresses on a daily basis; (2) we adopted a heuristic feature engineer approach to cluster connected devices into different types based on their daily connection duration. We tested the method in an office building located in California. In an area with an average occupancy of 22–27 people and a peak occupancy of 48–74 people, the root square mean error on the test set is less than four people. The error is within two people counts for more than 70% of estimations, and less than six counts for more than 90% of estimations, indicating a relatively high accuracy. The major contribution of this study is proposing a novel and accurate approach to detect occupant counts in a non-intrusive way, i.e., utilizing existing Wi-Fi infrastructure in buildings without requiring the installation of extra hardware or sensors. The method we proposed is generic and could be applied to other commercial buildings to infer occupant counts for energy efficient building control.

10aBuilding control10aMachine learning10aOccupancy estimation10aOccupant count10aRandom forest10aWi-Fi data1 aWang, Zhe1 aHong, Tianzhen1 aPiette, Mary, Ann1 aPritoni, Marco uhttps://linkinghub.elsevier.com/retrieve/pii/S036013231930333601992nas a2200229 4500008004100000022001300041245008400054210006900138260001200207300001200219490000800231520128900239653003601528653001501564653001701579653002601596653001801622653001601640100001901656700002001675856006701695 2019 eng d a0360132300aIntegrating physics-based models with sensor data: An inverse modeling approach0 aIntegrating physicsbased models with sensor data An inverse mode c05/2019 a23 - 310 v1543 a

Physics-based building energy models (e.g., EnergyPlus) rely on some unknown input parameters (e.g., zone air infiltration) that are hard to measure, leading to uncertainty in simulation results especially for existing buildings with varying operating conditions. With the increasing deployment of smart thermostats, zone air temperature data are readily available, posing a new opportunity for building energy modeling if such data can be harnessed. This study presents a novel inverse modeling approach which inverses the zone air heat balance equation and uses the measured zone air temperature to analytically calculate the zone air infiltration rate and zone internal thermal mass (e.g., furniture, interior partitions), which are two important model parameters with great variability and difficult to measure. This paper introduces the technical concept and algorithms of the inverse models, their implementation in EnergyPlus, and verification using EnergyPlus simulated building performance data. The inverse modeling approach provides new opportunities for integrating data from massive IoT sensors and devices to enhance the accuracy of simulation results which are used to inform decision making on energy retrofits and efficiency improvements of existing buildings.

10abuilding performance simulation10aenergyplus10ainfiltration10ainternal thermal mass10ainverse model10asensor data1 aHong, Tianzhen1 aLee, Sang, Hoon uhttps://linkinghub.elsevier.com/retrieve/pii/S036013231930160X02132nas a2200241 4500008004100000022001300041245011800054210006900172260001600241300001400257490000800271520136600279653001501645653001701660653002101677653001701698653001601715653002401731100001201755700001901767700001801786856008601804 2019 eng d a0378778800aAn inverse approach to solving zone air infiltration rate and people count using indoor environmental sensor data0 ainverse approach to solving zone air infiltration rate and peopl cJan-09-2019 a228 - 2420 v1983 a

Physics-based simulation of energy use in buildings is widely used in building design and performance rating, controls design and operations. However, various challenges exist in the modeling process. Model parameters such as people count and air infiltration rate are usually highly uncertain, yet they have significant impacts on the simulation accuracy. With the increasing availability and affordability of sensors and meters in buildings, a large amount of measured data has been collected including indoor environmental parameters, such as room air dry-bulb temperature, humidity ratio, and CO2 concentration levels. Fusing these sensor data with traditional energy modeling poses new opportunities to improve simulation accuracy. This study develops a set of physics-based inverse algorithms which can solve the highly uncertain and hard-to-measure building parameters such as zone-level people count and air infiltration rate. A simulation-based case study is conducted to verify the inverse algorithms implemented in EnergyPlus covering various sensor measurement scenarios and different modeling use cases. The developed inverse models can solve the zone people count and air infiltration at sub-hourly resolution using the measured zone air temperature, humidity and/or CO2 concentration given other easy-to-measure model parameters are known.

10aenergyplus10ainfiltration10aInverse problems10apeople count10asensor data10azone air parameters1 aLi, Han1 aHong, Tianzhen1 aSofos, Marina uhttps://simulationresearch.lbl.gov/publications/inverse-approach-solving-zone-air01978nas a2200145 4500008004100000022001300041245012900054210006900183260001600252300001100268520142500279100001401704700001901718856009501737 2019 eng d a1364032100aLearning occupants’ indoor comfort temperature through a Bayesian inference approach for office buildings in United States0 aLearning occupants indoor comfort temperature through a Bayesian cJan-11-2019 a1095933 a

A carefully chosen indoor comfort temperature as the thermostat set-point is the key to optimizing building energy use and occupants’ comfort and well-being. ASHRAE Standard 55 or ISO Standard 7730 uses the PMV-PPD model or the adaptive comfort model that is based on small-sized or outdated sample data, which raises questions on whether and how ranges of occupant thermal comfort temperature should be revised using more recent larger-sized dataset. In this paper, a Bayesian inference approach has been used to derive new occupant comfort temperature ranges for U.S. office buildings using the ASHRAE Global Thermal Comfort Database. Bayesian inference can express uncertainty and incorporate prior knowledge. The comfort temperatures were found to be higher and less variable at cooling mode than at heating mode, and with significant overlapped variation ranges between the two modes. The comfort operative temperature of occupants varies between 21.9 and 25.4°C for the cooling mode with a median of 23.7°C, and between 20.5 and 24.9°C for the heating mode with a median of 22.7°C. These comfort temperature ranges are similar to the current ASHRAE standard 55 in the heating mode but 2-3°C lower in the cooling mode. The results of this study could be adopted as more realistic thermostat set-points in building design, operation, control optimization, energy performance analysis, and policymaking.

1 aWang, Zhe1 aHong, Tianzhen uhttps://simulationresearch.lbl.gov/publications/learning-occupants%E2%80%99-indoor-comfort02424nas a2200241 4500008004100000022001300041245013600054210006900190260001200259300001200271490000800283520161400291653002301905653003401928653002301962653002701985100001402012700001902026700001202045700001902057700001602076856009002092 2019 eng d a0306261900aLinking energy-cyber-physical systems with occupancy prediction and interpretation through WiFi probe-based ensemble classification0 aLinking energycyberphysical systems with occupancy prediction an c02/2019 a55 - 690 v2363 a

With rapid advances in sensing and digital technologies, cyber-physical systems are regarded as the most prominent platforms to improve building design and management. Researchers investigated the possibility of integrating energy management system with cyber-physical systems as energy-cyber-physical systems to promote building energy management. However, minimizing energy consumption while fulfilling building functions for energy-cyber-physical systems is challenging due to the dynamics of building occupants. As occupant behavior is one major source of uncertainties for energy management, ignoring it often results in energy wastes caused by overheating and overcooling as well as discomfort due to insufficient thermal and ventilation services. To mitigate such uncertainties, this study proposed an occupancy linked energy-cyber-physical system that incorporates WiFi probe-based occupancy detection. The proposed framework utilized ensemble classification algorithms to extract three types of occupancy information. It creates a data interface to link energy management system and cyber-physical systems and allows automated occupancy detection and interpretation through assembling multiple weak classifiers for WiFi signals. A validation experiment in a large office room was conducted to examine the performance of the proposed occupancy linked energy-cyber-physical systems. The experiment and simulation results suggest that, with a proper classifier and occupancy type, the proposed model can potentially save about 26.4% of energy consumption from the cooling and ventilation demands.

10aBuilding occupancy10aEnergy-Cyber-Physical Systems10aensemble algorithm10aWi-Fi probe technology1 aWang, Wei1 aHong, Tianzhen1 aLi, Nan1 aWang, Ryan, Qi1 aChen, Jiayu uhttps://simulationresearch.lbl.gov/publications/linking-energy-cyber-physical-systems01921nas a2200265 4500008004100000022001300041245007100054210006600125260001200191300001600203490000800219520115000227653002401377653000901401653001401410653002501424653004301449653002101492100001501513700001201528700001901540700001501559700001401574856006701588 2019 eng d a0306261900aA novel approach for selecting typical hot-year (THY) weather data0 anovel approach for selecting typical hotyear THY weather data c03/2019 a1634 - 16480 v2423 a

The global climate change has resulted in not only warmer climate conditions but also more frequent extreme weather events, such as heat waves. However, the impact of heat waves on the indoor environment has been investigated in a limited manner. In this research, the indoor thermal environment is analyzed using a building performance simulation tool for a typical residential building in multiple cities in China, over a time period of 60 years using actual measured weather data, in order to gain a better understanding of the effect of heat wave events. The simulation results were used to analyze the indoor environment during hot summers. A new kind of weather data referred to as the typical hot year was defined and selected based on the simulated indoor environment during heat waves. The typical hot-year weather data can be used to simulate the indoor environment during extreme heat events and for the evaluation of effective technologies and strategies to mitigate against the impact of heat waves on the energy demand of buildings and human health. The limitations of the current study and future work are also discussed.

10aActual weather data10adest10aHeat wave10aMultiyear simulation10aResidential indoor thermal environment10aTypical hot year1 aGuo, Siyue1 aYan, Da1 aHong, Tianzhen1 aXiao, Chan1 aCui, Ying uhttps://linkinghub.elsevier.com/retrieve/pii/S030626191930465901972nas a2200145 4500008004100000245010000041210006900141260001200210520143000222100002401652700002601676700001501702700001901717856009001736 2019 eng d00aOPEN COMPUTING INFRASTRUCTURE FOR SHARING DATA ANALYTICS TO SUPPORT BUILDING ENERGY SIMULATIONS0 aOPEN COMPUTING INFRASTRUCTURE FOR SHARING DATA ANALYTICS TO SUPP c08/20193 a

Building energy simulation plays an increasingly important role in building design and operation. In this paper, we present an open computing infrastructure, Virtual Information Fabric Infrastructure (VIFI), that allows building designers and engineers to enhance their simulations by combining empirical data with diagnostic or prognostic models. Based on the idea of dynamic data-driven application systems (DDDAS), the VIFI infrastructure complements conventional data-centric sharing strategies and addresses key data sharing concerns such as the privacy of building occupants. To demonstrate the potential of the VIFI infrastructure, we simulate an empirically-derived lighting schedule in the U.S. Department of Energy's small office building reference model. We use the case study simulation to explore the possibility and potential of integrating data-centric and analytic-centric sharing strategies; the method of combining empirical data with simulations; the creation, sharing, and execution of analytics using VIFI; and the impact of incorporating empirical data on energy simulations. While the case study reveals clear advantages of the VIFI data infrastructure, research questions remain surrounding the motivation and benefits for sharing data, the metadata that are required to support the composition of analytics, and the performance metrics that could be used in assessing the applications of VIFI.

1 aKaraguzel, Omer, T.1 aElshambakey, Mohammed1 aZhu, Yimin1 aHong, Tianzhen uhttps://simulationresearch.lbl.gov/publications/open-computing-infrastructure-sharing02290nas a2200193 4500008004100000022001400041245012000055210006900175260001200244300001400256490000700270520148300277100001701760700001401777700001401791700001901805700001301824856025901837 2019 eng d a1996-359900aPerformance-driven optimization of urban open space configuration in the cold-winter and hot-summer region of China0 aPerformancedriven optimization of urban open space configuration c03/2019 a411 - 4240 v123 a

Urbanization has led to changes in urban morphology and climate, while urban open space has become an important ecological factor for evaluating the performance of urban development. This study presents an optimization approach using computational performance simulation. With a genetic algorithm using the Grasshopper tool, this study analyzed the layout and configuration of urban open space and its impact on the urban micro-climate under summer and winter conditions. The outdoor mean Universal Thermal Climate Index (UTCI) was applied as the performance indicator for evaluating the quality of the urban micro-climate. Two cases—one testbed and one real urban block in Nanjing, China—were used to validate the computer-aided simulation process. The optimization results in the testbed showed UTCI values varied from 36.5 to 37.3 °C in summer and from −4.9 to −1.9 °C in winter. In the case of the real urban block, optimization results show, for summer, although the average UTCI value increased by 0.6 °C, the average air velocity increased by 0.2 m/s; while in winter, the average UTCI value increased by 1.7 °C and the average air velocity decreased by 0.2 m/s. These results demonstrate that the proposed computer-aided optimization process can improve the thermal comfort conditions of open space in urban blocks. Finally, this study discusses strategies and guidelines for the layout design of urban open space to improve urban environment comfort.

1 aXu, Xiaodong1 aWu, Yifan1 aWang, Wei1 aHong, Tianzhen1 aXu, Ning uhttp://link.springer.com/10.1007/s12273-019-0510-zhttp://link.springer.com/content/pdf/10.1007/s12273-019-0510-z.pdfhttp://link.springer.com/content/pdf/10.1007/s12273-019-0510-z.pdfhttp://link.springer.com/article/10.1007/s12273-019-0510-z/fulltext.html02860nas a2200253 4500008004100000022001300041245017500054210006900229260001200298300001400310490000800324520184700332653002402179653000902203653002902212653002602241100001602267700001502283700001802298700002202316700002002338700001502358856023302373 2019 eng d a0306261900aPractical factors of envelope model setup and their effects on the performance of model predictive control for building heating, ventilating, and air conditioning systems0 aPractical factors of envelope model setup and their effects on t c02/2019 a410 - 4250 v2363 a

Model predictive control (MPC) for buildings is attracting significant attention in research and industry due to its potential to address a number of challenges facing the building industry, including energy cost reduction, grid integration, and occupant connectivity. However, the strategy has not yet been implemented at any scale, largely due to the significant effort required to configure and calibrate the model used in the MPC controller. While many studies have focused on methods to expedite model configuration and improve model accuracy, few have studied the impact a wide range of factors have on the accuracy of the resulting model. In addition, few have continued on to analyze these factors' impact on MPC controller performance in terms of final operating costs. Therefore, this study first identifies the practical factors affecting model setup, specifically focusing on the thermal envelope. The seven that are identified are building design, model structure, model order, data set, data quality, identification algorithm and initial guesses, and software tool-chain. Then, through a large number of trials, it analyzes each factor's influence on model accuracy, focusing on grey-box models for a single zone building envelope. Finally, this study implements a subset of the models identified with these factor variations in heating, ventilating, and air conditioning MPC controllers, and tests them in simulation of a representative case that aims to optimally cool a single-zone building with time-varying electricity prices. It is found that a difference of up to 20% in cooling cost for the cases studied can occur between the best performing model and the worst performing model. The primary factors attributing to this were model structure and initial parameter guesses during parameter estimation of the model.

10abuilding simulation10ahvac10aModel predictive control10aSystem identification1 aBlum, David1 aArendt, K.1 aRivalin, Lisa1 aPiette, Mary, Ann1 aWetter, Michael1 aVeje, C.T. uhttps://linkinghub.elsevier.com/retrieve/pii/S0306261918318099https://api.elsevier.com/content/article/PII:S0306261918318099?httpAccept=text/xmlhttps://api.elsevier.com/content/article/PII:S0306261918318099?httpAccept=text/plain02376nas a2200241 4500008004100000022001300041245008400054210006900138260001200207300001200219490000800231520164800239653001801887653003501905653001901940653001501959653001501974653002301989100001402012700001902026700002202045856006702067 2019 eng d a0360544200aPredicting plug loads with occupant count data through a deep learning approach0 aPredicting plug loads with occupant count data through a deep le c05/2019 a29 - 420 v1813 a

Predictive control has gained increasing attention for its ability to reduce energy consumption and improve occupant comfort in buildings. The plug loads prediction is a key component for the predictive building controls, as plug loads is a major source of internal heat gains in buildings. This study proposed a novel method to apply the Long-Short-Term-Memory (LSTM) Network, a special form of Recurrent Neural Network, to predict plug loads. The occupant count and the time have been confirmed to drive the plug load profile and thus selected as the features for the plug load prediction. The LSTM network was trained and tested with ground truth occupant count data collected from a real office building in Berkeley, California. Results from the LSTM network markedly improve the prediction accuracy compared with traditional linear regression methods and the classical Artificial Neural Network. 95% of 1-h predictions from LSTM network are within ±1 kW of the actual plug loads, given the average plug loads during the office hour is 8.6 kW. The CV(RMSE) of the predicted plug load is 11% for the next hour, and 20% for the next 8 h. Lastly, we compared four prediction approaches with the office building we monitored: LSTM vs. ARIMA, with occupant counts vs. without occupant counts. It was found, the prediction error of the LSTM approach is around 4% less than the ARIMA approach. Using occupant counts as an exogenous input could further reduce the prediction error by 5%–6%. The findings of this paper could shed light on the plug load prediction for building control optimizations such as model-predictive control.

10adeep learning10aLong short term memory network10aOccupant count10aPlug loads10aprediction10aPredictive control1 aWang, Zhe1 aHong, Tianzhen1 aPiette, Mary, Ann uhttps://linkinghub.elsevier.com/retrieve/pii/S036054421931020502188nas a2200301 4500008004100000245011100041210006900152260001600221520124300237653001701480653002401497653002901521653002501550100001601575700002001591700001501611700001401626700001901640700001601659700001501675700002001690700001801710700001801728700002001746700002001766700001801786856008201804 2019 eng d00aPrototyping the BOPTEST Framework for Simulation-Based Testing of Advanced Control Strategies in Buildings0 aPrototyping the BOPTEST Framework for SimulationBased Testing of aRome, Italy3 a

Advanced control strategies are becoming increasingly necessary in buildings in order to meet and balance requirements for energy efficiency, demand flexibility, and occupant comfort. Additional development and widespread adoption of emerging control strategies, however, ultimately require low implementation costs to reduce payback period and verified performance to gain control vendor, building owner, and operator trust. This is difficult in an already first-cost driven and risk-averse industry. Recent innovations in building simulation can significantly aid in meeting these requirements and spurring innovation at early stages of development by evaluating performance, comparing state-of-the-art to new strategies, providing installation experience, and testing controller implementations. This paper presents the development of a simulation framework consisting of test cases and software platform for the testing of advanced control strategies (BOPTEST - Building Optimization Performance Test). The objectives and requirements of the framework, components of a test case, and proposed software platform architecture are described, and the framework is demonstrated with a prototype implementation and example test case.

10abenchmarking10abuilding simulation10aModel predictive control10asoftware development1 aBlum, David1 aJorissen, Filip1 aHuang, Sen1 aChen, Yan1 aArroyo, Javier1 aBenne, Kyle1 aLi, Yanfei1 aGavan, Valentin1 aRivalin, Lisa1 aHelsen, Lieve1 aVrabie, Draguna1 aWetter, Michael1 aSofos, Marina uhttps://simulationresearch.lbl.gov/publications/prototyping-boptest-framework00428nas a2200133 4500008004100000245003700041210003700078260001200115653003300127653001300160100002000173700001600193856008500209 2019 eng d00aQuayside Energy Systems Analysis0 aQuayside Energy Systems Analysis c03/201910aDistrict Heating and cooling10amodelica1 aWetter, Michael1 aHu, Jianjun uhttps://simulationresearch.lbl.gov/publications/quayside-energy-systems-analysis01789nas a2200205 4500008004100000245013500041210006900176260001600245300000900261490000700270520100200277653012101279100001701400700001801417700001401435700001301449700001901462700001101481856009101492 2019 eng d00aRevealing Urban Morphology and Outdoor Comfort through Genetic Algorithm-Driven Urban Block Design in Dry and Hot Regions of China0 aRevealing Urban Morphology and Outdoor Comfort through Genetic A cJan-07-2019 a36830 v113 a

In areas with a dry and hot climate, factors such as strong solar radiation, high temperature, low humidity, dazzling light, and dust storms can tremendously reduce people’s thermal comfort. Therefore, researchers are paying more attention to outdoor thermal comfort in urban environments as part of urban design. This study proposed an automatic workflow to optimize urban spatial forms with the aim of improvement of outdoor thermal comfort conditions, characterized by the universal thermal climate index (UTCI). A city with a dry and hot climate—Kashgar, China—is further selected as an actual case study of an urban block and Rhino & Grasshopper is the platform used to conduct simulation and optimization process with the genetic algorithm. Results showed that in summer, the proposed method can reduce the averaged UTCI from 31.17 to 27.43 °C, a decrease of about 3.74 °C, and reduce mean radiation temperature (MRT) from 43.94 to 41.29 °C, a decrease of about 2.65 °C.

10adry and hot areas; outdoor thermal comfort; urban morphology; urban performance simulation; genetic algorithm-driven1 aXu, Xiaodong1 aYin, Chenhuan1 aWang, Wei1 aXu, Ning1 aHong, Tianzhen1 aLi, Qi uhttps://www.mdpi.com/2071-1050/11/13/3683https://www.mdpi.com/2071-1050/11/13/3683/pdf01980nas a2200277 4500008004100000022001300041245009800054210006900152260001200221300001400233490000800247520110300255653002201358653004301380653002401423653002601447653003401473653002101507653002001528100001401548700002201562700001601584700001601600700001901616856006701635 2019 eng d a0360132300aThe Squeaky wheel: Machine learning for anomaly detection in subjective thermal comfort votes0 aSqueaky wheel Machine learning for anomaly detection in subjecti c03/2019 a219 - 2270 v1513 a

Anomalous patterns in subjective votes can bias thermal comfort models built using data-driven approaches. A stochastic-based two-step framework to detect outliers in subjective thermal comfort data is proposed to address this problem. The anomaly detection technique involves defining similar conditions using a k-Nearest Neighbor (KNN) method and then quantifying the dissimilarity of the occupants' votes from their peers under similar thermal conditions through a Multivariate Gaussian approach. This framework is used to detect outliers in the ASHRAE Global Thermal Comfort Database I & II. The resulting anomaly-free dataset produced more robust comfort models avoiding dubious predictions. The proposed method has been proven to effectively distinguish outliers from inter-individual variabilities in thermal demand. The proposed anomaly detection framework could easily be applied to other applications with different variables or subjective metrics. Such a tool holds great promise for use in the development of occupancy responsive controls for automated building HVAC systems.

10aanomaly detection10aASHRAE global thermal comfort database10aK-nearest neighbors10aMultivariate Gaussian10aOccupancy responsive controls10aSubjective votes10athermal comfort1 aWang, Zhe1 aParkinson, Thomas1 aLi, Peixian1 aLin, Borong1 aHong, Tianzhen uhttps://linkinghub.elsevier.com/retrieve/pii/S036013231930086101724nas a2200229 4500008004100000022001300041245006000054210006000114260001600174300001100190490000800201520104600209653002201255653001501277653001701292653002601309653001801335653001601353100002001369700001901389856008601408 2019 eng d a0360132300aValidation of an inverse model of zone air heat balance0 aValidation of an inverse model of zone air heat balance cJan-08-2019 a1062320 v1613 a

This paper presents the validation method and results of an inverse model of zone air heat balance. The inverse model, implemented in EnergyPlus and published in a previous article [1], calculates highly uncertain model parameters such as internal thermal mass and infiltration airflow by inversely solving the zone air heat balance equation using the easy-to-measure zone air temperature data. The paper provides technical details of validation from the experiments using LBNL’s Facility for Low Energy eXperiment in Buildings (FLEXLAB) that measures zone air temperature under the controlled experiment of two levels of internal mass and four levels of infiltration airflow. The simulation results of the zone infiltration airflow and internal thermal mass from the inverse model agree well with the measured data from the FLEXLAB experiments. The validated inverse model in EnergyPlus can be used to enhance the energy modeling of existing buildings that enables energy performance assessments for energy efficiency improvements.

10aEnergy simulation10aenergyplus10ainfiltration10ainternal thermal mass10ainverse model10asensor data1 aLee, Sang, Hoon1 aHong, Tianzhen uhttps://simulationresearch.lbl.gov/publications/validation-inverse-model-zone-air00542nas a2200133 4500008004100000245013400041210006900175490000800244100001900252700002000271700001800291700001700309856008200326 2018 eng d00aBidirectional low temperature district energy systems with agent-based control: Performance comparison and operation optimization0 aBidirectional low temperature district energy systems with agent0 v2091 aBunning, Felix1 aWetter, Michael1 aFuchs, Marcus1 aMuller, Dirk uhttps://simulationresearch.lbl.gov/publications/bidirectional-low-temperature01824nas a2200205 4500008004100000245004000041210003900081490000700120520119400127653002401321653002401345653003601369653002201405653002001427653003001447100001901477700002001496700001501516856008701531 2018 eng d00aBuilding Simulation: Ten Challenges0 aBuilding Simulation Ten Challenges0 v113 a

Buildings consume more than one-third of the world’s primary energy. Reducing energy use and greenhouse-gas emissions in the buildings sector through energy conservation and efficiency improvements constitutes a key strategy for achieving global energy and environmental goals. Building performance simulation has been increasingly used as a tool for designing, operating and retrofitting buildings to save energy and utility costs. However, opportunities remain for researchers, software developers, practitioners and policymakers to maximize the value of building performance simulation in the design and operation of low energy buildings and communities that leverage interdisciplinary approaches to integrate humans, buildings, and the power grid at a large scale. This paper presents ten challenges that highlight some of the most important issues in building performance simulation, covering the full building life cycle and a wide range of modeling scales. The formulation and discussion of each challenge aims to provide insights into the state-of-the-art and future research opportunities for each topic, and to inspire new questions from young researchers in this field.

10abuilding energy use10abuilding life cycle10abuilding performance simulation10aenergy efficiency10aenergy modeling10azero-net-energy buildings1 aHong, Tianzhen1 aLangevin, Jared1 aSun, Kaiyu uhttps://simulationresearch.lbl.gov/publications/building-simulation-ten-challenges01905nas a2200217 4500008004100000022001400041245009000055210006900145260001200214300001100226520113500237653001301372653003101385653003101416653002301447653003301470100001401503700001901517700001501536856013601551 2018 eng d a1940-149300aBuildings.Occupants: a Modelica package for modelling occupant behaviour in buildings0 aBuildingsOccupants a Modelica package for modelling occupant beh c11/2018 a1 - 123 a

Energy-related occupant behaviour is crucial to design and operation of energy and control systems in buildings. Occupant behaviours are often oversimplified as static schedules or settings in building performance simulation ignoring their stochastic nature. The continuous and dynamic interaction between occupants and building systems motivates their simultaneous simulation in an efficient manner. In the past, simultaneous simulation has relied on co-simulation approaches or customized source code changes to building simulation programmes. This paper presents Buildings. Occupants, an open-source package implemented in Modelica, for the simulation of occupant behaviours of lighting, windows, blinds, heating and air conditioning systems in office and residential buildings. Examples were presented to illustrate how the models in the Occupants package are capable to simulate stochastic occupant behaviours. The major contribution of this work is to introduce the equation-based modelling approach to simulate occupant behaviours in buildings and to develop an open-source Occupants package in the Modelica language

10amodelica10aModelica Buildings Library10aModelica Occupants Package10aOccupant Behaviour10aOccupant behaviour modelling1 aWang, Zhe1 aHong, Tianzhen1 aJia, Ruoxi uhttps://www.tandfonline.com/doi/full/10.1080/19401493.2018.1543352https://www.tandfonline.com/doi/pdf/10.1080/19401493.2018.154335202762nas a2200241 4500008004100000022001300041245011200054210006900166260001200235300001400247490000800261520184900269653002602118653002102144653002402165653000902189653002502198653001602223100001702239700001202256700001902268856023302287 2018 eng d a0378778800aClustering and statistical analyses of air-conditioning intensity and use patterns in residential buildings0 aClustering and statistical analyses of airconditioning intensity c09/2018 a214 - 2270 v1743 a

Energy conservation in residential buildings has gained increased attention due to its large portion of global energy use and potential of energy savings. Occupant behavior has been recognized as a key factor influencing the energy use and load diversity in buildings, therefore more realistic and accurate air-conditioning (AC) operating schedules are imperative for load estimation in equipment design and operation optimization. With the development of sensor technology, it became easier to access an increasing amount of heating/cooling data from thermal energy metering systems in residential buildings, which provides another possible way to understand building energy usage and occupant behaviors. However, except for cooling energy consumption benchmarking, there currently lacks effective and easy approaches to analyze AC usage and provide actionable insights for occupants. To fill this gap, this study proposes clustering analysis to identify AC use patterns of residential buildings, and develops new key performance indicators (KPIs) and data analytics to explore the AC operation characteristics using the long-term metered cooling energy use data, which is of great importance for inhabitants to understand their thermal energy use and save energy cost through adjustment of their AC use behavior. We demonstrate the proposed approaches in a residential district comprising 300 apartments, located in Zhengzhou, China. Main outcomes include: Representative AC use patterns are developed for three room types of residential buildings in the cold climate zone of China, which can be used as more realistic AC schedules to improve accuracy of energy simulation; Distributions of KPIs on household cooling energy usage are established, which can be used for household AC use intensity benchmarking and performance diagnoses.

10aAC usage benchmarking10aAir-conditioning10aClustering analysis10aKPIs10aresidential building10aUse pattern1 aAn, Jingjing1 aYan, Da1 aHong, Tianzhen uhttps://linkinghub.elsevier.com/retrieve/pii/S0378778818307199https://api.elsevier.com/content/article/PII:S0378778818307199?httpAccept=text/xmlhttps://api.elsevier.com/content/article/PII:S0378778818307199?httpAccept=text/plain01954nas a2200241 4500008004100000245009500041210006900136490000800205520119700213653002201410653001201432653002301444653002201467653002101489653002501510100001401535700001201549700001701561700001901578700001401597700001401611856008701625 2018 eng d00aComparative Study of Air-Conditioning Energy Use of Four Office Buildings in China and USA0 aComparative Study of AirConditioning Energy Use of Four Office B0 v1693 a

Energy use in buildings has great variability. In order to design and operate low energy buildings as well as to establish building energy codes and standards and effective energy policy, it is crucial to understand and quantify key factors influencing building energy performance. This study investigates air-conditioning (AC) energy use of four office buildings in four locations: Beijing, Taiwan, Hong Kong, and Berkeley. Building simulation was employed to quantify the influences of key factors, including climate, building envelope and occupant behavior. Through simulation of various combinations of the three influencing elements, it is found that climate can lead to AC cooling consumption differences by almost two times, while occupant behavior resulted in the greatest differences (of up to three times) in AC cooling consumption. The influence of occupant behavior on AC energy consumption is not homogeneous. Under similar climates, when the occupant behavior in the building differed, the optimized building envelope design also differed. Overall, the optimal building envelope should be determined according to the climate as well as the occupants who use the building.

10aBuilding envelope10aclimate10aenergy consumption10aoccupant behavior10aoffice buildings10atechnological choice1 aZhou, Xin1 aYan, Da1 aAn, Jingjing1 aHong, Tianzhen1 aShi, Xing1 aJin, Xing uhttps://simulationresearch.lbl.gov/publications/comparative-study-air-conditioning02289nas a2200169 4500008004100000245003300041210003300074260001200107520180900119653001401928653001301942653000901955100002001964700002101984700001602005856009802021 2018 eng d00aControl Description Language0 aControl Description Language c08/20183 a

Properly designed and implemented building control sequences can significantly reduce energy consumption. However, there is currently no process with supporting tools that allows the assessment of the performance of different control sequences, export the control sequences in a vendor-neutral format for cost estimation and for implementation on a building automation system through machine-to-machine translation, and reuse the sequences for verification during commissioning.

This paper describes a Control Description Language (CDL) that we developed to create such a process. For CDL, we selected a subset of Modelica that allows a convenient representation of control sequences, simulation of the control sequence coupled to a building energy model, and development of translators from CDL to building automation systems. To aid in the development of such translators, we created a translator from CDL to a JSON intermediate format. In future work, we seek to work with building control providers to develop translators from CDL to commercial building automation systems.

Through a case study, we show that CDL suffices for simulation-based performance assessment of two ASHRAE-published control sequences for a variable air volume flow system of an office building. Moreover, the case study showed that merely due to differences in the control sequences, annual HVAC energy use was reduced by 30%. This difference is larger than the accuracy required when comparing different HVAC systems, thereby questioning the current practice of idealizing control sequences in building energy simulations, and demonstrating the importance of ensuring that the control sequence used during design simulations corresponds to the control sequence that will be implemented in the real building

10abuildings10acontrols10ahvac1 aWetter, Michael1 aGrahovac, Milica1 aHu, Jianjun uhttps://simulationresearch.lbl.gov/wetter/download/2018-americanModelica-WetterGrahovacHu.pdf02422nas a2200217 4500008004100000022001400041245009700055210006900152260001200221300000900233520152700242653002301769653002201792653002801814653002201842653002501864100001901889700001901908700001801927856025901945 2018 eng d a1570-646X00aA critical review on questionnaire surveys in the field of energy-related occupant behaviour0 acritical review on questionnaire surveys in the field of energyr c07/2018 a1-213 a

Occupants perform various actions to satisfy their physical and non-physical needs in buildings. These actions greatly affect building operations and thus energy use. Clearly understanding and accurately modelling occupant behaviour in buildings are crucial to guide energy-efficient building design and operation, and to reduce the gap between design and actual energy performance of buildings. To study and understand occupant behaviour, a cross-sectional questionnaire survey is one of the most useful tools to gain insights on general behaviour patterns and drivers, and to find connections between human, social and local comfort parameters. In this study, 33 projects were reviewed from the energy-related occupant behaviour research literature that employed cross-sectional surveys or interviews for data collection from the perspective of findings, limitations and methodological challenges. This research shows that future surveys are needed to bridge the gaps in literature but they would need to encompass a multidisciplinary approach to do so as until now only environmental and engineering factors were considered in these studies. Insights from social practice theories and techniques must be acquired to deploy robust and unbiased questionnaire results, which will provide new, more comprehensive knowledge in the field, and therefore occupant behaviour could be better understood and represented in building performance simulation to support design and operation of low or net-zero energy buildings.

10abehaviour modeling10aenergy efficiency10aEnergy use in buildings10aoccupant behavior10aquestionnaire survey1 aBelafi, Zsofia1 aHong, Tianzhen1 aReith, Andras uhttp://link.springer.com/10.1007/s12053-018-9711-zhttp://link.springer.com/content/pdf/10.1007/s12053-018-9711-z.pdfhttp://link.springer.com/content/pdf/10.1007/s12053-018-9711-z.pdfhttp://link.springer.com/article/10.1007/s12053-018-9711-z/fulltext.html03134nas a2200241 4500008004100000022001300041245011500054210006900169260001200238300001400250490000800264520230200272653005802574653001602632653002102648653002102669653004902690653001302739100001802752700001802770700002102788856008302809 2018 eng d a0378778800aEfficient modeling of optically-complex, non-coplanar exterior shading: Validation of matrix algebraic methods0 aEfficient modeling of opticallycomplex noncoplanar exterior shad c09/2018 a464 - 4830 v1743 a

It has long been established that shading windows with overhangs, fins, and other types of non-coplanar systems (NCS) is one of the most effective ways of controlling solar heat gains in buildings because they intercept solar radiation prior to entry into the building. Designers however often specify non-opaque materials (e.g., louvers, fritted glass, expanded metal mesh) for these systems in order to admit daylight, reduce lighting energy use, and improve indoor environmental quality. Most simulation tools rely on geometric calculations and radiosity methods to model the solar heat gain impacts of NCS and cannot model optically-complex materials or geometries. For daylighting analysis, optically-complex NCS can be modeled using matrix algebraic methods, although time-efficient parametric analysis has not yet been implemented. Determining the best design and/or material for static or operable NCS that minimize cooling, heating, and lighting energy use and peak demand requires an iterative process. This study describes and validates a matrix algebraic method that enables parametric energy analysis of NCS. Such capabilities would be useful not only for design but also for development of prescriptive energy-efficiency standards, rating and labeling systems for commercial products, development of design guidelines, and development of more optimal NCS technologies.

A facade or "F" matrix, which maps the transfer of flux from the NCS to the surface of the window, is introduced and its use is explained. A field study was conducted in a full-scale outdoor testbed to measure the daylight performance of an operable drop-arm awning. Simulated data were compared to measured data in order to validate the models. Results demonstrated model accuracy: simulated workplane illuminance was within 11-13%, surface luminance was within 16-18%, and the daylight glare probability was within 6-9% of measured results. Methods used to achieve accurate results are discussed. Results of the validation of daylighting performance are applicable to solar heat gain performance. Since exterior shading can also significantly reduce peak demand, these models enable stakeholders to more accurately assess HVAC and lighting impacts in support of grid management and resiliency goals.

10abidirectional scattering distribution function (BSDF)10adaylighting10aexterior shading10asolar heat gains10avalidation; building energy simulation tools10awindows.1 aWang, Taoning1 aWard, Gregory1 aLee, Eleanor, S. uhttps://www.sciencedirect.com/science/article/pii/S0378778818302457?via%3Dihub02000nas a2200253 4500008004100000022001300041245010400054210006900158260001200227300001100239490000700250520118500257653002701442653001801469653001601487653002501503653002001528100003001548700001501578700001901593700001901612700002901631856008601660 2018 eng d a1550485900aA Framework for Privacy-Preserving Data Publishing with Enhanced Utility for Cyber-Physical Systems0 aFramework for PrivacyPreserving Data Publishing with Enhanced Ut c12/2018 a1 - 220 v143 a

Cyber-physical systems have enabled the collection of massive amounts of data in an unprecedented level of spatial and temporal granularity. Publishing these data can prosper big data research, which, in turn, helps improve overall system efficiency and resiliency. The main challenge in data publishing is to ensure the usefulness of published data while providing necessary privacy protection. In our previous work (Jia et al. 2017a), we presented a privacy-preserving data publishing framework (referred to as PAD hereinafter), which can guarantee k-anonymity while achieving better data utility than traditional anonymization techniques. PAD learns the information of interest to data users or features from their interactions with the data publishing system and then customizes data publishing processes to the intended use of data. However, our previous work is only applicable to the case where the desired features are linear in the original data record. In this article, we extend PAD to nonlinear features. Our experiments demonstrate that for various data-driven applications, PAD can achieve enhanced utility while remaining highly resilient to privacy threats.

10acyber physical systems10adeep learning10ak-anonymity10aPrivacy preservation10aSmart buildings1 aSangogboye, Fisayo, Caleb1 aJia, Ruoxi1 aHong, Tianzhen1 aSpanos, Costas1 aKjærgaard, Mikkel, Baun uhttps://simulationresearch.lbl.gov/publications/framework-privacy-preserving-data02513nas a2200241 4500008004100000245010500041210006900146490000800215520166100223653003101884653003301915653003201948653002201980653002102002653002502023100001802048700002502066700002402091700002702115700001902142700002602161856008402187 2018 eng d00aHuman-building interaction at work: Findings from an interdisciplinary cross-country survey in Italy0 aHumanbuilding interaction at work Findings from an interdiscipli0 v1323 a

This study presents results from an interdisciplinary survey assessing contextual and behavioral factors driving occupants' interaction with building and systems in offices located across three different Mediterranean climates in Turin (Northern), Perugia (Central), and Rende (Southern) Italy. The survey instrument is grounded in an interdisciplinary framework that bridges the gap between building physics and social science environments on the energy- and comfort-related human-building interaction in the workspace. Outcomes of the survey questionnaire provide insights into four key learning objectives: (1) individual occupant's motivational drivers regarding interaction with shared building environmental controls (such as adjustable thermostats, operable windows, blinds and shades, and artificial lighting), (2) group dynamics such as perceived social norms, attitudes, and intention to share controls, (3) occupant perception of the ease of use and knowledge of how to operate control systems, and (4) occupant-perceived comfort, satisfaction, and productivity. This study attempts to identify climatic, cultural, and socio-demographic influencing factors, as well as to establish the validity of the survey instrument and robustness of outcomes for future studies. Also, the paper aims at illustrating why and how social science insights can bring innovative knowledge into the adoption of building technologies in shared contexts, thus enhancing perceived environmental satisfaction and effectiveness of personal indoor climate control in office settings and impacting office workers' productivity and reduced operational energy costs.

10aHuman-building interaction10aindoor environmental comfort10ainterdisciplinary framework10aoccupant behavior10aoffice buildings10aquestionnaire survey1 aD'Oca, Simona1 aPisello, Anna, Laura1 aDe Simone, Marilena1 aBarthelmes, Verena, M.1 aHong, Tianzhen1 aCorgnati, Stefano, P. uhttps://simulationresearch.lbl.gov/publications/human-building-interaction-work02294nas a2200265 4500008004100000022001300041245010900054210006900163260001200232300001400244490000800258520131500266653003101581653001701612653001501629653002401644653001901668653002201687100001501709700002001724700001901744700001401763700001801777856023301795 2018 eng d a1359431100aImpact of post-rainfall evaporation from porous roof tiles on building cooling load in subtropical China0 aImpact of postrainfall evaporation from porous roof tiles on bui c09/2018 a391 - 4000 v1423 a

Rainfall occurs frequently in subtropical regions of China, with the subsequent water evaporation from building roofs impacting the thermal performance and the energy consumption of buildings. We proposed a novel simulation method using actual meteorological data to evaluate this impact. New features were developed in EnergyPlus to enable the simulation: (1) an evaporation latent heat flux source term was added to the heat balance equation of the external surface and (2) algorithms for the evaporative cooling module (ECM) were developed and implemented into EnergyPlus. The ECM experimental results showed good agreement with the simulated results. The ECM was used to assess the impact of evaporation from porous roof tiles on the cooling load of a one-floor building in subtropical China. The results show that the evaporation process decreased the maximal values of the external and internal roof surface temperatures by up to 6.4 °C and 3.2 °C, respectively, while the lower internal surface temperature decreased the room accumulated cooling load by up to 14.8% during the hot summer period. The enhanced EnergyPlus capability can be used to evaluate the evaporative cooling performance of roofs with water-storage mediums, as well as to quantify their impact on building cooling loads.

10aBuilding energy simulation10acooling load10aenergyplus10aEvaporative Cooling10aRainfall event10aSubtropical China1 aZhang, Lei1 aZhang, Rongpeng1 aHong, Tianzhen1 aZhang, Yu1 aMeng, Qinglin uhttps://linkinghub.elsevier.com/retrieve/pii/S1359431117356107https://api.elsevier.com/content/article/PII:S1359431117356107?httpAccept=text/xmlhttps://api.elsevier.com/content/article/PII:S1359431117356107?httpAccept=text/plain02692nas a2200193 4500008004100000245010800041210006900149490000800218520202000226653001202246653001502258653002102273653002802294653003502322653001802357100001702375700001902392856008702411 2018 eng d00aImpacts of Building Geometry Modeling Methods on the Simulation Results of Urban Building Energy Models0 aImpacts of Building Geometry Modeling Methods on the Simulation 0 v2153 a

Urban-scale building energy modeling (UBEM)—using building modeling to understand how a group of buildings will perform together—is attracting increasing attention in the energy modeling field. Unlike modeling a single building, which will use detailed information, UBEM generally uses existing building stock data consisting of high-level building information. This study evaluated the impacts of three zoning methods and the use of floor multipliers on the simulated energy use of 940 office and retail buildings in three climate zones using City Building Energy Saver. The first zoning method, OneZone, creates one thermal zone per floor using the target building’s footprint. The second zoning method, AutoZone, splits the building’s footprint into perimeter and core zones. A novel, pixel-based automatic zoning algorithm is developed for the AutoZone method. The third zoning method, Prototype, uses the U.S. Department of Energy’s reference building prototype shapes. Results show that simulated source energy use of buildings with the floor multiplier are marginally higher by up to 2.6% than those modeling each floor explicitly, which take two to three times longer to run. Compared with the AutoZone method, the OneZone method results in decreased thermal loads and less equipment capacities: 15.2% smaller fan capacity, 11.1% smaller cooling capacity, 11.0% smaller heating capacity, 16.9% less heating loads, and 7.5% less cooling loads. Source energy use differences range from -7.6% to 5.1%. When comparing the Prototype method with the AutoZone method, source energy use differences range from -12.1% to 19.0%, and larger ranges of differences are found for the thermal loads and equipment capacities. This study demonstrated that zoning methods have a significant impact on the simulated energy use of UBEM. One recommendation resulting from this study is to use the AutoZone method with floor multiplier to obtain accurate results while balancing the simulation run time for UBEM.

10aCityBES10aenergyplus10aFloor multiplier10aGeometry Representation10aUrban Building Energy Modeling10aZoning Method1 aChen, Yixing1 aHong, Tianzhen uhttps://simulationresearch.lbl.gov/publications/impacts-building-geometry-modeling02103nas a2200181 4500008004100000245008900041210006900130520146500199653003601664653001001700653002301710653002901733653001501762100001901777700001901796700001801815856008801833 2018 eng d00aA Library of Building Occupant Behaviour Models Represented in a Standardised Schema0 aLibrary of Building Occupant Behaviour Models Represented in a S3 a

Over the past four decades, a substantial body of literature has explored the impacts of occupant behaviour (OB) on building technologies, operation, and energy consumption. A large number of data-driven behavioural models have been developed based on field data. These models lack standardisation and consistency, leading to difficulties in applications and comparison. To address this problem, an ontology was developed using the drivers-needs-actions-systems (DNAS) framework. Recent work has been carried out to implement the theoretical DNAS framework into an eXtensible Markup Language (XML) schema, titled ‘occupant behaviour XML’ (obXML) which is a practical implementation of OB models that can be integrated into building performance simulation (BPS) programs. This paper presents a newly developed library of OB models represented in the standardised obXML schema format. This library provides ready-to-use examples for BPS users to employ more accurate occupant representation in their energy models. The library, which contains an initial effort of 52 OB models, was made publicly available for the BPS community. As part of the library development process, limitations of the obXML schema were identified and addressed, and future improvements were proposed. Authors hope that by compiling this library building, energy modellers from all over the world can enhance their BPS models by integrating more accurate and robust OB patterns.

10abuilding performance simulation10aobXML10aOccupant Behaviour10aoccupant behaviour model10aXML schema1 aBelafi, Zsofia1 aHong, Tianzhen1 aReith, Andras uhttps://simulationresearch.lbl.gov/publications/library-building-occupant-behaviour02433nas a2200193 4500008004100000245009600041210006900137490000800206520175100214653002201965653001501987653004302002653002702045653002802072100001402100700001602114700001902130856009002149 2018 eng d00aModeling occupancy distribution in large spaces with multi-feature classification algorithm0 aModeling occupancy distribution in large spaces with multifeatur0 v1373 a

Occupancy information enables robust and flexible control of heating, ventilation, and air-conditioning (HVAC) systems in buildings. In large spaces, multiple HVAC terminals are typically installed to provide cooperative services for different thermal zones, and the occupancy information determines the cooperation among terminals. However, a person count at room-level does not adequately optimize HVAC system operation due to the movement of occupants within the room that creates uneven load distribution. Without accurate knowledge of the occupants' spatial distribution, the uneven distribution of occupants often results in under-cooling/heating or over-cooling/heating in some thermal zones. Therefore, the lack of high-resolution occupancy distribution is often perceived as a bottleneck for future improvements to HVAC operation efficiency. To fill this gap, this study proposes a multi-feature k-Nearest-Neighbors (k-NN) classification algorithm to extract occupancy distribution through reliable, low-cost Bluetooth Low Energy (BLE) networks. An on-site experiment was conducted in a typical office of an institutional building to demonstrate the proposed methods, and the experiment outcomes of three case studies were examined to validate detection accuracy. One method based on City Block Distance (CBD) was used to measure the distance between detected occupancy distribution and ground truth and assess the results of occupancy distribution. The results show the accuracy when CBD = 1 is over 71.4% and the accuracy when CBD = 2 can reach up to 92.9%.

10aenergy efficiency10aHVAC loads10amulti-feature classification algorithm10aoccupancy distribution10aoccupancy-based control1 aWang, Wei1 aChen, Jiayu1 aHong, Tianzhen uhttps://simulationresearch.lbl.gov/publications/modeling-occupancy-distribution-large02346nas a2200229 4500008004100000245009900041210006900140490000800209520158400217653003601801653001301837653002001850653001801870653001501888653003001903100002001933700001501953700001901968700002001987700002102007856008802028 2018 eng d00aA Novel Variable Refrigerant Flow (VRF) Heat Recovery System Model: Development and Validation0 aNovel Variable Refrigerant Flow VRF Heat Recovery System Model D0 v1683 a

As one of the latest emerging HVAC technologies, the Variable Refrigerant Flow (VRF) system with heat recovery (HR) configurations has obtained extensive attention from both the academia and industry. Compared with the conventional VRF systems with heat pump (HP) configurations, VRF-HR is capable of recovering heat from cooling zones to heating zones and providing simultaneous cooling and heating operations. This can further lead to substantial energy saving potential and more flexible zonal control. In this paper, a novel model is developed to simulate the energy performance of VRF-HR systems. It adheres to a more physics-based development with the ability to simulate the refrigerant loop performance and consider the dynamics of more operational parameters, which is essential for representing more advanced control logics. Another key feature of the model is the introduction of component-level curves for indoor units and outdoor units instead of overall performance curves for the entire system, and thus it requires much fewer user-specified performance curves as model inputs. The validation study shows good agreements between the simulated energy use from the new VRF-HR model and the laboratory measurement data across all operational modes at sub-hourly time steps. The model has been adopted in the official release of the EnergyPlus simulation program since Version 8.6, which enables more accurate and robust assessments of VRF-HR systems to support their applications in energy retrofit of existing buildings or design of zero-net-energy buildings.

10abuilding performance simulation10acontrols10aenergy modeling10aheat recovery10avalidation10aVariable refrigerant flow1 aZhang, Rongpeng1 aSun, Kaiyu1 aHong, Tianzhen1 aYura, Yoshinori1 aHinokuma, Ryohei uhttps://simulationresearch.lbl.gov/publications/novel-variable-refrigerant-flow-vrf02356nas a2200229 4500008004100000022001300041245012200054210006900176260001200245300001400257490000700271520146000278653001601738653002601754653002101780653002501801653001801826100001401844700001601858700001901874856023301893 2018 eng d a0926580500aOccupancy prediction through machine learning and data fusion of environmental sensing and Wi-Fi sensing in buildings0 aOccupancy prediction through machine learning and data fusion of c10/2018 a233 - 2430 v943 a

Occupancy information is crucial to building facility design, operation, and energy efficiency. Many studies propose the use of environmental sensors (such as carbon dioxide, air temperature, and relative humidity sensors) and radio-frequency sensors (Wi-Fi networks) to monitor, assess, and predict occupancy information for buildings. As many methods have been developed and a variety of sensory data sources are available, establishing a proper selection of model and data source is critical to the successful implementation of occupancy prediction systems. This study compared three popular machine learning algorithms, including k-nearest neighbors (kNN), support vector machine (SVM), and artificial neural network (ANN), combined with three data sources, including environmental data, Wi-Fi data, and fused data, to optimize the occupancy models' performance in various scenarios. Three error measurement metrics, the mean average error (MAE), mean average percentage error (MAPE), and root mean squared error (RMSE), have been employed to compare the models' accuracies. Examined with an on-site experiment, the results suggest that the ANN-based model with fused data has the best performance, while the SVM model is more suitable with Wi-Fi data. The results also indicate that, comparing with independent data sources, the fused data set does not necessarily improve model accuracy but shows a better robustness for occupancy prediction.

10adata fusion10aenvironmental sensing10aMachine learning10aoccupancy prediction10aWi-Fi sensing1 aWang, Wei1 aChen, Jiayu1 aHong, Tianzhen uhttps://linkinghub.elsevier.com/retrieve/pii/S0926580518302656https://api.elsevier.com/content/article/PII:S0926580518302656?httpAccept=text/xmlhttps://api.elsevier.com/content/article/PII:S0926580518302656?httpAccept=text/plain02098nas a2200181 4500008004100000022001300041245012600054210006900180260001200249300001400261490000800275520133900283100001401622700001601636700001901652700001201671856023301683 2018 eng d a0360132300aOccupancy prediction through Markov based feedback recurrent neural network (M-FRNN) algorithm with WiFi probe technology0 aOccupancy prediction through Markov based feedback recurrent neu c06/2018 a160 - 1700 v1383 a

Accurate occupancy prediction can improve facility control and energy efficiency of buildings. In recent years, buildings' exiting WiFi infrastructures have been widely studied in the research of occupancy and energy conservation. However, using WiFi to assess occupancy is challenging due to that occupancy information is often characterized stochastically and varies with time and easily disturbed by building components. To overcome such limitations, this study utilizes WiFi probe technology to actively scan WiFi connection requests and responses between access points and network devices of building occupants. With captured signals, this study proposed a Markov based feedback recurrent neural network (M-FRNN) algorithm to model and predict the occupancy profiles. One on-site experiment was conducted to collect ground truth data using camera-based video analysis and the results were used to validate the M-FRNN occupancy prediction model over a 9-day measurement period. From the results, the M-FRNN based occupancy model using WiFi probes shows best accuracies can reach 80.9%, 89.6%, and 93.9% with a tolerance of 2, 3, and 4 occupants respectively. This study demonstrated that WiFi data coupled with stochastic machine learning system can provide a viable alternative to determine a building's occupancy profile.

1 aWang, Wei1 aChen, Jiayu1 aHong, Tianzhen1 aZhu, Na uhttps://linkinghub.elsevier.com/retrieve/pii/S0360132318302464https://api.elsevier.com/content/article/PII:S0360132318302464?httpAccept=text/xmlhttps://api.elsevier.com/content/article/PII:S0360132318302464?httpAccept=text/plain02004nas a2200157 4500008004100000245015700041210006900198260002500267520129500292100002001587700001601607700002101623700001901644700001801663856016501681 2018 eng d00aOpenBuildingControl: Modeling Feedback Control as a Step Towards Formal Design, Specification, Deployment and Verification of Building Control Sequences0 aOpenBuildingControl Modeling Feedback Control as a Step Towards  aChicago, ILc09/20183 a

This paper presents ongoing work to develop tools and a process that will allow building designers to instantiate control sequences, configure them for their project, assess their performance in closed loop building energy simulation, and then export these sequences (i) for the control provider to bid on the project and to implement the sequences through machine-to-machine translation, and (ii) for the commissioning agent to verify their correct implementation.

The paper reports on the following: (i) The specification of a Control Description Language, (ii) its use to implement a subset of the ASHRAE Guideline 36 sequences, released as part of the Modelica Buildings library, (iii) its use in annual closed-loop simulations of a variable air- volume flow system, and (iv) lessons learned regarding simulation of closed-loop control.

In our case study, the Guideline 36 sequences yield 30% lower annual site HYAC energy use, under comparable comfort, than sequences published earlier by ASHRAE. The 30% differences in annual HYAC energy consumption due to changes in the control sequences raises the question of whether the idealization of control sequences that is common practice in today's building energy simulation leads to trustworthy energy use predictions.

1 aWetter, Michael1 aHu, Jianjun1 aGrahovac, Milica1 aEubanks, Brent1 aHaves, Philip uhttps://www.ashrae.org/File%20Library/Conferences/Specialty%20Conferences/2018%20Building%20Performance%20Analysis%20Conference%20and%20SimBuild/Papers/C107.pdf01861nas a2200241 4500008004100000245010500041210006900146260001200215300000900227490000700236520110600243653001701349653002101366653002701387653002201414653001101436100001701447700001601464700001401480700001901494700001701513856008901530 2018 eng d00aPerformance-Based Evaluation of Courtyard Design in China’s Cold-Winter Hot-Summer Climate Regions0 aPerformanceBased Evaluation of Courtyard Design in China s ColdW c10/2018 a39500 v103 a

Evaluates the performance of the traditional courtyard design of the Jiangnan Museum, located in Jiangsu Province. In the evaluation, the spatial layout of courtyards is adjusted, the aspect ratio is changed, and an ecological buffer space is created. To model and evaluate the performance of the courtyard design, this study applied the Computational fluid dynamics (CFD) software, Parabolic Hyperbolic Or Elliptic Numerical Integration Code Series (PHOENICS), for wind environment simulation, and the EnergyPlus-based software, DesignBuilder, for energy simulation. Results show that a good combination of courtyard layout and aspect ratio can improve the use of natural ventilation by increasing free cooling during hot summers and reducing cold wind in winters. The results also show that ecological buffer areas of a courtyard can reduce cooling loads in summer by approximately 19.6% and heating loads in winter by approximately 22.3%. The study provides insights into the optimal design of a courtyard to maximize its benefit in regulating the microclimate during both winter and summer.

10aaspect ratio10acourtyard design10aecological buffer area10aecological effect10alayout1 aXu, Xiaodong1 aLuo, Fenlan1 aWang, Wei1 aHong, Tianzhen1 aFu, Xiuzhang uhttp://www.mdpi.com/2071-1050/10/11/3950http://www.mdpi.com/2071-1050/10/11/3950/pdf02081nas a2200217 4500008004100000245010200041210006900143490000800212520134200220653002201562653002401584653003301608653001901641653002201660653002201682100002101704700001501725700001901740700002201759856008201781 2018 eng d00aQuantifying the benefits of a building retrofit using an integrated system approach: A case study0 aQuantifying the benefits of a building retrofit using an integra0 v1593 a

Building retrofits provide a large opportunity to significantly reduce energy consumption in the buildings sector. Traditional building retrofits focus on equipment upgrades, often at the end of equipment life or failure, and result in replacement with marginally improved similar technology and limited energy savings. The Integrated System (IS) retrofit approach enables much greater energy savings by leveraging interactive effects between end use systems, enabling downsized or lower energy technologies. This paper presents a case study in Hawaii quantifying the benefits of an IS retrofit approach compared to two traditional retrofit approaches: a Standard Practice of upgrading equipment to meet minimum code requirements, and an Improved Practice of upgrading equipment to a higher efficiency. The IS approach showed an energy savings of 84% over existing building energy use, much higher than the traditional approaches of 13% and 33%. The IS retrofit also demonstrated the greatest energy cost savings potential. While the degree of savings realized from the IS approach will vary by building and climate, these findings indicate that savings on the order of 50% and greater are not possible without an IS approach. It is therefore recommended that the IS approach be universally adopted to achieve deep energy savings.

10aBuilding retrofit10abuilding simulation10aEnergy conservation measures10aenergy savings10aintegrated design10aintegrated system1 aRegnier, Cynthia1 aSun, Kaiyu1 aHong, Tianzhen1 aPiette, Mary, Ann uhttps://simulationresearch.lbl.gov/publications/quantifying-benefits-building01823nas a2200241 4500008004100000022001400041245009000055210006900145260001200214300001100226520103500237653001301272653002001285653001501305653002701320653000801347100001701355700001401372700001901386700001901405700002101424856013601445 2018 eng d a1940-149300aRepresentation and evolution of urban weather boundary conditions in downtown Chicago0 aRepresentation and evolution of urban weather boundary condition c11/2018 a1 - 143 a

This study presents a novel computing technique for data exchange and coupling between a high-resolution weather simulation model and a building energy model, with a goal of evaluating the impact of urban weather boundary conditions on energy performance of urban buildings. The Weather Research and Forecasting (WRF) model is initialized with the operational High-Resolution Rapid Refresh (HRRR) dataset to provide hourly weather conditions over the Chicago region. We utilize the building footprint, land use, and building stock datasets to generate building energy models using EnergyPlus. We mapped the building exterior surfaces to local air nodes to import simulated microclimate data and to export buildings' heat emissions to their local environment. Preliminary experiments for a test area in Chicago show that predicted building cooling energy use differs by about 4.7% for the selected date when compared with simulations using TMY weather data and without considering the urban microclimate boundary conditions.

10acoupling10aenergy modeling10aenergyplus10aUrban climate modeling10aWRF1 aJain, Rajeev1 aLuo, Xuan1 aSever, Gökhan1 aHong, Tianzhen1 aCatlett, Charlie uhttps://www.tandfonline.com/doi/full/10.1080/19401493.2018.1534275https://www.tandfonline.com/doi/pdf/10.1080/19401493.2018.153427501432nas a2200121 4500008004100000245005900041210005900100520100900159100002001168700002001188700001801208856008401226 2018 eng d00aSimplifications for hydronic system models in Modelica0 aSimplifications for hydronic system models in Modelica3 a

Building systems and their heating, ventilation and air conditioning ow networks, are becoming increasingly complex. Some building energy simulation tools simulate these ow networks using pressure drop equations. These ow network models typically generate coupled algebraic nonlinear systems of equations, which become increasingly more difficult to solve as their sizes increase. This leads to longer computation times and can cause the solver to fail. These problems also arise when using the equation-based modelling language Modelica and Annex 60 based libraries. This may limit the applicability of the library to relatively small problems unless problems are restructured. This paper discusses two algebraic loop types and presents an approach that decouples algebraic loops into smaller parts, or removes them completely. The approach is applied to a case study model where an algebraic loop of 86 iteration variables is decoupled into smaller parts with a maximum of 5 iteration variables.

1 aJorissen, Filip1 aWetter, Michael1 aHelsen, Lieve uhttps://simulationresearch.lbl.gov/publications/simplifications-hydronic-system02543nas a2200277 4500008004100000022001300041245018600054210006900240260001200309300001400321490000800335520142800343653002701771653002701798653001801825653003601843100001901879700002001898700002201918700002101940700002401961700001301985700001501998700001902013856023302032 2018 eng d a0306261900aTranslating climate change and heating system electrification impacts on building energy use to future greenhouse gas emissions and electric grid capacity requirements in California0 aTranslating climate change and heating system electrification im c09/2018 a522 - 5340 v2253 a

Climate change and increased electrification of space and water heating in buildings can significantly affect future electricity demand and hourly demand profiles, which has implications for electric grid greenhouse gas emissions and capacity requirements. We use EnergyPlus to quantify building energy demand under historical and under several climate change projections of 32 kinds of building prototypes in 16 different climate zones of California and imposed these impacts on a year 2050 electric grid configuration by simulation in the Holistic Grid Resource Integration and Deployment (HIGRID) model. We find that climate change only prompted modest increases in grid resource capacity and negligible difference in greenhouse gas emissions since the additional electric load generally occurred during times with available renewable generation. Heating electrification, however, prompted a 30–40% reduction in greenhouse gas emissions but required significant grid resource capacity increases, due to the higher magnitude of load increases and lack of readily available renewable generation during the times when electrified heating loads occurred. Overall, this study translates climate change and electrification impacts to system-wide endpoint impacts on future electric grid configurations and highlights the complexities associated with translating building-level impacts to electric system-wide impacts.

10aBuilding Energy Demand10aClimate Change Impacts10aelectric grid10aHeating Electrification Effects1 aTarroja, Brian1 aChiang, Felicia1 aAghaKouchak, Amir1 aSamuelsen, Scott1 aRaghavan, Shuba, V.1 aWei, Max1 aSun, Kaiyu1 aHong, Tianzhen uhttps://linkinghub.elsevier.com/retrieve/pii/S0306261918306962https://api.elsevier.com/content/article/PII:S0306261918306962?httpAccept=text/xmlhttps://api.elsevier.com/content/article/PII:S0306261918306962?httpAccept=text/plain01796nas a2200157 4500008004100000245006900041210006800110260001200178520127200190100001601462700001801478700002001496700001601516700002401532856008201556 2018 eng d00aWhen Data Analytics Meet Site Operation: Benefits and Challenges0 aWhen Data Analytics Meet Site Operation Benefits and Challenges c08/20183 a

Demand for using data analytics for energy management in buildings is rising. Such analytics are required for advanced measurement and verification, commissioning, automated fault-detection and diagnosis, and optimal control. While novel analytics algorithms continue to be developed, bottlenecks and challenges arise when deploying them for demonstration, for a number of reasons that do not necessarily have to do with the algorithms themselves. It is important for developers of new technologies to be aware of the challenges and potential solutions during demonstration. Therefore, this paper describes a recent deployment of an automated, physical model-based, FDD and optimal control tool, highlighting its design and as-operated benefits that the tool provides. Furthermore, the paper presents challenges faced during deployment and testing along with solutions used to overcome these challenges. The challenges have been grouped into four categories: Data Management, Physical Model Development and Integration, Software Development and Deployment, and Operator Use. The paper concludes by discussing how challenges with this project generalize to common cases, how they could compare to other projects in their severity, and how they may be addressed.

1 aBlum, David1 aLin, Guanjing1 aSpears, Michael1 aPage, Janie1 aGranderson, Jessica uhttps://simulationresearch.lbl.gov/publications/when-data-analytics-meet-site02102nas a2200121 4500008004100000245005000041210004600091520170800137100001701845700001901862700001401881856008501895 2017 eng d00aAn Agent-Based Stochastic Occupancy Simulator0 aAgentBased Stochastic Occupancy Simulator3 a

Occupancy has significant impacts on building performance. However, in current building performance simulation programs, occupancy inputs are static and lack diversity, contributing to discrepancies between the simulated and actual building performance. This paper presents an Occupancy Simulator that simulates the stochastic behavior of occupant presence and movement in buildings, capturing the spatial and temporal occupancy diversity. Each occupant and each space in the building are explicitly simulated as an agent with their profiles of stochastic behaviors. The occupancy behaviors are represented with three types of models: (1) the status transition events (e.g., first arrival in office) simulated with Reinhart’s LIGHTSWITCH-2002 model, (2) the random moving events (e.g., from one office to another) simulated with Wang’s homogeneous Markov chain model, and (3) the meeting events simulated with a new stochastic model. A hierarchical data model was developed for the Occupancy Simulator, which reduces the amount of data input by using the concepts of occupant types and space types. Finally, a case study of a small office building is presented to demonstrate the use of the Simulator to generate detailed annual sub-hourly occupant schedules for individual spaces and the whole building. The Simulator is a web application freely available to the public and capable of performing a detailed stochastic simulation of occupant presence and movement in buildings. Future work includes enhancements in the meeting event model, consideration of personal absent days, verification and validation of the simulated occupancy results, and expansion for use with residential buildings.

1 aChen, Yixing1 aHong, Tianzhen1 aLuo, Xuan uhttps://simulationresearch.lbl.gov/publications/agent-based-stochastic-occupancy02453nas a2200253 4500008004100000245013600041210006900177260001200246300001200258490000800270520159800278653002101876653002301897653003201920653001601952653001901968653001401987653002502001653001802026100002302044700001902067700002902086856008402115 2017 eng d00aAnalysis of heating load diversity in German residential districts and implications for the application in district heating systems0 aAnalysis of heating load diversity in German residential distric c01/2017 a302-3130 v1393 a

In recent years, the application of district heating systems for the heat supply of residential districts has been increasing in Germany. Central supply systems can be very efficient due to diverse energy demand profiles which may lead to reduced installed equipment capacity. Load diversity in buildings has been investigated in former studies, especially for the electricity demand. However, little is known about the influence of single building characteristics (such as building envelope or hot water demand) on the overall heating peak load of a residential district. For measuring the diversity, the peak load ratio (PLR) index is used to represent the percentage reduction of peak load of a district system from a simple sum of individual peak loads of buildings. A total of 144 residential building load profiles have been created with the dynamic building simulation software IDA ICE for a theoretical analysis in which the PLR reaches 15%. Within this study, certain district features are identified which lead to higher diversity. Furthermore, these results are used in a district heating simulation model which confronts the possible advantage of reduced installed capacity with the practical disadvantage of heat distribution losses.  Likewise, the influence of load density and the district´s building structure can be analyzed. This study shows that especially in districts with high load density, which consist of newly constructed buildings with low supply temperature and high influence of the hot water demand, the advantages of load diversity can be exploited.

10adistrict heating10adomestic hot water10adynamic building simulation10aheat supply10aLoad diversity10apeak load10aresidential district10aspace heating1 aWeissmann, Claudia1 aHong, Tianzhen1 aGraubner, Carl-Alexander uhttps://simulationresearch.lbl.gov/publications/analysis-heating-load-diversity02592nas a2200193 4500008004100000245013700041210006900178520187800247653002902125653001202154653003302166653001502199653002202214653001602236100001702252700001902269700002202288856008802310 2017 eng d00aAutomatic Generation and Simulation of Urban Building Energy Models Based on City Datasets for City-Scale Building Retrofit Analysis0 aAutomatic Generation and Simulation of Urban Building Energy Mod3 a

Buildings in cities consume 30% to 70% of total primary energy, and improving building energy efficiency is one of the key strategies towards sustainable urbanization. Urban building energy models (UBEM) can support city managers to evaluate and prioritize energy conservation measures (ECMs) for investment and the design of incentive and rebate programs. This paper presents the retrofit analysis feature of City Building Energy Saver (CityBES) to automatically generate and simulate UBEM using EnergyPlus based on cities’ building datasets and user-selected ECMs. CityBES is a new open web-based tool to support city-scale building energy efficiency strategic plans and programs. The technical details of using CityBES for UBEM generation and simulation are introduced, including the workflow, key assumptions, and major databases. Also presented is a case study that analyzes the potential retrofit energy use and energy cost savings of five individual ECMs and two measure packages for 940 office and retail buildings in six city districts in northeast San Francisco, United States. The results show that: (1) all five measures together can save 23%-38% of site energy per building; (2) replacing lighting with light-emitting diode lamps and adding air economizers to existing heating, ventilation and air-conditioning (HVAC) systems are most cost-effective with an average payback of 2.0 and 4.3 years, respectively; and (3) it is not economical to upgrade HVAC systems or replace windows in San Franciso due to the city’s mild climate and minimal cooling and heating loads. The CityBES retrofit analysis feature does not require users to have deep knowledge of building systems or technologies for the generation and simulation of building energy models, which helps overcome major technical barriers for city managers and their consultants to adopt UBEM.

10aBuilding Energy Modeling10aCityBES10aEnergy conservation measures10aenergyplus10aRetrofit Analysis10aUrban Scale1 aChen, Yixing1 aHong, Tianzhen1 aPiette, Mary, Ann uhttps://simulationresearch.lbl.gov/publications/automatic-generation-and-simulation02060nas a2200265 4500008004100000245011700041210006900158260001200227300001200239490000800251520123400259653002401493653002401517653001501541653002501556653001801581653001701599100001401616700001201630700001901642700001501661700001401676700001401690856009001704 2017 eng d00aComparison of typical year and multiyear building simulations using a 55-year actual weather data set from China0 aComparison of typical year and multiyear building simulations us c06/2017 a890-9040 v1953 a

Weather has significant impacts on the thermal environment and energy use in buildings. Thus, accurate weather data are crucial for building performance evaluations. Traditionally, typical year data inputs are used to represent long-term weather data. However, there is no guarantee that a single year represents the changing climate well. In this study, the long-term representation of a typical year was assessed by comparing it to a 55-year actual weather data set. To investigate the weather impact on building energy use, 559 simulation runs of a prototype office building were performed for 10 large cities covering all climate zones in China. The analysis results demonstrated that the weather data varied significantly from year to year. Hence, a typical year cannot reflect the variation range of weather fluctuations. Typical year simulations overestimated or underestimated the energy use and peak load in many cases. With the increase in computational power of personal computers, it is feasible and essential to adopt multiyear simulations for full assessments of long-term building performance, as this will improve decision-making by allowing for the full consideration of variations in building energy use.

10aActual weather data10abuilding simulation10aenergy use10aMultiyear simulation10aPeak load  10aTypical year1 aCui, Ying1 aYan, Da1 aHong, Tianzhen1 aXiao, Chan1 aLuo, Xuan1 aZhang, Qi uhttps://simulationresearch.lbl.gov/publications/comparison-typical-year-and-multiyear02405nas a2200217 4500008004100000245009900041210006900140520168500209653001901894653002301913653002301936653002101959653001701980653002701997100001202024700001902036700001202055700001502067700001702082856008802099 2017 eng d00aData Analytics and Optimization of an Ice-Based Energy Storage System for Commercial Buildings0 aData Analytics and Optimization of an IceBased Energy Storage Sy3 a

Ice-based thermal energy storage (TES) systems can shift peak cooling demand and reduce operational energy costs (with time-of-use rates) in commercial buildings. The accurate prediction of the cooling load, and the optimal control strategy for managing the charging and discharging of a TES system, are two critical elements to improving system performance and achieving energy cost savings. This study utilizes data-driven analytics and modeling to holistically understand the operation of an ice–based TES system in a shopping mall, calculating the system’s performance using actual measured data from installed meters and sensors. Results show that there is significant savings potential when the current operating strategy is improved by appropriately scheduling the operation of each piece of equipment of the TES system, as well as by determining the amount of charging and discharging for each day. A novel optimal control strategy, determined by an optimization algorithm of Sequential Quadratic Programming, was developed to minimize the TES system’s operating costs. Three heuristic strategies were also investigated for comparison with our proposed strategy, and the results demonstrate the superiority of our method to the heuristic strategies in terms of total energy cost savings. Specifically, the optimal strategy yields energy costs of up to 11.3% per day and 9.3% per month compared with current operational strategies. A one-day-ahead hourly load prediction was also developed using machine learning algorithms, which facilitates the adoption of the developed data analytics and optimization of the control strategy in a real TES system operation.

10aData Analytics10aenergy cost saving10aheuristic strategy10aMachine learning10aoptimization10aThermal energy storage1 aLuo, Na1 aHong, Tianzhen1 aLi, Hui1 aJia, Rouxi1 aWeng, Wenguo uhttps://simulationresearch.lbl.gov/publications/data-analytics-and-optimization-ice00991nas a2200157 4500008004100000245017100041210006900212260003100281520034200312100001900654700001800673700001800691700001700709700002200726856008500748 2017 eng d00aDevelopment of Automated Procedures to Generate Reference Building Models for ASHRAE Standard 90.1 and India’s Building Energy Code and Implementation in OpenStudio0 aDevelopment of Automated Procedures to Generate Reference Buildi aSan Francisco, CAc08/20173 a

This paper describes a software system for automatically generating a reference (baseline) building energy model from the proposed (as-designed) building energy model. This system is built using the OpenStudio Software Development Kit (SDK) and is designed to operate on building energy models in the OpenStudio file format. 

1 aParker, Andrew1 aHaves, Philip1 aJegi, Subhash1 aGarg, Vishal1 aRavache, Baptiste uhttps://simulationresearch.lbl.gov/publications/development-automated-procedures02289nas a2200217 4500008004100000245009600041210006900137490000800206520155700214100002601771700001801797700002701815700002201842700001801864700002301882700001701905700002901922700002001951700001801971856008201989 2017 eng d00aDynamic equation-based thermo-hydraulic pipe model for district heating and cooling systems0 aDynamic equationbased thermohydraulic pipe model for district he0 v1513 a

Simulation and optimisation of district heating and cooling networks requires efficient and realistic models of the individual network elements in order to correctly represent heat losses or gains, temperature propagation and pressure drops. Due to more recent thermal networks incorporating meshing decentralised heat and cold sources, the system often has to deal with variable temperatures and mass flow rates, with flow reversal occurring more frequently. This paper presents the mathematical derivation and software implementation in Modelica of a thermo-hydraulic model for thermal networks that meets the above requirements and compares it to both experimental data and a commonly used model. Good correspondence between experimental data from a controlled test set-up and simulations using the presented model was found. Compared to measurement data from a real district heating network, the simulation results led to a larger error than in the controlled test set-up, but the general trend is still approximated closely and the model yields results similar to a pipe model from the Modelica Standard Library. However, the presented model simulates 1.7 (for low number of volumes) to 68 (for highly discretized pipes) times faster than a conventional model for a realistic test case. A working implementation of the presented model is made openly available within the IBPSA Modelica Library. The model is robust in the sense that grid size and time step do not need to be adapted to the flow rate, as is the case in finite volume models.

1 avan der Heijde, Brahm1 aFuchs, Marcus1 aTugores, Carles, Ribas1 aSchweiger, Gerald1 aSartor, Kevin1 aBasciotti, Daniele1 aMuller, Dirk1 aNytsch-Geusen, Christoph1 aWetter, Michael1 aHelsen, Lieve uhttps://simulationresearch.lbl.gov/publications/dynamic-equation-based-thermo02489nas a2200205 4500008004100000245008600041210006900127520180800196653001702004653002002021653002102041653001702062653001502079653003202094100001402126700001902140700001702159700002202176856008502198 2017 eng d00aElectric Load Shape Benchmarking for Small- and Medium-Sized Commercial Buildings0 aElectric Load Shape Benchmarking for Small and MediumSized Comme3 a

Small- and medium-sized commercial buildings owners and utility managers often look for opportunities for energy cost savings through energy efficiency and energy waste minimization. However, they currently lack easy access to low-cost tools that help interpret the massive amount of data needed to improve understanding of their energy use behaviors. Benchmarking is one of the techniques used in energy audits to identify which buildings are priorities for an energy analysis. Traditional energy performance indicators, such as the energy use intensity (annual energy per unit of floor area), consider only the total annual energy consumption, lacking consideration of the fluctuation of energy use behavior over time, which reveals the time of use information and represents distinct energy use behaviors during different time spans. To fill the gap, this study developed a general statistical method using 24-hour electric load shape benchmarking to compare a building or business/tenant space against peers. Specifically, the study developed new forms of benchmarking metrics and data analysis methods to infer the energy performance of a building based on its load shape. We first performed a data experiment with collected smart meter data using over 2,000 small- and medium-sized businesses in California. We then conducted a cluster analysis of the source data, and determined and interpreted the load shape features and parameters with peer group analysis. Finally, we implemented the load shape benchmarking feature in an open-access web-based toolkit (the Commercial Building Energy Saver) to provide straightforward and practical recommendations to users. The analysis techniques were generic and flexible for future datasets of other building types and in other utility territories.

10abenchmarking10aBuilding energy10acluster analysis10aload profile10aload shape10arepresentative load pattern1 aLuo, Xuan1 aHong, Tianzhen1 aChen, Yixing1 aPiette, Mary, Ann uhttps://simulationresearch.lbl.gov/publications/electric-load-shape-benchmarking02095nas a2200277 4500008003900000022001300039245010600052210006900158260001200227300001400239490000800253520125200261653001701513653001801530653001701548653001501565653001301580653001501593100002601608700002001634700002101654700002001675700001901695700001801714856008501732 2017 d a0378778800aEnergy saving potential of a two-pipe system for simultaneous heating and cooling of office buildings0 aEnergy saving potential of a twopipe system for simultaneous hea c01/2017 a234 - 2470 v1343 a

This paper analyzes the performance of a novel two-pipe system that operates one water loop to simultaneously provide space heating and cooling with a water supply temperature of around 22 °C. To analyze the energy performance of the system, a simulation-based research was conducted. The two-pipe system was modelled using the equation-based Modelica modeling language in Dymola. A typical office building model was considered as the case study. Simulations were run for two construction sets of the building envelope and two conditions related to inter-zone air flows. To calculate energy savings, a conventional four-pipe system was modelled and used for comparison. The conventional system presented two separated water loops for heating and cooling with supply temperatures of 45 °C and 14 °C, respectively. Simulation results showed that the two-pipe system was able to use less energy than the four-pipe system thanks to three effects: useful heat transfer from warm to cold zones, higher free cooling potential and higher efficiency of the heat pump. In particular, the two-pipe system used approximately between 12% and 18% less total annual primary energy than the four-pipe system, depending on the simulation case considered.

10aactive beams10aenergy saving10aHVAC systems10alow-exergy10amodelica10asimulation1 aMaccarini, Alessandro1 aWetter, Michael1 aAfshari, Alireza1 aHultmark, Goran1 aBergsoe, Niels1 aVorre, Anders uhttps://simulationresearch.lbl.gov/publications/energy-saving-potential-two-pipe02757nas a2200109 4500008004100000245011400041210006900155520229900224100001502523700001902538856009002557 2017 eng d00aA Framework for Quantifying the Impact of Occupant Behavior on Energy Savings of Energy Conservation Measures0 aFramework for Quantifying the Impact of Occupant Behavior on Ene3 a

To improve energy efficiency—during new buildings design or during a building retrofit—evaluating the energy savings potential of energy conservation measures (ECMs) is a critical task. In building retrofits, occupant behavior significantly impacts building energy use and is a leading factor in uncertainty when determining the effectiveness of retrofit ECMs. Current simulation-based assessment methods simplify the representation of occupant behavior by using a standard or representative set of static and homogeneous assumptions ignoring the dynamics, stochastics, and diversity of occupant's energy-related behavior in buildings. The simplification contributes to significant gaps between the simulated and measured actual energy performance of buildings.

This study presents a framework for quantifying the impact of occupant behaviors on ECM energy savings using building performance simulation. During the first step of the study, three occupant behavior styles (austerity, normal, and wasteful) were defined to represent different levels of energy consciousness of occupants regarding their interactions with building energy systems (HVAC, windows, lights and plug-in equipment). Next, a simulation workflow was introduced to determine a range of the ECM energy savings. Then, guidance was provided to interpret the range of ECM savings to support ECM decision making. Finally, a pilot study was performed in a real building to demonstrate the application of the framework. Simulation results show that the impact of occupant behaviors on ECM savings vary with the type of ECM. Occupant behavior minimally affects energy savings for ECMs that are technology-driven (the relative savings differ by less than 2%) and have little interaction with the occupants; for ECMs with strong occupant interaction, such as the use of zonal control variable refrigerant flow system and natural ventilation, energy savings are significantly affected by occupant behavior (the relative savings differ by up to 20%). The study framework provides a novel, holistic approach to assessing the uncertainty of ECM energy savings related to occupant behavior, enabling stakeholders to understand and assess the risk of adopting energy efficiency technologies for new and existing buildings.

1 aSun, Kaiyu1 aHong, Tianzhen uhttps://simulationresearch.lbl.gov/publications/framework-quantifying-impact-occupant02581nas a2200121 4500008004100000245006200041210005700103520215200160100001802312700001902330700002002349856009002369 2017 eng d00aThe Human Dimensions of Energy Use in Buildings: A Review0 aHuman Dimensions of Energy Use in Buildings A Review3 a

The "human dimensions" of energy use in buildings refer to the energy-related behaviors of key stakeholders that affect energy use over the building life cycle. Stakeholders include building designers, operators, managers, engineers, occupants, industry, vendors, and policymakers, who directly or indirectly influence the acts of designing, constructing, living, operating, managing, and regulating the built environments, from individual building up to the urban scale. Among factors driving high-performance buildings, human dimensions play a role that is as significant as that of technological advances. However, this factor is not well understood, and, as a result, human dimensions are often ignored or simplified by stakeholders. This paper presents a review of the literature on human dimensions of building energy use to assess the state-of-the-art in this topic area. The paper highlights research needs for fully integrating human dimensions into the building design and operation processes with the goal of reducing energy use in buildings while enhancing occupant comfort and productivity. This research focuses on identifying key needs for each stakeholder involved in a building's lifecycle and takes an interdisciplinary focus that spans the fields of architecture and engineering design, sociology, data science, energy policy, codes, and standards to provide targeted insights. Greater understanding of the human dimensions of energy use has several potential benefits including reductions in operating cost for building owners;enhanced comfort conditions and productivity for building occupants;more effective building energy management and automation systems for building operators and energy managers; and the integration of more accurate control logic into the next generation of human-in-the-loop technologies. The review concludes by summarizing recommendations for policy makers and industry stakeholders for developing codes, standards, and technologies that can leverage the human dimensions of energy use to reliably predict and achieve energy use reductions in the residential and commercial buildings sectors.

1 aD'Oca, Simona1 aHong, Tianzhen1 aLangevin, Jared uhttps://simulationresearch.lbl.gov/publications/human-dimensions-energy-use-buildings02000nas a2200205 4500008004100000245008800041210006900129490000800198520130700206653002701513653002001540653002201560653002201582653002701604653002001631100002101651700001901672700001701691856008601708 2017 eng d00aIEA EBC Annex 53: Total Energy Use in Buildings – Analysis and Evaluation Methods0 aIEA EBC Annex 53 Total Energy Use in Buildings Analysis and Eval0 v1523 a

One of the most significant barriers to achieving deep building energy efficiency is a lack of knowledge about the factors determining energy use. In fact, there is often a significant discrepancy between designed and real energy use in buildings, which is poorly understood but are believed to have more to do with the role of human behavior than building design. Building energy use is mainly influenced by six factors: climate, building envelope, building services and energy systems, building operation and maintenance, occupants’ activities and behavior, and indoor environmental quality. In the past, much research focused on the first three factors. However, the next three human-related factors can have an influence as significant as the first three. Annex 53 employed an interdisciplinary approach, integrating building science, architectural engineering, computer modeling and simulation, and social and behavioral science to develop and apply methods to analyze and evaluate the real energy use in buildings considering the six influencing factors. Outcomes from Annex 53 improved understanding and strengthen knowledge regarding the robust prediction of total energy use in buildings, enabling reliable quantitative assessment of energy-savings measures, policies, and techniques.

10aenergy data definition10aenergy modeling10aenergy monitoring10aoccupant behavior10aPerformance Evaluation10areal energy use1 aYoshino, Hiroshi1 aHong, Tianzhen1 aNord, Natasa uhttps://simulationresearch.lbl.gov/publications/iea-ebc-annex-53-total-energy-use02536nas a2200253 4500008004100000245008200041210006900123490000800192520173700200653002501937653002001962653001501982653002101997653003102018653002202049100001202071700001902083700001502102700002202117700001802139700002202157700001902179856008402198 2017 eng d00aIEA EBC Annex 66: Definition and simulation of occupant behavior in buildings0 aIEA EBC Annex 66 Definition and simulation of occupant behavior 0 v1563 a

More than 30% of the total primary energy in the world is consumed in buildings. It is crucial to reduce building energy consumption in order to preserve energy resources and mitigate global climate change. Building performance simulations have been widely used for the estimation and optimization of building performance, providing reference values for the assessment of building energy consumption and the effects of energy-saving technologies. Among the various factors influencing building energy consumption, occupant behavior has drawn increasing attention. Occupant behavior includes occupant presence, movement, and interaction with building energy devices and systems. However, there are gaps in occupant behavior modeling as different energy modelers have employed varied data and tools to simulate occupant behavior, therefore producing different and incomparable results. Aiming to address these gaps, the International Energy Agency (IEA) Energy in Buildings and Community (EBC) Programme Annex 66 has established a scientific methodological framework for occupant behavior research, including data collection, behavior model representation, modeling and evaluation approaches, and the integration of behavior modeling tools with building performance simulation programs. Annex 66 also includes case studies and application guidelines to assist in building design, operation, and policymaking, using interdisciplinary approaches to reduce energy use in buildings and improve occupant comfort and productivity. This paper highlights the key research issues, methods, and outcomes pertaining to Annex 66, and offers perspectives on future research needs to integrate occupant behavior with the building life cycle.

10abuilding performance10aenergy modeling10aenergy use10aIEA EBC Annex 6610aInterdisciplinary approach10aoccupant behavior1 aYan, Da1 aHong, Tianzhen1 aDong, Bing1 aMahdavi, Ardeshir1 aD'Oca, Simona1 aGaetani, Isabella1 aFeng, Xiaohang uhttps://simulationresearch.lbl.gov/publications/iea-ebc-annex-66-definition-and02386nas a2200181 4500008004100000245007500041210006900116520176700185653002301952653001501975653001601990653002802006653002202034653002402056100002002080700001902100856008502119 2017 eng d00aModeling of HVAC Operational Faults in Building Performance Simulation0 aModeling of HVAC Operational Faults in Building Performance Simu3 a

Operational faults are common in the heating, ventilating, and air conditioning (HVAC) systems of existing buildings, leading to a decrease in energy efficiency and occupant comfort. Various fault detection and diagnostic methods have been developed to identify and analyze HVAC operational faults at the component or subsystem level. However, current methods lack a holistic approach to predicting the overall impacts of faults at the building level—an approach that adequately addresses the coupling between various operational components, the synchronized effect between simultaneous faults, and the dynamic nature of fault severity. This study introduces the novel development of a fault-modeling feature in EnergyPlus which fills in the knowledge gap left by previous studies. This paper presents the design and implementation of the new feature in EnergyPlus and discusses in detail the fault-modeling challenges faced. The new fault-modeling feature enables EnergyPlus to quantify the impacts of faults on building energy use and occupant comfort, thus supporting the decision making of timely fault corrections. Including actual building operational faults in energy models also improves the accuracy of the baseline model, which is critical in the measurement and verification of retrofit or commissioning projects. As an example, EnergyPlus version 8.6 was used to investigate the impacts of a number of typical operational faults in an office building across several U.S. climate zones. The results demonstrate that the faults have significant impacts on building energy performance as well as on occupant thermal comfort. Finally, the paper introduces future development plans for EnergyPlus fault-modeling capability.

10aenergy performance10aenergyplus10ahvac system10aModeling and simulation10aOperational fault10aThermal comfort  1 aZhang, Rongpeng1 aHong, Tianzhen uhttps://simulationresearch.lbl.gov/publications/modeling-hvac-operational-faults01392nas a2200133 4500008004100000245008600041210006900127260002700196520090500223653003501128100001601163700002001179856005901199 2017 eng d00aMPCPy: An Open-Source Software Platform for Model Predictive Control in Buildings0 aMPCPy An OpenSource Software Platform for Model Predictive Contr aSan Franciscoc08/20173 a

Within the last decade, needs for building control systems that reduce cost, energy, or peak demand, and that facilitate building-grid integration, district-energy system optimization, and occupant interaction, while maintaining thermal comfort and indoor air quality, have come about.  Current PID and schedule-based control systems are not capable of fulfilling these needs, while Model Predictive Control (MPC) could.  Despite the critical role MPC-enabled buildings can play in future energy infrastructures, widespread adoption of MPC within the building industry has yet to occur.  To address barriers associated with system setup and configuration, this paper introduces an open-source software platform that emphasizes use of self-tuning adaptive models, usability by non-experts of MPC, and a flexible architecture that enables application across projects.

10aModel predictive control (MPC)1 aBlum, David1 aWetter, Michael uhttp://www.ibpsa.org/proceedings/BS2017/BS2017_351.pdf02155nas a2200133 4500008004100000245009000041210006900131520167300200100001701873700001201890700001901902700001501921856008501936 2017 eng d00aA Novel Stochastic Modeling Method to Simulate Cooling Loads in Residential Districts0 aNovel Stochastic Modeling Method to Simulate Cooling Loads in Re3 a

District cooling systems are widely used in urban residential communities in China. Most district cooling systems are oversized;this leads to wasted investment and low operational efficiency and thus energy wastage. The accurate prediction of district cooling loads that supports rightsizing cooling plant equipment remains a challenge. This study developed a new stochastic modeling method that includes (1) six prototype house models representing a majority of apartments in the district, (2)occupant behavior models in residential buildings reflecting the temporal and spatial diversity and complexity based on a large-scale residential survey in China, and (3) a stochastic sampling process to represent all apartments and occupants in the district. The stochastic method was employed in a case study using the DeST simulation engine to simulate the cooling loads of a real residential district in Wuhan, China. The simulation results agree well with the actual measurement data based on five performance metrics representing the aggregated cooling loads, the peak cooling loads as well as the spatial load distribution,and the load profiles. Two currently used simulation methods were also employed to simulate the district cooling loads. The simulation results showed that oversimplified occupant behavior assumptions lead to significant overestimations of the peak cooling load and total district cooling loads. Future work will aim to simplify the workflow and data requirements of the stochastic method to enable its practical application as well as explore its application in predicting district heating loads and in commercial or mixed-use districts.

1 aAn, Jingjing1 aYan, Da1 aHong, Tianzhen1 aSun, Kaiyu uhttps://simulationresearch.lbl.gov/publications/novel-stochastic-modeling-method02042nas a2200193 4500008004100000245014000041210006900181520132600250653002201576653003601598653001801634653001501652653002201667100001901689700001701708700001901725700001801744856008601762 2017 eng d00aOccupant behavior models: A critical review of implementation and representation approaches in building performance simulation programs0 aOccupant behavior models A critical review of implementation and3 a

Occupant behavior (OB) in buildings is a leading factor influencing energy use in buildings. Quantifying this influence requires the integration of OB models with building performance simulation (BPS). This study reviews approaches to representing and implementing OB models in today’s popular BPS programs, and discusses weaknesses and strengths of these approaches and key issues in integrating of OB models with BPS programs. Two key findings are: (1) a common data model is needed to standardize the representation of OB models, enabling their flexibility and exchange among BPS programs and user applications; the data model can be implemented using a standard syntax (e.g., in the form of XML schema), and (2) a modular software implementation of OB models, such as functional mock-up units for co-simulation, adopting the common data model, has advantages in providing a robust and interoperable integration with multiple BPS programs. Such common OB model representation and implementation approaches help standardize the input structures of OB models, enable collaborative development of a shared library of OB models, and allow for rapid and widespread integration of OB models with BPS programs to improve the simulation of occupant behavior and quantification of their impact on building performance.

10aBehavior Modeling10abuilding performance simulation10aco-simulation10adata model10aoccupant behavior1 aHong, Tianzhen1 aChen, Yixing1 aBelafi, Zsofia1 aD'Oca, Simona uhttps://simulationresearch.lbl.gov/publications/occupant-behavior-models-critical02401nas a2200229 4500008004100000245007200041210006900113260001200182490000800194520165900202653003301861653002201894653002501916653002201941653003501963653001701998100001402015700001902029700001702048700001902065856008702084 2017 eng d00aPerformance Evaluation of an Agent-based Occupancy Simulation Model0 aPerformance Evaluation of an Agentbased Occupancy Simulation Mod c04/20170 v1153 a

Occupancy is an important factor driving building performance. Static and homogeneous occupant schedules, commonly used in building performance simulation, contribute to issues such as performance gaps between simulated and measured energy use in buildings. Stochastic occupancy models have been recently developed and applied to better represent spatial and temporal diversity of occupants in buildings. However, there is very limited evaluation of the usability and accuracy of these models. This study used measured occupancy data from a real office building to evaluate the performance of an agent-based occupancy simulation model: the Occupancy Simulator. The occupancy patterns of various occupant types were first derived from the measured occupant schedule data using statistical analysis. Then the performance of the simulation model was evaluated and verified based on (1) whether the distribution of observed occupancy behavior patterns follows the theoretical ones included in the Occupancy Simulator, and (2) whether the simulator can reproduce a variety of occupancy patterns accurately. Results demonstrated the feasibility of applying the Occupancy Simulator to simulate a range of occupancy presence and movement behaviors for regular types of occupants in office buildings, and to generate stochastic occupant schedules at the room and individual occupant levels for building performance simulation. For future work, model validation is recommended, which includes collecting and using detailed interval occupancy data of all spaces in an office building to validate the simulated occupant schedules from the Occupancy Simulator.

10amodel performance evaluation10aoccupancy pattern10aOccupancy simulation10aoccupant behavior10aoccupant presence and movement10averification1 aLuo, Xuan1 aLam, Khee, Poh1 aChen, Yixing1 aHong, Tianzhen uhttps://simulationresearch.lbl.gov/publications/performance-evaluation-agent-based01615nas a2200193 4500008004100000245007900041210006900120520095300189653002001142653001901162653002201181653003401203653002501237100001401262700001901276700001501295700002101310856009001331 2017 eng d00aA Preliminary Investigation of Water Usage Behavior in Single-Family Homes0 aPreliminary Investigation of Water Usage Behavior in SingleFamil3 a

As regional drought conditions continue deteriorating around the world, residential water use has been brought into the built environment spotlight. Nevertheless, the understanding of water use behavior in residential buildings is still limited. This paper presents data analytics and results from monitoring data of daily water use (DWU) in 50 single-family homes in Texas, USA. The results show the typical frequency distribution curve of the DWU per household and indicate personal income, education level and energy use of appliances all have statistically significant effects on the DWU per capita. Analysis of the water-intensive use demonstrates the residents tend to use more water in post-vacation days. These results help generate awareness of water use behavior in homes. Ultimately, this research could support policy makers to establish a water use baseline and inform water conservation programs.

 

10adaily water use10aData Analytics10aoccupant behavior10aresidential water consumption10aWater usage behavior1 aXue, Peng1 aHong, Tianzhen1 aDong, Bing1 aMak, Cheuk, Ming uhttps://simulationresearch.lbl.gov/publications/preliminary-investigation-water-usage02483nas a2200241 4500008004100000245008900041210006900130260001200199300001400211490000700225520173000232653002201962653002501984653002402009653001502033653002202048653001802070100001702088700001502105700001902120700001402139856008802153 2017 eng d00aSimulation and visualization of energy-related occupant behavior in office buildings0 aSimulation and visualization of energyrelated occupant behavior  c03/2017 a785–7980 v103 a

In current building performance simulation programs, occupant presence and interactions with building systems are over-simplified and less indicative of real world scenarios, contributing to the discrepancies between simulated and actual energy use in buildings. Simulation results are normally presented using various types of charts. However, using those charts, it is difficult to visualize and communicate the importance of occupants’ behavior to building energy performance. This study introduced a new approach to simulating and visualizing energy-related occupant behavior in office buildings. First, the Occupancy Simulator was used to simulate the occupant presence and movement and generate occupant schedules for each space as well as for each occupant. Then an occupant behavior functional mockup unit (obFMU) was used to model occupant behavior and analyze their impact on building energy use through co-simulation with EnergyPlus. Finally, an agent-based model built upon AnyLogic was applied to visualize the simulation results of the occupant movement and interactions with building systems, as well as the related energy performance. A case study using a small office building in Miami, FL was presented to demonstrate the process and application of the Occupancy Simulator, the obFMU and EnergyPlus, and the AnyLogic module in simulation and visualization of energy-related occupant behaviors in office buildings. The presented approach provides a new detailed and visual way for policy makers, architects, engineers and building operators to better understand occupant energy behavior and their impact on energy use in buildings, which can improve the design and operation of low energy buildings.

10aBehavior Modeling10abuilding performance10abuilding simulation10aenergyplus10aoccupant behavior10avisualization1 aChen, Yixing1 aLiang, Xin1 aHong, Tianzhen1 aLuo, Xuan uhttps://simulationresearch.lbl.gov/publications/simulation-and-visualization-energy03410nas a2200409 4500008004100000245008500041210006900126260001200195520213600207653000902343653002502352653002202377653002002399653001902419653002302438653003302461653003902494653003202533653001302565653002102578100002202599700001902621700002202640700002102662700002002683700001702703700002302720700002202743700002102765700002002786700002302806700001902829700001502848700002802863700002002891856008902911 2017 eng d00aSmall and Medium Building Efficiency Toolkit and Community Demonstration Program0 aSmall and Medium Building Efficiency Toolkit and Community Demon c03/20173 a

Small commercial buildings in the United States consume 47 percent of all primary energy consumed in the building sector. Retrofitting small and medium commercial buildings may pose a steep challenge for owners, as many lack the expertise and resources to identify and evaluate cost-effective energy retrofit strategies. To address this problem, this project developed the Commercial Building Energy Saver (CBES), an energy retrofit analysis toolkit that calculates the energy use of a building, identifies and evaluates retrofit measures based on energy savings, energy cost savings, and payback. The CBES Toolkit includes a web app for end users and the CBES Application Programming Interface for integrating CBES with other energy software tools. The toolkit provides a rich feature set, including the following:

  1. Energy Benchmarking providing an Energy Star score
  2. Load Shape Analysis to identify potential building operation improvements
  3. Preliminary Retrofit Analysis which uses a custom developed pre-simulated database
  4. Detailed Retrofit Analysis which utilizes real time EnergyPlus simulations

In a parallel effort the project team developed technologies to measure outdoor airflow rate; commercialization and use would avoid both excess energy use from over ventilation and poor indoor air quality resulting from under ventilation.

If CBES is adopted by California’s statewide small office and retail buildings, by 2030 the state can anticipate 1,587 gigawatt hours of electricity savings, 356 megawatts of non-coincident peak demand savings, 30.2 megatherms of natural gas savings, $227 million of energy-related cost savings, and reduction of emissions by 757,866 metric tons of carbon dioxide equivalent. In addition, consultant costs will be reduced in the retrofit analysis process.

CBES contributes to the energy savings retrofit field by enabling a straightforward and uncomplicated decision-making process for small and medium business owners and leveraging different levels of assessment to match user background, preference, and data availability.

10aCBES10acommercial buildings10aenergy efficiency10aenergy modeling10aenergy savings10aindoor air quality10aindoor environmental quality10aoutdoor air measurement technology10aoutdoor airflow intake rate10aretrofit10aventilation rate1 aPiette, Mary, Ann1 aHong, Tianzhen1 aFisk, William, J.1 aBourassa, Norman1 aChan, Wanyu, R.1 aChen, Yixing1 aCheung, H.Y., Iris1 aHotchi, Toshifumi1 aKloss, Margarita1 aLee, Sang, Hoon1 aPrice, Phillip, N.1 aSchetrit, Oren1 aSun, Kaiyu1 aTaylor-Lange, Sarah, C.1 aZhang, Rongpeng uhttps://simulationresearch.lbl.gov/publications/small-and-medium-building-efficiency02859nas a2200229 4500008004100000022003900041245011200080210006900192260001200261300001200273490000700285520208600292653002302378653003602401653001502437653002302452653001702475100001902492700001902511700001802530856008102548 2017 eng d aPrint 1996-3599; Online 1996-874400aSmart Building Management vs. Intuitive Human Control — Lessons learnt from an office building in Hungary0 aSmart Building Management vs Intuitive Human Control Lessons lea c12/2017 a811-8280 v103 a

Smart building management and control are adopted nowadays to achieve zero-net energy use in buildings. However, without considering the human dimension, technologies alone do not necessarily guarantee high performance in buildings. An office building was designed and built according to state-of-the-art design and energy management principles in 2008. Despite the expectations of high performance, the owner was facing high utility bills and low user comfort in the building located in Budapest, Hungary. The objective of the project was to evaluate the energy performance and comfort indices of the building, to identify the causes of malfunction and to elaborate a comprehensive energy concept. Firstly, current building conditions and operation parameters were evaluated. Our investigation found that the state-of-the-art building management system was in good conditions but it was operated by building operators and occupants who are not aware of the building management practice. The energy consumption patterns of the building were simulated with energy modelling software. The baseline model was calibrated to annual measured energy consumption, using actual occupant behaviour and presence, based on results of self-reported surveys, occupancy sensors and fan-coil usage data. Realistic occupant behaviour models can capture diversity of occupant behaviour and better represent the real energy use of the building. This way our findings and the effect of our proposed improvements could be more reliable. As part of our final comprehensive energy concept, we proposed intervention measures that would increase indoor thermal comfort and decrease energy consumption of the building. A parametric study was carried out to evaluate and quantify energy, comfort and return on investment of each measure. It was found that in the best case the building could save 23% of annual energy use. Future work includes the follow-up of: occupant reactions to intervention measures, the realized energy savings, the measurement of occupant satisfaction and behavioural changes.

10abuilding operation10abuilding performance simulation10acase study10aOccupant Behaviour10aoptimization1 aBelafi, Zsofia1 aHong, Tianzhen1 aReith, Andras uhttps://simulationresearch.lbl.gov/publications/smart-building-management-vs02293nas a2200241 4500008004100000245016600041210006900207520145100276653002201727653001801749653002101767653002301788653002501811653002201836653001501858100001401873700001201887700001701899700001901916700001401935700001501949856008701964 2017 eng d00aSpatial Distribution of Internal Heat Gains: A Probabilistic Representation and Evaluation of Its Influence on Cooling Equipment Sizing in Large Office Buildings0 aSpatial Distribution of Internal Heat Gains A Probabilistic Repr3 a

Internal heat gains from occupants, lighting, and plug loads are significant components of the space cooling load in an office building. Internal heat gains vary with time and space. The spatial diversity is significant, even for spaces with the same function in the same building. The stochastic nature of internal heat gains makes determining the peak cooling load to size air-conditioning systems a challenge. The traditional conservative practice of considering the largest internal heat gain among spaces and applying safety factors overestimates the space cooling load, which leads to oversized air-conditioning equipment and chiller plants. In this study, a field investigation of several large office buildings in China led to the development of a new probabilistic approach that represents the spatial diversity of the design internal heat gain of each tenant as a probability distribution function. In a large office building, a central chiller plant serves all air handling units (AHUs), with each AHU serving one or more floors of the building. Therefore, the spatial diversity should be considered differently when the peak cooling loads to size the AHUs and chillers are calculated. The proposed approach considers two different levels of internal heat gains to calculate the peak cooling loads and size the AHUs and chillers in order to avoid oversizing, improve the overall operating efficiency, and thus reduce energy use.

10aair handling unit10achiller plant10aequipment sizing10ainternal heat gain10aspatial distribution10aspatial diversity10astochastic1 aZhang, Qi1 aYan, Da1 aAn, Jingjing1 aHong, Tianzhen1 aTian, Wei1 aSun, Kaiyu uhttps://simulationresearch.lbl.gov/publications/spatial-distribution-internal-heat02072nas a2200133 4500008004100000245014300041210006900184520152000253100001801773700002001791700001901811700001901830856008901849 2017 eng d00aSynthesizing building physics with social psychology: An interdisciplinary framework for context and occupant behavior in office buildings0 aSynthesizing building physics with social psychology An interdis3 a

This study introduces an interdisciplinary framework for investigating building-user interaction in office spaces. The framework is a synthesis of theories from building physics and social psychology including social cognitive theory, the theory of planned behavior, and the drivers-needs-actions-systems ontology for energy-related behaviors. The goal of the research framework is to investigate the effects of various behavioral adaptations and building controls (i.e., adjusting thermostats, operating windows, blinds and shades, and switching on/off artificial lights) to determine impacts on occupant comfort and energy-related operational costs in the office environment. This study attempts to expand state-of-the-art understanding of: (1) the environmental, personal, and behavioral drivers motivating occupants to interact with building control systems across four seasons, (2) how occupants’ intention to share controls is influenced by social-psychological variables such as attitudes, subjective norms, and perceived behavioral control in group negotiation dynamic, (3) the perceived ease of usage and knowledge of building technologies, and (4) perceived satisfaction and productivity. To ground the validation of the theoretical framework in diverse office settings and contexts at the international scale, an online survey was designed to collect cross-country responses from office occupants among 14 universities and research centers within the United States, Europe, China, and Australia.

1 aD'Oca, Simona1 aChen, Chien-Fen1 aHong, Tianzhen1 aBelafi, Zsofia uhttps://simulationresearch.lbl.gov/publications/synthesizing-building-physics-social01971nas a2200193 4500008004100000245013400041210006900175520127100244653001201515653002001527653001701547653004101564653002201605100001401627700001201641700001901653700001601672856008901688 2017 eng d00aTemporal and spatial characteristics of the urban heat island in Beijing and the impact on building design and energy performance0 aTemporal and spatial characteristics of the urban heat island in3 a

With the increased urbanization in most countries worldwide, the urban heat island (UHI) effect, referring to the phenomenon that an urban area has higher ambient temperature than the surrounding rural area, has gained much attention in recent years. Given that Beijing is developing rapidly both in urban population and economically, the UHI effect can be significant. A long-term measured weather dataset from 1961 to 2014 for ten rural stations and seven urban stations in Beijing, was analyzed in this study, to understand the detailed temporal and spatial characteristics of the UHI in Beijing. The UHI effect in Beijing is significant, with an urban-to-rural temperature difference of up to 8℃ during the winter nighttime. Furthermore, the impacts of UHIs on building design and energy performance were also investigated. The UHI in Beijing led to an approximately 11% increase in cooling load and 16% decrease in heating load in the urban area compared with the rural area, whereas the urban heating peak load decreased 9% and the cooling peak load increased 7% because of the UHI effect. This study provides insights into the UHI in Beijing and recommendations to improve building design and decision-making while considering the urban microclimate.

10abeijing10abuilding design10aMicroclimate10aTemporal and spatial characteristics10aurban heat island1 aCui, Ying1 aYan, Da1 aHong, Tianzhen1 aMa, Jingjin uhttps://simulationresearch.lbl.gov/publications/temporal-and-spatial-characteristics01990nas a2200205 4500008004100000245007700041210006900118520131200187653002201499653002501521653002401546653001501570653002201585653002201607100001901629700001201648700001801660700002001678856008601698 2017 eng d00aTen Questions Concerning Occupant Behavior in Buildings: The Big Picture0 aTen Questions Concerning Occupant Behavior in Buildings The Big 3 a

Occupant behavior has significant impacts on building energy performance and occupant comfort. However, occupant behavior is not well understood and is often oversimplified in the building life cycle, due to its stochastic, diverse, complex, and interdisciplinary nature. The use of simplified methods or tools to quantify the impacts of occupant behavior in building performance simulations significantly contributes to performance gaps between simulated models and actual building energy consumption. Therefore, it is crucial to understand occupant behavior in a comprehensive way, integrating qualitative approaches and data- and model-driven quantitative approaches, and employing appropriate tools to guide the design and operation of low-energy residential and commercial buildings that integrate technological and human dimensions. This paper presents ten questions, highlighting some of the most important issues regarding concepts, applications, and methodologies in occupant behavior research. The proposed questions and answers aim to provide insights into occupant behavior for current and future researchers, designers, and policy makers, and most importantly, to inspire innovative research and applications to increase energy efficiency and reduce energy use in buildings.

 

10aBehavior Modeling10abuilding performance10abuilding simulation10aenergy use10ainterdisciplinary10aoccupant behavior1 aHong, Tianzhen1 aYan, Da1 aD'Oca, Simona1 aChen, Chien-Fei uhttps://simulationresearch.lbl.gov/publications/ten-questions-concerning-occupant02540nas a2200241 4500008004100000245008400041210006900125260001200194520178100206653001001987653002201997653002302019653002202042653002502064653002302089100001202112700001902124700001402143700001402157700001702171700001302188856009702201 2017 eng d00aA Thorough Assessment of China’s Standard for Energy Consumption of Buildings0 aThorough Assessment of China s Standard for Energy Consumption o c03/20173 a

China’s Design Standard for Energy Efficiency of Public Buildings (the Design Standard) is widely used in the design phase to regulate the energy efficiency of physical assets (envelope, lighting, HVAC) in buildings. However, the standard does not consider many important factors that influence the actual energy use in buildings, and this can lead to gaps between the design estimates and actual energy consumption. To achieve the national energy savings targets defined in the strategic 12th Five-Year Plan, China developed the first standard for energy consumption of buildings GB/T51161-2016 (the Consumption Standard). This study provides an overview of the Consumption Standard, identifies its strengths and weaknesses, and recommends future improvements. The analysis and discussion of the constraint value and the leading value, two key indicators of the energy use intensity, provide insight into the intent and effectiveness of the Consumption Standard. The results indicated that consistency between China’s Design Standard GB 50189-2015 and the Consumption Standard GB/T51161-2016 could be achieved if the Design Standard used the actual building operations and occupant behavior in calculating the energy use in Chinese buildings. The development of an outcome-based code in the U.S. was discussed in comparison with China’s Consumption Standard, and this revealed the strengths and challenges associated with implementing a new compliance method based on actual energy use in buildings in the U.S. Overall, this study provides important insights into the latest developments of actual consumption-based building energy standards, and this information should be valuable to building designers and energy policy makers in China and the U.S.

10aChina10acode and standard10aenergy consumption10aenergy efficiency10aEnergy Use Intensity10aoutcome-based code1 aYan, Da1 aHong, Tianzhen1 aLi, Cheng1 aZhang, Qi1 aAn, Jingjing1 aHu, shan uhttps://simulationresearch.lbl.gov/publications/thorough-assessment-china%E2%80%99s-standard01628nas a2200241 4500008003900000245009100039210006900130260001200199300001200211490000800223520083600231653002201067653003401089653003601123653001501159653002201174100001901196700002801215700001801243700001201261700002601273856008701299 2016 d00aAdvances in research and applications of energy-related occupant behavior in buildings0 aAdvances in research and applications of energyrelated occupant  c03/2016 a694-7020 v1163 a

Occupant behavior is one of the major factors influencing building energy consumption and contributing to uncertainty in building energy use prediction and simulation. Currently the understanding of occupant behavior is insufficient both in building design, operation and retrofit, leading to incorrect simplifications in modeling and analysis. This paper introduced the most recent advances and current obstacles in modeling occupant behavior and quantifying its impact on building energy use. The major themes include advancements in data collection techniques, analytical and modeling methods, and simulation applications which provide insights into behavior energy savings potential and impact. There has been growing research and applications in this field, but significant challenges and opportunities still lie ahead.

10aBehavior Modeling10aBuilding design and operation10abuilding performance simulation10aenergy use10aoccupant behavior1 aHong, Tianzhen1 aTaylor-Lange, Sarah, C.1 aD'Oca, Simona1 aYan, Da1 aCorgnati, Stefano, P. uhttps://simulationresearch.lbl.gov/publications/advances-research-and-applications01736nas a2200121 4500008003900000245007500039210006900114520129700183100001701480700001401497700001901511856008401530 2016 d00aAn Agent-Based Occupancy Simulator for Building Performance Simulation0 aAgentBased Occupancy Simulator for Building Performance Simulati3 a

Traditionally, in building energy modeling (BEM) programs, occupancy inputs are deterministic and less indicative of real world scenarios, contributing to discrepancies between simulated and actual energy use in buildings. This paper presents an agent-based occupancy simulator, which models each occupant as an agent with specified movement events and statistics of space uses. To reduce the amount of data inputs, the simulator allows users to group occupants with similar behaviors as an occupant type, and spaces with similar function as a space type. It is a web-based application with friendly graphical user interface, cloud computing, and data storage. A case study is presented to demonstrate the usage of the occupancy simulator and its integration with EnergyPlus and obFMU. It first shows the required data inputs and the results from the occupancy simulator. Then, the generated occupant schedules are used in the EnergyPlus and obFMU simulation to evaluate the impacts of occupant behavior on building energy performance. The simulation results indicate that the occupancy simulator can capture the diversity of space’s occupancy behavior rather than the static weekly profiles, and can generate realistic occupancy schedules to support building performance simulation.

1 aChen, Yixing1 aLuo, Xuan1 aHong, Tianzhen uhttps://simulationresearch.lbl.gov/publications/agent-based-occupancy-simulator02436nas a2200217 4500008004100000245013500041210006900176520163000245653002401875653002501899653002301924653002201947653003801969653004402007100001602051700001202067700001502079700001902094700001602113856008902129 2016 eng d00aA Comparative Study on Energy Performance of Variable Refrigerant Flow Systems and Variable Air Volume Systems in Office Buildings0 aComparative Study on Energy Performance of Variable Refrigerant 3 a

Variable air volume (VAV) systems and variable refrigerant flow (VRF) systems are popularly used in office buildings. This study investigated VAV and VRF systems in five typical office buildings in China, and compared their air conditioning energy use. Site survey and field measurements were conducted to collect data of building characteristics and operation. Measured cooling electricity use was collected from sub-metering in the five buildings. The sub-metering data, normalized by climate and operating hours, show that VRF systems consumed much less air conditioning energy by up to 70% than VAV systems. This is mainly due to the different operation modes of both system types leading to much fewer operating hours of the VRF systems. Building simulation was used to quantify the impact of operation modes of VRF and VAV systems on cooling loads using a prototype office building in China. Simulated results show the VRF operation mode leads to much less cooling loads than the VAV operation mode, by 42% in Hong Kong and 53% in Qingdao. The VRF systems operated in the part-time-part-space mode enabling occupants to turn on air-conditioning only when needed and when spaces were occupied, while the VAV systems operated in the full-time-full-space mode limiting occupants’ control of operation. The findings provide insights into VRF systems operation and controls as well as its energy performance, which can inform HVAC designers on system selection and building operators or facility managers on improving VRF system operations.    


 

 

10abuilding simulation10acomparative analysis10aenergy performance10afield measurement10aVariable Air Volume (VAV) Systems10aVariable Refrigerant Flow (VRF) Systems1 aYu, Xinqiao1 aYan, Da1 aSun, Kaiyu1 aHong, Tianzhen1 aZhu, Dandan uhttps://simulationresearch.lbl.gov/publications/comparative-study-energy-performance00823nas a2200229 4500008004100000245011300041210006900154653002400223653002200247653002900269653002300298653002300321653002900344653002900373100001500402700002000417700001400437700001900451700001800470700001800488856008700506 2016 eng d00aThe Impact of Evaporation Process on Thermal Performance of Roofs - Model Development and Numerical Analysis0 aImpact of Evaporation Process on Thermal Performance of Roofs Mo10aEvaporative Cooling10amodel development10aNet zero energy building10aNumerical analysis10aPassive techniques10aPorous building material10aRoof thermal performance1 aZhang, Lei1 aZhang, Rongpeng1 aZhang, Yu1 aHong, Tianzhen1 aMeng, Qinglin1 aFeng, Yanshan uhttps://simulationresearch.lbl.gov/publications/impact-evaporation-process-thermal02209nas a2200181 4500008004100000245009800041210006900139520155000208653001901758653002401777653003101801653003301832653001401865100001501879700001901894700002701913856008701940 2016 eng d00aImproving the accuracy of energy baseline models for commercial buildings with occupancy data0 aImproving the accuracy of energy baseline models for commercial 3 a

More than 80% of energy is consumed during operation phase of a building’s life cycle, so energy efficiency retrofit for existing buildings is considered a promising way to reduce energy use in buildings. The investment strategies of retrofit depend on the ability to quantify energy savings by “measurement and verification” (M&V), which compares actual energy consumption to how much energy would have been used without retrofit (called the “baseline” of energy use). Although numerous models exist for predicting baseline of energy use, a critical limitation is that occupancy has not been included as a variable. However, occupancy rate is essential for energy consumption and was emphasized by previous studies. This study develops a new baseline model which is built upon the Lawrence Berkeley National Laboratory (LBNL) model but includes the use of building occupancy data. The study also proposes metrics to quantify the accuracy of prediction and the impacts of variables. However, the results show that including occupancy data does not significantly improve the accuracy of the baseline model, especially for HVAC load. The reasons are discussed further. In addition, sensitivity analysis is conducted to show the influence of parameters in baseline models. The results from this study can help us understand the influence of occupancy on energy use, improve energy baseline prediction by including the occupancy factor, reduce risks of M&V and facilitate investment strategies of energy efficiency retrofit.

10abaseline model10abuilding energy use10aEnergy Efficiency Retrofit10aMeasurement and verification10aoccupancy1 aLiang, Xin1 aHong, Tianzhen1 aShen, Geoffrey, Qiping uhttps://simulationresearch.lbl.gov/publications/improving-accuracy-energy-baseline02318nas a2200193 4500008003900000245006900039210006900108520165900177653001901836653003701855653001501892653002101907653002501928100001801953700002601971700002501997700001902022856008302041 2016 d00aIntroduction to an occupant behavior motivation survey framework0 aIntroduction to an occupant behavior motivation survey framework3 a

An increasing body of research is underlying the need to foster energy behaviors and interaction with technology as a way to achieve energy savings in office buildings. However, engaging office users into more “forgiving” comfort-adaptive behavior is not a trivial task, since neither consequences nor benefits for changing behavior have visible or tangible effects on them personally. Since the 70’s, survey studies in the field of building science have been used to gain better understanding of multidisciplinary drivers of occupant behavior with respect to comfort and energy requirements in buildings. Rather than focusing on individual behaviors – and influencing factors – purpose of this survey research is to provide quantitative descriptions on the collective and social motivations within the complexity of different social groups in working environment, under different geographical context, culture and norms. The resultant questionnaire survey emerges as a combination of traditional and adaptive comfort theories, merged with social science theory. The questionnaire explores to what extent the occupant energy-related behavior in working spaces is driven by a motivational sphere influenced by i) comfort requirements, ii) habits, iii) intentions and iv) actual control of building systems. The key elements of the proposed occupant behavior motivational framework are grounded on the Driver Need Action System framework for energy-related behaviors in buildings. Goal of the study is to construct an additional layer of standardized knowledge to enrich the state-of-the-art on energy-related behavior in office buildings.

10aDNAs framework10aenergy-related occupant behavior10amotivation10aoffice buildings10aquestionnaire survey1 aD'Oca, Simona1 aCorgnati, Stefano, P.1 aPisello, Anna, Laura1 aHong, Tianzhen uhttps://simulationresearch.lbl.gov/publications/introduction-occupant-behavior01991nas a2200109 4500008003900000245008300039210006900122520156300191100002001754700001901774856008801793 2016 d00aModeling and Simulation of Operational Faults of HVAC Systems Using Energyplus0 aModeling and Simulation of Operational Faults of HVAC Systems Us3 a

HVAC operations play a significant role among various driving factors to improve energy performance of buildings. Extensive researches have been conducted on the design efficiencies and control strategies of HVAC system, but very few focused on the impacts of its operational faults on the building energy efficiency. Modeling and simulation of operational faults can lead to better understandings of the fault impacts and thus support decision making of timely fault corrections which can further benefit the efficient system operation, improve the indoor thermal comfort, and prolong the equipment service life. Fault modeling is also critical to achieve more accurate and reliable model calibrations. This paper introduces the modeling and simulation of operational faults using EnergyPlus, a comprehensive whole building performance simulation tool. The paper discusses the challenges of operational fault modeling, and compares three approaches to simulate operational faults using EnergyPlus. The paper also introduces the latest development of native fault objects within EnergyPlus. As an example, EnergyPlus version 8.4 is used to investigate the impacts of the integrated thermostat and humidistat faults in a typical office building across several U.S. climate zones. The results demonstrate that the faults create significant impacts on the building energy performance as well as occupant thermal comfort. At last, the paper introduces the future development plan of EnergyPlus for the further improvement of its fault modeling capability.

1 aZhang, Rongpeng1 aHong, Tianzhen uhttps://simulationresearch.lbl.gov/publications/modeling-and-simulation-operational01835nas a2200169 4500008003900000245005800039210005700097520128500154653001601439653002101455653002501476653002201501100001501523700001901538700002701557856008101584 2016 d00aOccupancy data analytics and prediction: a case study0 aOccupancy data analytics and prediction a case study3 a

Occupants are a critical impact factor of building energy consumption. Numerous previous studies emphasized the role of occupants and investigated the interactions between occupants and buildings. However, a fundamental problem, how to learn occupancy patterns and predict occupancy schedule, has not been well addressed due to highly stochastic activities of occupants and insufficient data. This study proposes a data mining based approach for occupancy schedule learning and prediction in office buildings. The proposed approach first recognizes the patterns of occupant presence by cluster analysis, then learns the schedule rules by decision tree, and finally predicts the occupancy schedules based on the inducted rules. A case study was conducted in an office building in Philadelphia, U.S. Based on one-year observed data, the validation results indicate that the proposed approach significantly improves the accuracy of occupancy schedule prediction. The proposed approach only requires simple input data (i.e., the time series data of occupant number entering and exiting a building), which is available in most office buildings. Therefore, this approach is practical to facilitate occupancy schedule prediction, building energy simulation and facility operation.

10adata mining10aMachine learning10aoccupancy prediction10aoccupant presence1 aLiang, Xin1 aHong, Tianzhen1 aShen, Geoffrey, Qiping uhttps://simulationresearch.lbl.gov/publications/occupancy-data-analytics-and02035nas a2200181 4500008004100000245009300041210006900134520139300203653002101596653002201617653003601639653001901675653001501694653002201709100001501731700001901746856008801765 2016 eng d00aA Simulation Approach to Estimate Energy Savings Potential of Occupant Behavior Measures0 aSimulation Approach to Estimate Energy Savings Potential of Occu3 a

Occupant behavior in buildings is a leading factor influencing energy use in buildings. Low-cost behavioral solutions have demonstrated significant potential energy savings. Estimating the behavioral savings potential is important for a more effective design of behavior change interventions, which in turn will support more effective energy-efficiency policies. This study introduces a simulation approach to estimate the energy savings potential of occupant behavior measures. First it defines five typical occupant behavior measures in office buildings, then simulates and analyzes their individual and integrated impact on energy use in buildings. The energy performance of the five behavior measures was evaluated using EnergyPlus simulation for a real office building across four typical U.S. climates and two vintages. The Occupancy Simulator was used to simulate the occupant movement in each zone with inputs from the site survey of the case building. Based on the simulation results, the occupant behavior measures can achieve overall site energy savings as high as 22.9% for individual measures and up to 41.0% for integrated measures. Although energy savings of behavior measures would vary depending upon many factors, the presented simulation approach is robust and can be adopted for other studies aiming to quantify occupant behavior impact on building performance.

10abehavior measure10aBehavior Modeling10abuilding performance simulation10aenergy savings10aenergyplus10aoccupant behavior1 aSun, Kaiyu1 aHong, Tianzhen uhttps://simulationresearch.lbl.gov/publications/simulation-approach-estimate-energy01862nas a2200133 4500008004100000245007800041210006900119260001200188520137400200100002501574700002001599700002201619856008701641 2016 eng d00aA Tale of Three District Energy Systems: Metrics and Future Opportunities0 aTale of Three District Energy Systems Metrics and Future Opportu c08/20173 a

Improving the sustainability of cities is crucial for meeting climate goals in the next several decades. One way this is being tackled is through innovation in district energy systems, which can take advantage of local resources and economies of scale to improve the performance of whole neighborhoods in ways infeasible for individual buildings. These systems vary in physical size, end use services, primary energy resources, and sophistication of control. They also vary enormously in their choice of optimization metrics while all under the umbrella-goal of improved sustainability.

This paper explores the implications of choice of metric on district energy systems using three case studies: Stanford University, the University of California at Merced, and the Richmond Bay campus of the University of California at Berkeley. They each have a centralized authority to implement large-scale projects quickly, while maintaining data records, which makes them relatively effective at achieving their respective goals. Comparing the systems using several common energy metrics reveals significant differences in relative system merit. Additionally, a novel bidirectional heating and cooling system is presented. This system is highly energy-efficient, and while more analysis is required, may be the basis of the next generation of district energy systems

1 aPass, Rebecca, Zarin1 aWetter, Michael1 aPiette, Mary, Ann uhttps://simulationresearch.lbl.gov/publications/tale-three-district-energy-systems02261nas a2200241 4500008003900000245011100039210006900150260001200219520144900231653002401680653003201704653002001736653001501756653003101771653001301802100002001815700001901835700002201854700001701876700001701893700002801910856008101938 2015 d00aAccelerating the energy retrofit of commercial buildings using a database of energy efficiency performance0 aAccelerating the energy retrofit of commercial buildings using a c07/20153 a

Small and medium-sized commercial buildings can be retrofitted to significantly reduce their energy use, however it is a huge challenge as owners usually lack of the expertise and resources to conduct detailed on-site energy audit to identify and evaluate cost-effective energy technologies. This study presents a DEEP (database of energy efficiency performance) that provides a direct resource for quick retrofit analysis of commercial buildings. DEEP, compiled from the results of about ten million EnergyPlus simulations, enables an easy screening of ECMs (energy conservation measures) and retrofit analysis. The simulations utilize prototype models representative of small and mid-size offices and retails in California climates. In the formulation of DEEP, large scale EnergyPlus simulations were conducted on high performance computing clusters to evaluate hundreds of individual and packaged ECMs covering envelope, lighting, heating, ventilation, air-conditioning, plug-loads, and service hot water. The architecture and simulation environment to create DEEP is flexible and can expand to cover additional building types, additional climates, and new ECMs. In this study DEEP is integrated into a web-based retrofit toolkit, the Commercial Building Energy Saver, which provides a platform for energy retrofit decision making by querying DEEP and unearthing recommended ECMs, their estimated energy savings and financial payback.

10abuilding simulation10aEnergy conservation measure10aenergy modeling10aenergyplus10aHigh Performance computing10aretrofit1 aLee, Sang, Hoon1 aHong, Tianzhen1 aPiette, Mary, Ann1 aSawaya, Geof1 aChen, Yixing1 aTaylor-Lange, Sarah, C. uhttps://simulationresearch.lbl.gov/publications/accelerating-energy-retrofit02732nas a2200265 4500008003900000245013300039210006900172260001200241300001200253490000600265520189500271653001302166653001002179653002202189653001202211653001202223100002102235700001802256700001902274700002102293700002902314700001802343700001502361856009002376 2015 d00aAssessment of the Potential to Achieve Very Low Energy Use in Public Buildings in China with Advanced Window and Shading Systems0 aAssessment of the Potential to Achieve Very Low Energy Use in Pu c05/2015 a668-6990 v53 a

As rapid growth in the construction industry continues to occur in China, the increased demand for a higher standard living is driving significant growth in energy use and demand across the country. Building codes and standards have been implemented to head off this trend, tightening prescriptive requirements for fenestration component measures using methods similar to the US model energy code American Society of Heating, Refrigerating and Air-Conditioning Engineers (ASHRAE) 90.1. The objective of this study is to (a) provide an overview of applicable code requirements and current efforts within China to enable characterization and comparison of window and shading products, and (b) quantify the load reduction and energy savings potential of several key advanced window and shading systems, given the divergent views on how space conditioning requirements will be met in the future.

System-level heating and cooling loads and energy use performance were evaluated for a code-compliant large office building using the EnergyPlus building energy simulation program. Commercially-available, highly-insulating, low-emittance windows were found to produce 24-66% lower perimeter zone HVAC electricity use compared to the mandated energy-efficiency standard in force (GB 50189-2005) in cold climates like Beijing. Low-e windows with operable exterior shading produced up to 30-80% reductions in perimeter zone HVAC electricity use in Beijing and 18-38% reductions in Shanghai compared to the standard. The economic context of China is unique since the cost of labor and materials for the building industry is so low. Broad deployment of these commercially available technologies with the proper supporting infrastructure for design, specification, and verification in the field would enable significant reductions in energy use and greenhouse gas emissions in the near term.

10abuilding10aChina10aenergy efficiency10ashading10awindows1 aLee, Eleanor, S.1 aPang, Xiufeng1 aMcNeil, Andrew1 aHoffmann, Sabine1 aThanachareonkit, Anothai1 aLi, Zhengrong1 aDing, Yong uhttps://simulationresearch.lbl.gov/publications/assessment-potential-achieve-very-low00936nas a2200157 4500008004100000245008500041210006900126260003000195520038100225653004400606653001000650100001800660700002200678700002400700856005400724 2015 eng d00aCLIMATE-SPECIFIC MODELING AND ANALYSIS FOR BEST-PRACTICE INDIAN OFFICE BUILDINGS0 aCLIMATESPECIFIC MODELING AND ANALYSIS FOR BESTPRACTICE INDIAN OF aHyderabad, Indiac12/20153 a

This paper describes the methodology and results of building energy modeling to validate and quantify the energy savings from conservation measures in medium-sized office buildings in four different climate zones in India. We present the different energy measures and their expected and simulated performances and discuss the results and the influence of climate. 

10aClimate specific building energy models10aindia1 aSingh, Reshma1 aRavache, Baptiste1 aDutton, Spencer, M. uhttp://www.ibpsa.org/proceedings/BS2015/p2714.pdf02814nas a2200349 4500008003900000245007400039210006900113260001100182490000800193520171300201653003701914653005101951653001402002653003202016653003202048653002602080653002202106653001502128653001502143653001302158653002002171653002402191100001902215700002202234700001702256700002002273700002802293700002002321700001502341700002302356856008502379 2015 d00aCommercial Building Energy Saver: An energy retrofit analysis toolkit0 aCommercial Building Energy Saver An energy retrofit analysis too c9/20150 v1593 a

Small commercial buildings in the United States consume 47% of the total primary energy of the buildings sector. Retrofitting small and medium commercial buildings poses a huge challenge for owners because they usually lack the expertise and resources to identify and evaluate cost-effective energy retrofit strategies. This paper presents the Commercial Building Energy Saver (CBES), an energy retrofit analysis toolkit, which calculates the energy use of a building, identifies and evaluates retrofit measures in terms of energy savings, energy cost savings and payback. The CBES Toolkit includes a web app (APP) for end users and the CBES Application Programming Interface (API) for integrating CBES with other energy software tools. The toolkit provides a rich set of features including: (1) Energy Benchmarking providing an Energy Star score, (2) Load Shape Analysis to identify potential building operation improvements, (3) Preliminary Retrofit Analysis which uses a custom developed pre-simulated database and, (4) Detailed Retrofit Analysis which utilizes real-time EnergyPlus simulations. CBES includes 100 configurable energy conservation measures (ECMs) that encompass IAQ, technical performance and cost data, for assessing 7 different prototype buildings in 16 climate zones in California and 6 vintages. A case study of a small office building demonstrates the use of the toolkit for retrofit analysis. The development of CBES provides a new contribution to the field by providing a straightforward and uncomplicated decision making process for small and medium business owners, leveraging different levels of assessment dependent upon user background, preference and data availability.

10aBuilding Technologies Department10aBuilding Technology and Urban Systems Division10abuildings10abuildings energy efficiency10aCommercial Building Systems10aconservation measures10aenergy efficiency10aenergy use10aenergyplus10aExternal10aRetrofit Energy10asimulation research1 aHong, Tianzhen1 aPiette, Mary, Ann1 aChen, Yixing1 aLee, Sang, Hoon1 aTaylor-Lange, Sarah, C.1 aZhang, Rongpeng1 aSun, Kaiyu1 aPrice, Phillip, N. uhttps://simulationresearch.lbl.gov/publications/commercial-building-energy-saver02384nas a2200253 4500008003900000245010000039210006900139260001200208300001200220490000700232520158600239653002401825653001501849653002201864653002201886653002101908653002501929653002401954100001401978700001201992700001902004700001702023856009002040 2015 d00aData Analysis and Stochastic Modeling of Lighting Energy Use in Large Office Buildings in China0 aData Analysis and Stochastic Modeling of Lighting Energy Use in  c01/2015 a275-2870 v863 a

Lighting consumes about 20% to 40% of the total electricity use in large office buildings in China. Commonly in building simulations, static time schedules for typical weekdays, weekends and holidays are assumed to represent the dynamics of lighting energy use in buildings. This approach does not address the stochastic nature of lighting energy use, which can be influenced by occupant behavior in buildings. This study analyzes the main characteristics of lighting energy use over various timescales, based on the statistical analysis of measured lighting energy use data from 15 large office buildings in Beijing and Hong Kong. It was found that in these large office buildings, the 24-hourly variation in lighting energy use was mainly driven by the schedules of the building occupants. Outdoor illuminance levels had little impact on lighting energy use due to the lack of automatic daylighting controls (an effective retrofit measure to reduce lighting energy use) and the relatively small perimeter area exposed to natural daylight. A stochastic lighting energy use model for large office buildings was further developed to represent diverse occupant activities, at six different time periods throughout a day, and also the annual distribution of lighting power across these periods. The model was verified using measured lighting energy use from the 15 buildings. The developed stochastic lighting model can generate more accurate lighting schedules for use in building energy simulations, improving the simulation accuracy of lighting energy use in real buildings.

10abuilding simulation10aenergy use10aLighting modeling10aoccupant behavior10aoffice buildings10aPoisson distribution10astochastic modeling1 aZhou, Xin1 aYan, Da1 aHong, Tianzhen1 aRen, Xiaoxin uhttps://simulationresearch.lbl.gov/publications/data-analysis-and-stochastic-modeling02285nas a2200241 4500008003900000245007400039210006900113260001200182300000900194490000700203520156400210653002301774653002401797653001501821653001601836653001801852653002201870653001801892100001701910700001201927700001901939856008501958 2015 d00aData Mining of Space Heating System Performance in Affordable Housing0 aData Mining of Space Heating System Performance in Affordable Ho c07/2015 a1-130 v893 a

The space heating in residential buildings accounts for a considerable amount of the primary energy use. Therefore, understanding the operation and performance of space heating systems becomes crucial in improving occupant comfort while reducing energy use. This study investigated the behavior of occupants adjusting their thermostat settings and heating system operations in a 62-unit affordable housing complex in Revere, Massachusetts, USA. The data mining methods, including clustering approach and decision trees, were used to ascertain occupant behavior patterns. Data tabulating ON/OFF space heating states was assessed, to provide a better understanding of the intermittent operation of space heating systems in terms of system cycling frequency and the duration of each operation. The decision tree was used to verify the link between room temperature settings, house and heating system characteristics and the heating energy use. The results suggest that the majority of apartments show fairly constant room temperature profiles with limited variations during a day or between weekday and weekend. Data clustering results revealed six typical patterns of room temperature profiles during the heating season. Space heating systems cycled more frequently than anticipated due to a tight range of room thermostat settings and potentially oversized heating capacities. The results from this study affirm data mining techniques are an effective method to analyze large datasets and extract hidden patterns to inform design and improve operations.

10aaffordable housing10abuilding simulation10aclustering10adata mining10adecision tree10aoccupant behavior10aspace heating1 aRen, Xiaoxin1 aYan, Da1 aHong, Tianzhen uhttps://simulationresearch.lbl.gov/publications/data-mining-space-heating-system02141nas a2200109 4500008003900000245009800039210006900137520170600206100001801912700001901930856008201949 2015 d00aA Data-mining Approach to Discover Patterns of Window Opening and Closing Behavior in Offices0 aDatamining Approach to Discover Patterns of Window Opening and C3 a

Understanding the relationship between occupant behaviors and building energy consumption is one of the most effective ways to bridge the gap between predicted and actual energy consumption in buildings. However effective methodologies to remove the impact of other variables on building energy consumption and isolate the leverage of the human factor precisely are still poorly investigated. Moreover, the effectiveness of statistical and data mining approaches in finding meaningful correlations in data is largely undiscussed in literature. This study develops a framework combining statistical analysis with two data-mining techniques, cluster analysis and association rules mining, to identify valid window operational patterns in measured data. Analyses are performed on a data set with measured indoor and outdoor physical parameters and human interaction with operable windows in 16 offices. Logistic regression was first used to identify factors influencing window opening and closing behavior. Clustering procedures were employed to obtain distinct behavioral patterns, including motivational, opening duration, interactivity and window position patterns. Finally the clustered patterns constituted a base for association rules segmenting the window opening behaviors into two archetypal office user profiles for which different natural ventilation strategies as well as robust building design recommendations that may be appropriate. Moreover, discerned working user profiles represent more accurate input to building energy modeling programs, to investigate the impacts of typical window opening behavior scenarios on energy use, thermal comfort and productivity in office buildings

1 aD'Oca, Simona1 aHong, Tianzhen uhttps://simulationresearch.lbl.gov/publications/data-mining-approach-discover02785nas a2200145 4500008003900000245011200039210006900151520224000220100002002460700001902480700001702499700001702516700002202533856008402555 2015 d00aDEEP: A Database of Energy Efficiency Performance to Accelerate Energy Retrofitting of Commercial Buildings0 aDEEP A Database of Energy Efficiency Performance to Accelerate E3 a

The paper presents a method and process to establish a database of energy efficiency performance (DEEP) to enable quick and accurate assessment of energy retrofit of commercial buildings. DEEP was compiled from results of about 35 million EnergyPlus simulations. DEEP provides energy savings for screening and evaluation of retrofit measures targeting the small and medium-sized office and retail buildings in California. The prototype building models are developed for a comprehensive assessment of building energy performance based on DOE commercial reference buildings and the California DEER prototype buildings. The prototype buildings represent seven building types across six vintages of constructions and 16 California climate zones. DEEP uses these prototypes to evaluate energy performance of about 100 energy conservation measures covering envelope, lighting, heating, ventilation, air-conditioning, plug-loads, and domestic hot water. DEEP consists the energy simulation results for individual retrofit measures as well as packages of measures to consider interactive effects between multiple measures. The large scale EnergyPlus simulations are being conducted on the super computers at the National Energy Research Scientific Computing Center of Lawrence Berkeley National Laboratory. The pre-simulation database is a part of an on-going project to develop a web-based retrofit toolkit for small and medium-sized commercial buildings in California, which provides real-time energy retrofit feedback by querying DEEP with recommended measures, estimated energy savings and financial payback period based on users’ decision criteria of maximizing energy savings, energy cost savings, carbon reduction, or payback of investment. The pre-simulated database and associated comprehensive measure analysis enhances the ability to performance assessments of retrofits to reduce energy use for small and medium buildings and business owners who typically do not have resources to conduct costly building energy audit. DEEP will be migrated into the DEnCity - DOE’s Energy City, which integrates large-scale energy data for multi-purpose, open, and dynamic database leveraging diverse source of existing simulation data.

1 aLee, Sang, Hoon1 aHong, Tianzhen1 aSawaya, Geof1 aChen, Yixing1 aPiette, Mary, Ann uhttps://simulationresearch.lbl.gov/publications/deep-database-energy-efficiency01769nas a2200121 4500008003900000245010800039210006900147520127800216100002001494700001801514700003101532856008401563 2015 d00aDesign choices for thermofluid flow components and systems that are exported as Functional Mockup Units0 aDesign choices for thermofluid flow components and systems that 3 a

This paper discusses design decisions for exporting Modelica thermofluid flow components as Functional Mockup Units. The purpose is to provide guidelines that will allow building energy simulation programs and HVAC equipment manufacturers to effectively use FMUs for modeling of HVAC components and systems. We provide an analysis for direct input-output dependencies of such components and discuss how these dependencies can lead to algebraic loops that are formed when connecting thermofluid flow components. Based on this analysis, we provide recommendations that increase the computing efficiency of such components and systems that are formed by connecting multiple components. We explain what code optimizations are lost when providing thermofluid flow components as FMUs rather than Modelica code. We present an implementation of a package for FMU export of such components, explain the rationale for selecting the connector variables of the FMUs and finally provide computing benchmarks for different design choices. It turns out that selecting temperature rather than specific enthalpy as input and output signals does not lead to a measurable increase in computing time, but selecting nine small FMUs rather than a large FMU increases computing time by 70%

1 aWetter, Michael1 aFuchs, Marcus1 aNouidui, Thierry, Stephane uhttps://simulationresearch.lbl.gov/publications/design-choices-thermofluid-flow02134nas a2200253 4500008003900000245009200039210006900131260001100200490000800211520133600219653002401555653002001579653001501599653001401614653002101628653003001649100001901679700001501698700002001713700002101733700002301754700002001777856008301797 2015 d00aDevelopment and validation of a new variable refrigerant flow systemmodel in EnergyPlus0 aDevelopment and validation of a new variable refrigerant flow sy c9/20150 v1173 a

Variable refrigerant flow (VRF) systems vary the refrigerant flow to meet the dynamic zone thermalloads, leading to more efficient operations than other system types. This paper introduces a new modelthat simulates the energy performance of VRF systems in the heat pump (HP) operation mode. Com-pared with the current VRF-HP models implemented in EnergyPlus, the new VRF system model has morecomponent models based on physics and thus has significant innovations in: (1) enabling advanced con-trols, including variable evaporating and condensing temperatures in the indoor and outdoor units, andvariable fan speeds based on the temperature and zone load in the indoor units, (2) adding a detailedrefrigerant pipe heat loss calculation using refrigerant flow rate, operational conditions, pipe length, andpipe insulation materials, (3) improving accuracy of simulation especially in partial load conditions, and(4) improving the usability of the model by significantly reducing the number of user input performancecurves. The VRF-HP model is implemented in EnergyPlus and validated with measured data from fieldtests. Results show that the new VRF-HP model provides more accurate estimate of the VRF-HP systemperformance, which is key to determining code compliance credits as well as utilities incentive for VRFtechnologies.

10abuilding simulation10aenergy modeling10aenergyplus10aHeat pump10amodel validation10aVariable refrigerant flow1 aHong, Tianzhen1 aSun, Kaiyu1 aZhang, Rongpeng1 aHinokuma, Ryohei1 aKasahara, Shinichi1 aYura, Yoshinori uhttps://simulationresearch.lbl.gov/publications/development-and-validation-new02128nas a2200241 4500008003900000245007200039210006900111260002700180300001400207490000700221520132000228653003001548653003301578653002301611653002201634653002901656653002701685100002001712700001901732700002201751700002801773856008501801 2015 d00aEnergy retrofit analysis toolkit for commercial buildings: A review0 aEnergy retrofit analysis toolkit for commercial buildings A revi bElsevier Ltd.c09/2015 a1087-11000 v893 a

Retrofit analysis toolkits can be used to optimize energy or cost savings from retrofit strategies, accelerating the adoption of ECMs (energy conservation measures) in buildings. This paper provides an up-todate review of the features and capabilities of 18 energy retrofit toolkits, including ECMs and the calculation engines. The fidelity of the calculation techniques, a driving component of retrofit toolkits, were evaluated. An evaluation of the issues that hinder effective retrofit analysis in terms of accessibility, usability, data requirement, and the application of efficiency measures, provides valuable insights into advancing the field forward. Following this review the general concepts were determined: (1) toolkits developed primarily in the private sector use empirically data-driven methods or benchmarking to provide ease of use, (2) almost all of the toolkits which used EnergyPlus or DOE-2 were freely accessible, but suffered from complexity, longer data input and simulation run time, (3) in general, there appeared to be a fine line between having too much detail resulting in a long analysis time or too little detail which sacrificed modeling fidelity. These insights provide an opportunity to enhance the design and development of existing and new retrofit toolkits in the future.

10aBuilding energy retrofit10aEnergy conservation measures10aEnergy efficiency10aEnergy simulation10aRetrofit analysis tools10aWeb-based applications1 aLee, Sang, Hoon1 aHong, Tianzhen1 aPiette, Mary, Ann1 aTaylor-Lange, Sarah, C. uhttps://simulationresearch.lbl.gov/publications/energy-retrofit-analysis-toolkit01796nas a2200217 4500008003900000245010600039210006900145260001200214300001200226490000800238520106600246653002801312653001301340653002901353653002001382653001501402100002001417700001901437700003101456856009101487 2015 d00aEquation-based languages – A new paradigm for building energy modeling, simulation and optimization0 aEquationbased languages A new paradigm for building energy model c04/2016 a290-3000 v1173 a

Most of the state-of-the-art building simulation programs implement models in imperative programming languages. This complicates modeling and excludes the use of certain efficient methods for simulation and optimization. In contrast, equation-based modeling languages declare relations among variables, thereby allowing the use of computer algebra to enable much simpler schematic modeling and to generate efficient code for simulation and optimization.

We contrast the two approaches in this paper. We explain how such manipulations support new use cases. In the first of two examples, we couple models of the electrical grid, multiple buildings, HVAC systems and controllers to test a controller that adjusts building room temperatures and PV inverter reactive power to maintain power quality. In the second example, we contrast the computing time for solving an optimal control problem for a room-level model predictive controller with and without symbolic manipulations. Exploiting the equation-based language led to 2200 times faster solution.

10aEquation-based modeling10amodelica10aMulti-physics simulation10aOptimal control10asmart grid1 aWetter, Michael1 aBonvini, Marco1 aNouidui, Thierry, Stephane uhttps://simulationresearch.lbl.gov/publications/equation-based-languages-%E2%80%93-new02052nas a2200217 4500008003900000245008100039210006900120260005100189520129700240100001601537700002401553700002001577700002501597700001801622700001901640700002101659700002201680700002101702700002701723856008401750 2015 d00aGreen, Clean, & Mean: Pushing the Energy Envelope in Tech Industry Buildings0 aGreen Clean Mean Pushing the Energy Envelope in Tech Industry Bu bLawrence Berkeley National Laboratoryc05/20153 a

When it comes to innovation in energy and building performance, one can expect leading-edge activity from the technology sector. As front-line innovators in design, materials science, and information management, developing and operating high-performance buildings is a natural extension of their core business.

The energy choices made by technology companies have broad importance given their influence on society at large as well as the extent of their own energy footprint. Microsoft, for example, has approximately 250 facilities around the world (30 million square feet of floor area), with significant aggregate energy use of approximately 4 million kilowatt-hours per day.

There is a degree of existing documentation of efforts to design, build, and operate facilities in the technology sector. However, the material is fragmented and typically looks only at a single company, or discrete projects within a company.Yet, there is no single resource for corporate planners and decision makers that takes stock of the opportunities and documents sector-specific case studies in a structured manner. This report seeks to fill that gap, doing so through a combination of generalized technology assessments (“Key Strategies”) and case studies (“Flagship Projects”).

1 aMills, Evan1 aGranderson, Jessica1 aChan, Wanyu, R.1 aDiamond, Richard, C.1 aHaves, Philip1 aNordman, Bruce1 aMathew, Paul, A.1 aPiette, Mary, Ann1 aRobinson, Gerald1 aSelkowitz, Stephen, E. uhttps://simulationresearch.lbl.gov/publications/green-clean-mean-pushing-energy02767nas a2200193 4500008003900000245008400039210006900123520210600192653002202298653002602320653002002346653003102366653002202397653002302419100001402442700001902456700001202475856008602487 2015 d00aAn Insight into Actual Energy Use and Its Drivers in High-Performance Buildings0 aInsight into Actual Energy Use and Its Drivers in HighPerformanc3 a

Using portfolio analysis and individual detailed case studies, we studied the energy performance and drivers of energy use in 51 high-performance office buildings in the U.S., Europe, China, and other parts of Asia. Portfolio analyses revealed that actual site energy use intensity (EUI) of the study buildings varied by a factor of as much as 11, indicating significant variation in real energy use in HPBs worldwide. Nearly half of the buildings did not meet the American Society of Heating, Refrigerating, and Air Conditioning Engineers (ASHRAE) Standard 90.1-2004 energy target, raising questions about whether a building’s certification as high performing accurately indicates that a building is energy efficient and suggesting that improvement in the design and operation of HPBs is needed to realize their energy-saving potential. We studied the influence of climate, building size, and building technologies on building energy performance and found that although all are important, none are decisive factors in building energy use. EUIs were widely scattered in all climate zones. There was a trend toward low energy use in small buildings, but the correlation was not absolute; some small HPBs exhibited high energy use, and some large HPBs exhibited low energy use. We were unable to identify a set of efficient technologies that correlated directly to low EUIs. In two case studies, we investigated the influence of occupant behavior as well as operation and maintenance on energy performance and found that both play significant roles in realizing energy savings. We conclude that no single factor determines the actual energy performance of HPBs, and adding multiple efficient technologies does not necessarily improve building energy performance; therefore, an integrated design approach that takes account of climate, technology, occupant behavior, and operations and maintenance practices should be implemented to maximize energy savings in HPBs. These findings are intended to help architects, engineers, operators, and policy makers improve the design and operation of HPBs.

10aactual energy use10abuilding technologies10adriving factors10ahigh-performance buildings10aintegrated design10aperformance rating1 aLi, Cheng1 aHong, Tianzhen1 aYan, Da uhttps://simulationresearch.lbl.gov/publications/insight-actual-energy-use-and-its00387nas a2200121 4500008003900000245003100039210003100070100002000101700001600121700003100137700001800168856007900186 2015 d00aModelica Buildings Library0 aModelica Buildings Library1 aWetter, Michael1 aZuo, Wangda1 aNouidui, Thierry, Stephane1 aPang, Xiufeng uhttps://simulationresearch.lbl.gov/publications/modelica-buildings-library02039nas a2200217 4500008003900000245007300039210006900112260001200181300001200193490000700205520135500212653002301567653002401590653001601614653002301630653002201653653002001675100001801695700001901713856008901732 2015 d00aOccupancy Schedules Learning Process Through a Data Mining Framework0 aOccupancy Schedules Learning Process Through a Data Mining Frame c02/2015 a395-4080 v883 a

Building occupancy is a paramount factor in building energy simulations. Specifically, lighting, plug loads, HVAC equipment utilization, fresh air requirements and internal heat gain or loss greatly depends on the level of occupancy within a building. Developing the appropriate methodologies to describe and reproduce the intricate network responsible for human-building interactions are needed. Extrapolation of patterns from big data streams is a powerful analysis technique which will allow for a better understanding of energy usage in buildings. A three-step data mining framework is applied to discover occupancy patterns in office spaces. First, a data set of 16 offices with 10 min interval occupancy data, over a two year period is mined through a decision tree model which predicts the occupancy presence. Then a rule induction algorithm is used to learn a pruned set of rules on the results from the decision tree model. Finally, a cluster analysis is employed in order to obtain consistent patterns of occupancy schedules. The identified occupancy rules and schedules are representative as four archetypal working profiles that can be used as input to current building energy modeling programs, such as EnergyPlus or IDA-ICE, to investigate impact of occupant presence on design, operation and energy use in office buildings.

10aBehavioral Pattern10abuilding simulation10adata mining10aOccupancy schedule10aoccupant behavior10aOffice Building1 aD'Oca, Simona1 aHong, Tianzhen uhttps://simulationresearch.lbl.gov/publications/occupancy-schedules-learning-process01728nas a2200265 4500008003900000245010500039210006900144260001200213300001200225490000800237520089300245653002401138653002201162653002001184653001501204653002201219100001201241700002101253700001901274700001901293700001701312700002301329700002201352856008801374 2015 d00aOccupant Behavior Modeling for Building Performance Simulation: Current State and Future Challenges0 aOccupant Behavior Modeling for Building Performance Simulation C c11/2015 a264-2780 v1073 a

Occupant behavior is now widely recognized as a major contributing factor to uncertainty of building performance. While a surge of research on the topic has occurred over the past four decades, and particularly the past few years, there are many gaps in knowledge and limitations to current methodologies. This paper outlines the state-of-the-art research, current obstacles and future needs and directions for the following four-step iterative process: (1) occupant monitoring and data collection, (2) model development, (3) model evaluation, and (4) model implementation into building simulation tools. Major themes include the need for greater rigor in experimental methodologies; detailed, honest, and candid reporting of methods and results; and development of an efficient means to implement occupant behavior models and integrate them into building energy modeling programs.

10abuilding simulation10aenergy efficiency10aenergy modeling10aenergy use10aoccupant behavior1 aYan, Da1 aO'Brien, William1 aHong, Tianzhen1 aFeng, Xiaohang1 aGunay, Burak1 aTahmasebi, Farhang1 aMahdavi, Ardeshir uhttps://simulationresearch.lbl.gov/publications/occupant-behavior-modeling-building02313nas a2200265 4500008003900000245014200039210006900181260001200250300001200262490000700274520142200281653003201703653002401735653002001759653001001779653002201789653001501811100001901826700001801845700002801863700002701891700001701918700002601935856008601961 2015 d00aAn Ontology to Represent Energy-Related Occupant Behavior in Buildings. Part II: Implementation of the DNAS framework using an XML schema0 aOntology to Represent EnergyRelated Occupant Behavior in Buildin c08/2015 a196-2050 v943 a

Energy-related occupant behavior in buildings is difficult to define and quantify, yet critical to our understanding of total building energy consumption. Part I of this two-part paper introduced the DNAS (Drivers, Needs, Actions and Systems) framework, to standardize the description of energy-related occupant behavior in buildings. Part II of this paper implements the DNAS framework into an XML (eXtensible Markup Language) schema, titled ‘occupant behavior XML’ (obXML). The obXML schema is used for the practical implementation of the DNAS framework into building simulation tools. The topology of the DNAS framework implemented in the obXML schema has a main root element OccupantBehavior, linking three main elements representing Buildings, Occupants and Behaviors. Using the schema structure, the actions of turning on an air conditioner and closing blinds provide two examples of how the schema standardizes these actions using XML. The obXML schema has inherent flexibility to represent numerous, diverse and complex types of occupant behaviors in buildings, and it can also be expanded to encompass new types of behaviors. The implementation of the DNAS framework into the obXML schema will facilitate the development of occupant information modeling (OIM) by providing interoperability between occupant behavior models and building energy modeling programs.

10abuilding energy consumption10abuilding simulation10aenergy modeling10aobXML10aoccupant behavior10aXML schema1 aHong, Tianzhen1 aD'Oca, Simona1 aTaylor-Lange, Sarah, C.1 aTurner, William, J. N.1 aChen, Yixing1 aCorgnati, Stefano, P. uhttps://simulationresearch.lbl.gov/publications/ontology-represent-energy-related02575nas a2200241 4500008003900000245011800039210006900157260001200226300001200238490000700250520177500257653002002032653003802052653001302090653002202103653001302125653001502138100001902153700001802172700002702190700002802217856008802245 2015 d00aAn Ontology to Represent Energy-related Occupant Behavior in Buildings Part I: Introduction to the DNAs Framework0 aOntology to Represent Energyrelated Occupant Behavior in Buildin c10/2015 a764-7770 v923 a

Reducing energy consumption in the buildings sector requires significant changes, but technology alone may fail to guarantee efficient energy performance. Human behavior plays a pivotal role in building design, operation, management and retrofit, and is a crucial positive factor for improving the indoor environment, while reducing energy use at low cost. Over the past 40 years, a substantial body of literature has explored the impacts of human behavior on building technologies and operation. Often, need-action-event cognitive theoretical frameworks were used to represent human-machine interactions. In Part I of this paper a review of more than 130 published behavioral studies and frameworks was conducted. A large variety of data-driven behavioral models have been developed based on field monitoring of the human-building-system interaction. Studies have emerged scattered geographically around the world that lack in standardization and consistency, thus leading to difficulties when comparing one with another. To address this problem, an ontology to represent energy-related occupant behavior in buildings is presented. Accordingly, the technical DNAs framework is developed based on four key components: i) the Drivers of behavior, ii) the Needs of the occupants, iii) the Actions carried out by the occupants, and iv) the building systems acted upon by the occupants. This DNAs framework is envisioned to support the international research community to standardize a systematic representation of energy-related occupant behavior in buildings. Part II of this paper further develops the DNAs framework as an XML (eXtensible Markup Language) schema, obXML, for exchange of occupant information modeling and integration with building simulation tools.

10aBuilding energy10ahuman-building-system interaction10amodeling10aoccupant behavior10aontology10asimulation1 aHong, Tianzhen1 aD'Oca, Simona1 aTurner, William, J. N.1 aTaylor-Lange, Sarah, C. uhttps://simulationresearch.lbl.gov/publications/ontology-represent-energy-related-002242nas a2200133 4500008003900000245007600039210006900115520175500184100001501939700001901954700002801973700002202001856008502023 2015 d00aA pattern-based automated approach to building energy model calibration0 apatternbased automated approach to building energy model calibra3 a

Building model calibration is critical in bringing simulated energy use closer to the actual consumption. This paper presents a novel, automated model calibration approach that uses logic linking parameter tuning with bias pattern recognition to overcome some of the disadvantages associated with traditional calibration processes. The pattern-based process contains four key steps: (1) running the original precalibrated energy model to obtain monthly simulated electricity and gas use; (2) establishing a pattern bias, either Universal or Seasonal Bias, by comparing load shape patterns of simulated and actual monthly energy use; (3) using programmed logic to select which parameter to tune first based on bias pattern, weather and input parameter interactions; and (4) automatically tuning the calibration parameters and checking the progress using pattern-fit criteria. The automated calibration algorithm was implemented in the Commercial Building Energy Saver, a web-based building energy retrofit analysis toolkit. The proof of success of the methodology was demonstrated using a case study of an office building located in San Francisco. The case study inputs included the monthly electricity bill, monthly gas bill, original building model and weather data with outputs resulting in a calibrated model that more closely matched that of the actual building energy use profile. The novelty of the developed calibration methodology lies in linking parameter tuning with the underlying logic associated with bias pattern identification. Although there are some limitations to this approach, the pattern-based automated calibration methodology can be universally adopted as an alternative to manual or hierarchical calibration approaches.

1 aSun, Kaiyu1 aHong, Tianzhen1 aTaylor-Lange, Sarah, C.1 aPiette, Mary, Ann uhttps://simulationresearch.lbl.gov/publications/pattern-based-automated-approach01903nas a2200229 4500008003900000245004100039210004100080260001200121300001200133490000700145520126600152653002401418653001801442653001401460653002201474653002001496653002401516100001901540700001201559700001901571856008301590 2015 d00aSimulation of Occupancy in Buildings0 aSimulation of Occupancy in Buildings c01/2015 a348-3590 v873 a

Occupants are involved in a variety of activities in buildings, which drive them to move among rooms, enter or leave a building. In this study, occupancy is defined at four levels and varies with time: (1) the number of occupants in a building, (2) occupancy status of a space, (3) the number of occupants in a space, and (4) the space location of an occupant. Occupancy has a great influence on internal loads and ventilation requirement, thus building energy consumption. Based on a comprehensive review and comparison of literature on occupancy modeling, three representative occupancy models, corresponding to the levels 2–4, are selected and implemented in a software module. Main contributions of our study include: (1) new methods to classify occupancy models, (2) the review and selection of various levels of occupancy models, and (3) new methods to integrate these model into a tool that can be used in different ways for different applications and by different audiences. The software can simulate more detailed occupancy in buildings to improve the simulation of energy use, and better evaluate building technologies in buildings. The occupancy of an office building is simulated as an example to demonstrate the use of the software module.

10abuilding simulation10aco-simulation10aoccupancy10aoccupant behavior10asoftware module10astochastic modeling1 aFeng, Xiaohang1 aYan, Da1 aHong, Tianzhen uhttps://simulationresearch.lbl.gov/publications/simulation-occupancy-buildings01114nas a2200121 4500008003900000245009700039210006900136520064700205100002000852700002000872700001800892856008200910 2015 d00aSimulation Speed Analysis and Improvements of Modelica Models for Building Energy Simulation0 aSimulation Speed Analysis and Improvements of Modelica Models fo3 a

This paper presents an approach for speeding up Modelica models. Insight is provided into how Modelica models are solved and what determines the tool’s computational speed. Aspects such as algebraic loops, code efficiency and integrator choice are discussed. This is illustrated using simple building simulation examples and Dymola. The generality of the work is in some cases verified using OpenModelica. Using this approach, a medium sized office building including building envelope, heating ventilation and air conditioning (HVAC) systems and control strategy can be simulated at a speed five hundred times faster than real time.

1 aJorissen, Filip1 aWetter, Michael1 aHelsen, Lieve uhttps://simulationresearch.lbl.gov/publications/simulation-speed-analysis-and02025nas a2200229 4500008003900000245008400039210006900123260001200192300001200204490000700216520132300223653002001546653002901566653001001595653002201605653001301627653002101640100001901661700001401680700001201694856008901706 2015 d00aUpdates to the China Design Standard for Energy Efficiency in Public Buildings0 aUpdates to the China Design Standard for Energy Efficiency in Pu c12/2015 a187-1980 v873 a

The China Design Standard for Energy Efficiency in public buildings (GB 50189) debuted in 2005 when China completed the 10th Five-Year Plan. GB 50189-2005 played a crucial role in regulating the energy efficiency in Chinese commercial buildings. The standard was recently updated in 2014 to increase energy savings targets by 30% compared with the 2005 standard. This paper reviews the major changes to the standard, including expansion of energy efficiency coverage and more stringent efficiency requirements. The paper also discusses the interrelationship of the design standard with China's other building energy standards. Furthermore, comparisons are made with ASHRAE Standard 90.1-2013 to provide contrasting differences in efficiency requirements. Finally recommendations are provided to guide the future standard revision, focusing on three areas: (1) increasing efficiency requirements of building envelope and HVAC systems, (2) adding a whole-building performance compliance pathway and implementing a ruleset based automatic code baseline model generation in an effort to reduce the discrepancies of baseline models created by different tools and users, and (3) adding inspection and commissioning requirements to ensure building equipment and systems are installed correctly and operate as designed.

10abuilding design10abuilding energy standard10aChina10aenergy efficiency10aGB 5018910aPublic buildings1 aHong, Tianzhen1 aLi, Cheng1 aYan, Da uhttps://simulationresearch.lbl.gov/publications/updates-china-design-standard-energy02234nas a2200313 4500008003900000245007900039210006900118260001200187300001200199490000700211520134300218653001401561653001501575653001801590653001501608653002401623653002901647653001501676653001301691100001701704700001901721700001301740700001401753700001301767700001501780700001501795700002201810856008801832 2014 d00aComparison of Building Energy Use Data Between the United States and China0 aComparison of Building Energy Use Data Between the United States c08/2014 a165-1750 v783 a

Buildings in the United States and China consumed 41% and 28% of the total primary energy in 2011, respectively. Good energy data are the cornerstone to understanding building energy performance and supporting research, design, operation, and policy making for low energy buildings. This paper presents initial outcomes from a joint research project under the U.S.–China Clean Energy Research Center for Building Energy Efficiency. The goal is to decode the driving forces behind the discrepancy of building energy use between the two countries; identify gaps and deficiencies of current building energy monitoring, data collection, and analysis; and create knowledge and tools to collect and analyze good building energy data to provide valuable and actionable information for key stakeholders. This paper first reviews and compares several popular existing building energy monitoring systems in both countries. Next a standard energy data model is presented. A detailed, measured building energy data comparison was conducted for a few office buildings in both countries. Finally issues of data collection, quality, sharing, and analysis methods are discussed. It was found that buildings in both countries performed very differently, had potential for deep energy retrofit, but that different efficiency measures should apply.

10abuildings10acomparison10adata analysis10adata model10aEnergy benchmarking10aenergy monitoring system10aenergy use10aretrofit1 aXia, Jianjun1 aHong, Tianzhen1 aShen, Qi1 aFeng, Wei1 aYang, Le1 aIm, Piljae1 aLu, Alison1 aBhandari, Mahabir uhttps://simulationresearch.lbl.gov/publications/comparison-building-energy-use-data03531nas a2200241 4500008003900000245007900039210006900118260002200187300001100209490000800220520280200228653001403030653001503044653002403059653001503083653003103098653001303129100001903142700001303161700001603174700001403190856008503204 2014 d00aData and Analytics to Inform Energy Retrofit of High Performance Buildings0 aData and Analytics to Inform Energy Retrofit of High Performance bElsevierc08/2014 a90-1060 v1263 a

Buildings consume more than one-third of the world’s primary energy. Reducing energy use in buildings with energy efficient technologies is feasible and also driven by energy policies such as energy benchmarking, disclosure, rating, and labeling in both the developed and developing countries. Current energy retrofits focus on the existing building stocks, especially older buildings, but the growing number of new high performance buildings built around the world raises a question that how these buildings perform and whether there are retrofit opportunities to further reduce their energy use. This is a new and unique problem for the building industry. Traditional energy audit or analysis methods are inadequate to look deep into the energy use of the high performance buildings. This study aims to tackle this problem with a new holistic approach powered by building performance data and analytics. First, three types of measured data are introduced, including the time series energy use, building systems operating conditions, and indoor and outdoor environmental parameters. An energy data model based on the ISO Standard 12655 is used to represent the energy use in buildings in a three-level hierarchy. Secondly, a suite of analytics were proposed to analyze energy use and to identify retrofit measures for high performance buildings. The data-driven analytics are based on monitored data at short time intervals, and cover three levels of analysis – energy profiling, benchmarking and diagnostics. Thirdly, the analytics were applied to a high performance building in California to analyze its energy use and identify retrofit opportunities, including: (1) analyzing patterns of major energy end-use categories at various time scales, (2) benchmarking the whole building total energy use as well as major end-uses against its peers, (3) benchmarking the power usage effectiveness for the data center, which is the largest electricity consumer in this building, and (4) diagnosing HVAC equipment using detailed time-series operating data. Finally, a few energy efficiency measures were identified for retrofit, and their energy savings were estimated to be 20% of the whole-building electricity consumption. Based on the analyses, the building manager took a few steps to improve the operation of fans, chillers, and data centers, which will lead to actual energy savings. This study demonstrated that there are energy retrofit opportunities for high performance buildings and detailed measured building performance data and analytics can help identify and estimate energy savings and to inform the decision making during the retrofit process. Challenges of data collection and analytics were also discussed to shape best practice of retrofitting high performance buildings.

10aAnalytics10adata model10aEnergy benchmarking10aenergy use10aHigh performance buildings10aretrofit1 aHong, Tianzhen1 aYang, Le1 aHill, David1 aFeng, Wei uhttps://simulationresearch.lbl.gov/publications/data-and-analytics-inform-energy03143nas a2200229 4500008003900000024002700039245009400066210006900160260004200229520232200271653003802593653003402631653000802665653003302673653002502706100001802731700002002749700002002769700002102789700002402810856007902834 2014 d aCEC‐500‐2015‐00100aDevelopment of Diagnostic and Measurement and Verification Tools for Commercial Buildings0 aDevelopment of Diagnostic and Measurement and Verification Tools bCalifornia Energy Commissionc09/20143 a

This research developed new measurement and verification tools and new automated fault detection and diagnosis tools, and deployed them in the Universal Translator. The Universal Translator is a tool, developed by Pacific Gas and Electric, that manages large sets of measured data from building control systems and enables off‐line analysis of building performance. There were four technical projects following the program administration tasks identified as Project 1:

  1. Program Administration
  2. Methods and Tools to Reduce the Cost of Measurement and Verification.
  3. Fault Detection and Diagnostics for Commercial Heating, Ventilating, and Air‐ Conditioning Systems.
  4. Test Procedures and Tools to Characterize Fan and Duct System Performance in Large Commercial Buildings.
  5. Universal Translator Development: Integration of Application Programming Interface.

Project 1 consisted of administrative tasks related to the project.

Project 2 addressed the need for less expensive measurement and verification tools to determine the costs and benefits of retrofits and retro‐commissioning at both the individual building level and the utility program level.

Project 3 extended previous work on fault detection and diagnosis to additional systems and subsystems, including dual duct heating, ventilating and air‐conditioning systems and fan‐coil terminal units.

Project 4 combined previous work on duct leakage and fan modeling to develop a performance assessment method for existing fan/duct systems that could also be used in the analysis of retrofit measures identified by the tools in Projects 2 and 3 using the EnergyPlus simulation program to help select the most cost‐effective package of improvements.

Some of the diagnostic methods and tools developed in projects 2 through 4 were incorporated in the Universal Translator via a new application programming interface that was specified, developed and tested in Project 5. Combined, these tools support analyses of energy savings produced by new construction commissioning, retro‐commissioning, improved routine operations and code compliance. The new application programming interface could also facilitate future development, testing and deployment of new diagnostic tools.

10aapplication programming interface10afault detection and diagnosis10aM&V10aMeasurement and verification10aUniversal Translator1 aHaves, Philip1 aWray, Craig, P.1 aJump, David, A.1 aVeronica, Daniel1 aFarley, Christopher uhttps://simulationresearch.lbl.gov/publications/development-diagnostic-and00559nas a2200181 4500008003900000245005300039210005300092100001900145700001400164700002500178700001200203700001400215700001400229700001500243700001500258700001700273856008700290 2014 d00aIntegrated Design for High Performance Buildings0 aIntegrated Design for High Performance Buildings1 aHong, Tianzhen1 aLi, Cheng1 aDiamond, Richard, C.1 aYan, Da1 aZhang, Qi1 aZhou, Xin1 aGuo, Siyue1 aSun, Kaiyu1 aWang, Jingyi uhttps://simulationresearch.lbl.gov/publications/integrated-design-high-performance02607nas a2200169 4500008003900000245006200039210006000101520204900161100001902210700001802229700001902247700001702266700002302283700002002306700002102326856009002347 2014 d00aA New Model to Simulate Energy Performance of VRF Systems0 aNew Model to Simulate Energy Performance of VRF Systems3 a

This paper presents a new model to simulate energy performance of variable refrigerant flow (VRF) systems in heat pump operation mode (either cooling or heating is provided but not simultaneously). The main improvement of the new model is the introduction of the evaporating and condensing temperature in the indoor and outdoor unit capacity modifier functions. The independent variables in the capacity modifier functions of the existing VRF model in EnergyPlus are mainly room wet-bulb temperature and outdoor dry-bulb temperature in cooling mode and room dry-bulb temperature and outdoor wet-bulb temperature in heating mode. The new approach allows compliance with different specifications of each indoor unit so that the modeling accuracy is improved. The new VRF model was implemented in a custom version of EnergyPlus 7.2. This paper first describes the algorithm for the new VRF model, which is then used to simulate the energy performance of a VRF system in a Prototype House in California that complies with the requirements of Title 24 – the California Building Energy Efficiency Standards. The VRF system performance is then compared with three other types of HVAC systems: the Title 24-2005 Baseline system, the traditional High Efficiency system, and the EnergyStar Heat Pump system in three typical California climates: Sunnyvale, Pasadena and Fresno. Calculated energy savings from the VRF systems are significant. The HVAC site energy savings range from 51 to 85%, while the TDV (Time Dependent Valuation) energy savings range from 31 to 66% compared to the Title 24 Baseline Systems across the three climates. The largest energy savings are in Fresno climate followed by Sunnyvale and Pasadena. The paper discusses various characteristics of the VRF systems contributing to the energy savings. It should be noted that these savings are calculated using the Title 24 prototype House D under standard operating conditions. Actual performance of the VRF systems for real houses under real operating conditions will vary.

1 aHong, Tianzhen1 aPang, Xiufeng1 aSchetrit, Oren1 aWang, Liping1 aKasahara, Shinichi1 aYura, Yoshinori1 aHinokuma, Ryohei uhttps://simulationresearch.lbl.gov/publications/new-model-simulate-energy-performance00390nas a2200109 4500008003900000245004500039210004500084100002000129700001900149700002200168856009000190 2014 d00aReview of Existing Energy Retrofit Tools0 aReview of Existing Energy Retrofit Tools1 aLee, Sang, Hoon1 aHong, Tianzhen1 aPiette, Mary, Ann uhttps://simulationresearch.lbl.gov/publications/review-existing-energy-retrofit-tools02422nas a2200121 4500008003900000245007300039210006900112260003300181520192500214100001402139700001902153856012802172 2014 d00aRevisit of Energy Use and Technologies of High Performance Buildings0 aRevisit of Energy Use and Technologies of High Performance Build aSeattle, WAbASHRAEc06/20143 a

Energy consumed by buildings accounts for one third of the world’s total primary energy use. Associated with the conscious of energy savings in buildings, High Performance Buildings (HPBs) has surged across the world, with wide promotion and adoption of various performance rating and certification systems. It is valuable to look into the actual energy performance of HPBs and to understand their influencing factors.

To shed some light on this topic, this paper conducted a series of portfolio analysis based on a database of 51 high performance office buildings across the world. Analyses showed that the actual site Energy Use Intensity (EUI) of the 51 buildings varied by a factor of up to 11, indicating a large scale of variation of the actual energy performance of the current HPBs. Further analysis of the correlation between EUI and climate elucidated ubiquitous phenomenon of EUI scatter throughout all climate zones, implying that the weather is not a decisive factor, although important, for the actual energy consumption of an individual building. On the building size via EUI, analysis disclosed that smaller buildings have a tendency to achieving lower energy use. Even so, the correlation is not absolute since some large buildings demonstrated low energy use while some small buildings performed opposite. Concerning the technologies, statistics indicated that the application of some technologies had correlations with some specific building size and climate characteristic. However, it was still hard to pinpoint a set of technologies which was directly correlative with a group of low EUI buildings.

It is concluded that no a single factor essentially determines the actual energy performance of HPBs. To deliver energy-efficient buildings, an integrated design taking account of climate, technology, occupant behavior as well as operation and maintenance should be implemented.

1 aLi, Cheng1 aHong, Tianzhen uhttps://www.techstreet.com/ashrae/standards/se-14-c033-revisit-of-energy-use-and-technologies-of-high-performance-buildings01865nas a2200145 4500008004100000245014400041210006900185260001200254490000700266520130200273100002101575700001801596700002101614856008401635 2014 eng d00aThe Role of International Partnerships in Delivering Low- Energy Building Design: A Case Study of the Singapore Scientific Planning Process0 aRole of International Partnerships in Delivering Low Energy Buil c05/20140 v143 a

This paper explores the role of international partnerships to facilitate low-energy building
design, construction, and operations. We briefly discuss multiple collaboration models
and the levels of impact they support. We present a case study of one collaborative
partnership model, the Scientific Planning Support (SPS) team. Staff from the Lawrence
Berkeley National Laboratory, the Austrian Institute of Technology, and Nanyang
Technological University formed the SPS team to provide design assistance and process
support during the design phase of a low-energy building project. Specifically, the SPS
team worked on the Clean Tech Two project, a tenanted laboratory and office building
that seeks Green Mark Platinum, the highest green building certification in Singapore.
The SPS team hosted design charrettes, helped to develop design alternatives, and
provided suggestions on the design process in support of this aggressive energy target.
This paper describes these efforts and discusses how teams like the SPS team and other partnership schemes can be leveraged to achieve high performance, low-energy buildingsat an international scale.

1 aParrish, Kristen1 aSingh, Reshma1 aChien, Szu-Cheng uhttps://simulationresearch.lbl.gov/publications/role-international-partnerships02296nas a2200193 4500008003900000245011200039210006900151520161300220653002401833653002401857653002201881653002201903653002301925653002401948100001501972700001901987700001502006856008102021 2014 d00aStochastic Modeling of Overtime Occupancy and Its Application in Building Energy Simulation and Calibration0 aStochastic Modeling of Overtime Occupancy and Its Application in3 a

Overtime is a common phenomenon around the world. Overtime drives both internal heat gains from occupants, lighting and plug-loads, and HVAC operation during overtime periods. Overtime leads to longer occupancy hours and extended operation of building services systems beyond normal working hours, thus overtime impacts total building energy use. Current literature lacks methods to model overtime occupancy because overtime is stochastic in nature and varies by individual occupants and by time. To address this gap in the literature, this study aims to develop a new stochastic model based on the statistical analysis of measured overtime occupancy data from an office building. A binomial distribution is used to represent the total number of occupants working overtime, while an exponential distribution is used to represent the duration of overtime periods. The overtime model is used to generate overtime occupancy schedules as an input to the energy model of a second office building. The measured and simulated cooling energy use during the overtime period is compared in order to validate the overtime model. A hybrid approach to energy model calibration is proposed and tested, which combines ASHRAE Guideline 14 for the calibration of the energy model during normal working hours, and a proposed KS test for the calibration of the energy model during overtime. The developed stochastic overtime model and the hybrid calibration approach can be used in building energy simulations to improve the accuracy of results, and better understand the characteristics of overtime in office buildings.

10abuilding energy use10abuilding simulation10amodel calibration10aoccupant behavior10aovertime occupancy10astochastic modeling1 aSun, Kaiyu1 aHong, Tianzhen1 aGuo, Siyue uhttps://simulationresearch.lbl.gov/publications/stochastic-modeling-overtime02814nas a2200169 4500008003900000245008800039210006900127520221500196653002402411653002202435653001402457653002202471653001502493100002702508700001902535856009002554 2014 d00aA Technical Framework to Describe Occupant Behavior for Building Energy Simulations0 aTechnical Framework to Describe Occupant Behavior for Building E3 a

Green buildings that fail to meet expected design performance criteria indicate that technology alone does not guarantee high performance. Human influences are quite often simplified and ignored in the design, construction, and operation of buildings. Energy-conscious human behavior has been demonstrated to be a significant positive factor for improving the indoor environment while reducing the energy use of buildings. In our study we developed a new technical framework to describe energy-related human behavior in buildings. The energy-related behavior includes accounting for individuals and groups of occupants and their interactions with building energy services systems, appliances and facilities. The technical framework consists of four key components:

  1. the drivers behind energy-related occupant behavior, which are biological, societal, environmental, physical, and economical in nature
  2. the needs of the occupants are based on satisfying criteria that are either physical (e.g. thermal, visual and acoustic comfort) or non-physical (e.g. entertainment, privacy, and social reward)
  3. the actions that building occupants perform when their needs are not fulfilled
  4. the systems with which an occupant can interact to satisfy their needs

The technical framework aims to provide a standardized description of a complete set of human energy-related behaviors in the form of an XML schema. For each type of behavior (e.g., occupants opening/closing windows, switching on/off lights etc.) we identify a set of common behaviors based on a literature review, survey data, and our own field study and analysis. Stochastic models are adopted or developed for each type of behavior to enable the evaluation of the impact of human behavior on energy use in buildings, during either the design or operation phase. We will also demonstrate the use of the technical framework in assessing the impact of occupancy behavior on energy saving technologies. The technical framework presented is part of our human behavior research, a 5-year program under the U.S. - China Clean Energy Research Center for Building Energy Efficiency.

10abuilding simulation10aenergy efficiency10aframework10aoccupant behavior10aXML schema1 aTurner, William, J. N.1 aHong, Tianzhen uhttps://simulationresearch.lbl.gov/publications/technical-framework-describe-occupant01503nas a2200181 4500008003900000245009000039210006900129520087000198653003801068653002101106653002701127653002001154100001401174700001201188700001901200700001601219856008601235 2013 d00aBuilding energy modeling programs comparison Research on HVAC systems simulation part0 aBuilding energy modeling programs comparison Research on HVAC sy3 a

Building energy simulation programs are effective tools for the evaluation of building energy saving and optimization of design. The fact that large discrepancies exist in simulated results when different BEMPs are used to model the same building has caused wide concern. Urgent research is needed to identify the main elements that contribute towards the simulation results. This technical report summarizes methodologies, processes, and the main assumptions of three building energy modeling programs (BEMPs) for HVAC calculations: EnergyPlus, DeST, and DOE-2.1E, and test cases are designed to analyze the calculation process in detail. This will help users to get a better understanding of BEMPs and the research methodology of building simulation. This will also help build a foundation for building energy code development and energy labeling programs.

10aBuilding energy modeling programs10acomparison tests10aHVAC system simulation10atheory analysis1 aZhou, Xin1 aYan, Da1 aHong, Tianzhen1 aZhu, Dandan uhttps://simulationresearch.lbl.gov/publications/building-energy-modeling-programs05291nas a2200193 4500008003900000245004400039210004400083260001200127520474700139100001904886700001404905700001504919700001704934700001304951700001304964700001504977700002204992856008305014 2013 d00aBuilding Energy Monitoring and Analysis0 aBuilding Energy Monitoring and Analysis c06/20133 a

U.S. and China are the world's top two economics. Together they consumed one-third of the world's primary energy. It is an unprecedented opportunity and challenge for governments, researchers and industries in both countries to join together to address energy issues and global climate change. Such joint collaboration has huge potential in creating new jobs in energy technologies and services.

Buildings in the US and China consumed about 40% and 25% of the primary energy in both countries in 2010 respectively. Worldwide, the building sector is the largest contributor to the greenhouse gas emission. Better understanding and improving the energy performance of buildings is a critical step towards sustainable development and mitigation of global climate change.

This project aimed to develop a standard methodology for building energy data definition, collection, presentation, and analysis; apply the developed methods to a standardized energy monitoring platform, including hardware and software, to collect and analyze building energy use data; and compile offline statistical data and online real-time data in both countries for fully understanding the current status of building energy use. This helps decode the driving forces behind the discrepancy of building energy use between the two countries; identify gaps and deficiencies of current building energy monitoring, data collection, and analysis; and create knowledge and tools to collect and analyze good building energy data to provide valuable and actionable information for key stakeholders.

Key research findings were summarized as follows:

The research outputs from the project can help better understand energy performance of buildings, improve building operations to reduce energy waste and increase efficiency, identify retrofit opportunities for existing buildings, and provide guideline to improve the design of new buildings. The standardized energy monitoring and analysis platform as well as the collected real building data can also be used for other CERC projects that need building energy measurements, and be further linked to building energy benchmarking and rating/labeling systems.

1 aHong, Tianzhen1 aFeng, Wei1 aLu, Alison1 aXia, Jianjun1 aYang, Le1 aShen, Qi1 aIm, Piljae1 aBhandari, Mahabir uhttps://simulationresearch.lbl.gov/publications/building-energy-monitoring-and00439nas a2200121 4500008003900000245006600039210006500105260001200170100001400182700001900196700001200215856009000227 2013 d00aComparison of Building Energy Modeling Programs: HVAC Systems0 aComparison of Building Energy Modeling Programs HVAC Systems c08/20131 aZhou, Xin1 aHong, Tianzhen1 aYan, Da uhttps://simulationresearch.lbl.gov/publications/comparison-building-energy-modeling-002003nas a2200217 4500008003900000245008000039210006900119520131400188653002401502653001501526653001301541653001301554653002201567653002101589653002501610100001401635700001201649700001701661700001901678856008801697 2013 d00aData Analysis and Modeling of Lighting Energy Use in Large Office Buildings0 aData Analysis and Modeling of Lighting Energy Use in Large Offic3 a

Lighting consumes about 20 to 40% of total electricity use in large office buildings in the U.S. and China. In order to develop better lighting simulation models it is crucial to understand the characteristics of lighting energy use. This paper analyzes the main characteristics of lighting energy use over various time scales, based on the statistical analysis of measured lighting energy use of 17 large office buildings in Beijing and Hong Kong. It was found that the daily 24-hour variations of lighting energy use were mainly driven by the schedule of the building occupants. Outdoor illumination levels have little impact on lighting energy use in large office buildings due to the lack of automatic daylighting controls and relatively small perimeter areas. A stochastic lighting energy use model was developed based on different occupant activities during six time periods throughout a day, and the annual distribution of lighting power across those periods. The model was verified using measured lighting energy use of one selected building. This study demonstrates how statistical analysis and stochastic modeling can be applied to lighting energy use. The developed lighting model can be adopted by building energy modeling programs to improve the simulation accuracy of lighting energy use.

10abuilding simulation10aenergy use10alighting10amodeling10aoccupant behavior10aoffice buildings10aPoisson distribution1 aZhou, Xin1 aYan, Da1 aRen, Xiaoxin1 aHong, Tianzhen uhttps://simulationresearch.lbl.gov/publications/data-analysis-and-modeling-lighting02500nas a2200253 4500008003900000022003900039245010600078210006900184260003900253300001200292490000600304520167200310653003701982653002702019653001502046653000902061653001302070653001502083100001602098700001902114700001202133700001702145856008402162 2013 d aPrint: 1996-3599; Online 1996-874400aA Detailed Loads Comparison of Three Building Energy Modeling Programs: EnergyPlus, DeST and DOE-2.1E0 aDetailed Loads Comparison of Three Building Energy Modeling Prog bTsinghua University Pressc09/2013 a323-3350 v63 a

Building energy simulation is widely used to help design energy efficient building envelopes and HVAC systems, develop and demonstrate compliance of building energy codes, and implement building energy rating programs. However, large discrepancies exist between simulation results from different building energy modeling programs (BEMPs). This leads many users and stakeholders to lack confidence in the results from BEMPs and building simulation methods. This paper compared the building thermal load modeling capabilities and simulation results of three BEMPs: EnergyPlus, DeST and DOE-2.1E. Test cases, based upon the ASHRAE Standard 140 tests, were designed to isolate and evaluate the key influencing factors responsible for the discrepancies in results between EnergyPlus and DeST. This included the load algorithms and some of the default input parameters. It was concluded that there is little difference between the results from EnergyPlus and DeST if the input values are the same or equivalent despite there being many discrepancies between the heat balance algorithms. DOE-2.1E can produce large errors for cases when adjacent zones have very different conditions, or if a zone is conditioned part-time while adjacent zones are unconditioned. This was due to the lack of a strict zonal heat balance routine in DOE-2.1E, and the steady state handling of heat flow through interior walls and partitions. This comparison study did not produce another test suite, but rather a methodology to design tests that can be used to identify and isolate key influencing factors that drive the building thermal loads, and a process with which to carry them out.

10abuilding energy modeling program10abuilding thermal loads10acomparison10adest10aDOE-2.1E10aenergyplus1 aZhu, Dandan1 aHong, Tianzhen1 aYan, Da1 aWang, Chuang uhttps://simulationresearch.lbl.gov/publications/detailed-loads-comparison-three03302nas a2200229 4500008003900000245012400039210006900163260005100232300001200283490000800295520248200303653003102785653002402816653001502840653002802855653003202883653001702915100001902932700002002951700001802971856008302989 2013 d00aA Fresh Look at Weather Impact on Peak Electricity Demand and Energy Use of Buildings Using 30-Year Actual Weather Data0 aFresh Look at Weather Impact on Peak Electricity Demand and Ener bLawrence Berkeley National Laboratoryc11/2013 a333-3500 v1113 a

Buildings consume more than one third of the world’s total primary energy. Weather plays a unique and significant role as it directly affects the thermal loads and thus energy performance of buildings. The traditional simulated energy performance using Typical Meteorological Year (TMY) weather data represents the building performance for a typical year, but not necessarily the average or typical long-term performance as buildings with different energy systems and designs respond differently to weather changes. Furthermore, the single-year TMY simulations do not provide a range of results that capture yearly variations due to changing weather, which is important for building energy management, and for performing risk assessments of energy efficiency investments. This paper employs large-scale building simulation (a total of 3162 runs) to study the weather impact on peak electricity demand and energy use with the 30-year (1980–2009) Actual Meteorological Year (AMY) weather data for three types of office buildings at two design efficiency levels, across all 17 ASHRAE climate zones. The simulated results using the AMY data are compared to those from the TMY3 data to determine and analyze the differences. Besides further demonstration, as done by other studies, that actual weather has a significant impact on both the peak electricity demand and energy use of buildings, the main findings from the current study include: (1) annual weather variation has a greater impact on the peak electricity demand than it does on energy use in buildings; (2) the simulated energy use using the TMY3 weather data is not necessarily representative of the average energy use over a long period, and the TMY3 results can be significantly higher or lower than those from the AMY data; (3) the weather impact is greater for buildings in colder climates than warmer climates; (4) the weather impact on the medium-sized office building was the greatest, followed by the large office and then the small office; and (5) simulated energy savings and peak demand reduction by energy conservation measures using the TMY3 weather data can be significantly underestimated or overestimated. It is crucial to run multi-decade simulations with AMY weather data to fully assess the impact of weather on the long-term performance of buildings, and to evaluate the energy savings potential of energy conservation measures for new and existing buildings from a life cycle perspective.

10aActual meteorological year10abuilding simulation10aenergy use10aPeak electricity demand10aTypical meteorological year10aweather data1 aHong, Tianzhen1 aChang, Wen-Kuei1 aLin, Hung-Wen uhttps://simulationresearch.lbl.gov/publications/fresh-look-weather-impact-peak01616nas a2200133 4500008003900000245006700039210006500106260003000171520113400201100003101335700002001366700001601386856008001402 2013 d00aFunctional Mock-Up Unit Import in EnergyPlus For Co-Simulation0 aFunctional MockUp Unit Import in EnergyPlus For CoSimulation aChambery, Francec08/20133 a

This paper describes how to use the recently implemented Functional Mock-up Unit (FMU) for co-simulation import interface in EnergyPlus to link EnergyPlus with simulation tools packaged as FMUs. The interface complies with the Functional Mock-up Interface (FMI) for co-simulation standard version 1.0, which is an open standard designed to enable links between different simulation tools that are packaged as FMUs. This article starts with an introduction of the FMI and FMU concepts. We then discuss the implementation of the FMU import interface in EnergyPlus. After that, we present two use cases. The first use case is to model a HVAC system in Modelica, export it as an FMU, and link it to a room model in EnergyPlus. The second use case is an extension of the first case where a shading controller is modeled in Modelica, exported as an FMU, and used in the EnergyPlus room model to control the shading device of one of its windows. In both cases, the FMUs are imported into EnergyPlus which models the building envelope and manages the data-exchange between the envelope and the systems in the FMUs during run-time.

1 aNouidui, Thierry, Stephane1 aWetter, Michael1 aZuo, Wangda uhttps://simulationresearch.lbl.gov/publications/functional-mock-unit-import02408nas a2200229 4500008003900000022001400039245011700053210006900170260001200239300001200251490000600263520165000269653002401919653002001943653002201963653002201985653002102007653002502028100002002053700001902073856008602092 2013 d a1996-874400aStatistical Analysis and Modeling of Occupancy Patterns in Open-Plan Offices using Measured Lighting-Switch Data0 aStatistical Analysis and Modeling of Occupancy Patterns in OpenP c03/2013 a23–320 v63 a

Occupancy profile is one of the driving factors behind discrepancies between the measured and simulated energy consumption of buildings. The frequencies of occupants leaving their offices and the corresponding durations of absences have significant impact on energy use and the operational controls of buildings. This study used statistical methods to analyze the occupancy status, based on measured lighting-switch data in five-minute intervals, for a total of 200 open-plan (cubicle) offices. Five typical occupancy patterns were identified based on the average daily 24-hour profiles of the presence of occupants in their cubicles. These statistical patterns were represented by a one-square curve, a one-valley curve, a two-valley curve, a variable curve, and a flat curve. The key parameters that define the occupancy model are the average occupancy profile together with probability distributions of absence duration, and the number of times an occupant is absent from the cubicle. The statistical results also reveal that the number of absence occurrences decreases as total daily presence hours decrease, and the duration of absence from the cubicle decreases as the frequency of absence increases. The developed occupancy model captures the stochastic nature of occupants moving in and out of cubicles, and can be used to generate a more realistic occupancy schedule. This is crucial for improving the evaluation of the energy saving potential of occupancy based technologies and controls using building simulations. Finally, to demonstrate the use of the occupancy model, weekday occupant schedules were generated and discussed.

10abuilding simulation10aoccupancy model10aoccupancy pattern10aoccupant schedule10aoffice buildings10astatistical analysis1 aChang, Wen-Kuei1 aHong, Tianzhen uhttps://simulationresearch.lbl.gov/publications/statistical-analysis-and-modeling00650nas a2200181 4500008003900000245010300039210006900142260001200211100002100223700001800244700001500262700002100277700002100298700002100319700002100340700002300361856008400384 2013 d00aTransforming BIM to BEM: Generation of Building Geometry for the NASA Ames Sustainability Base BIM0 aTransforming BIM to BEM Generation of Building Geometry for the  c01/20131 aO'Donnell, James1 aMaile, Tobias1 aRose, Cody1 aMrazovic, Natasa1 aMorrissey, Elmer1 aRegnier, Cynthia1 aParrish, Kristen1 aBazjanac, Vladimir uhttps://simulationresearch.lbl.gov/publications/transforming-bim-bem-generation00472nas a2200109 4500008003900000245011000039210006900149100001900218700002700237700001400264856008400278 2013 d00aThe Two-Day CERC-BEE Forum on Building Integrated Design and Occupant Behavior: Presentations and Summary0 aTwoDay CERCBEE Forum on Building Integrated Design and Occupant 1 aHong, Tianzhen1 aTurner, William, J. N.1 aLi, Cheng uhttps://simulationresearch.lbl.gov/publications/two-day-cerc-bee-forum-building01318nas a2200193 4500008003900000245006300039210006300102260002500165520071500190100002400905700001500929700001900944700002200963700002900985700002601014700002001040700001801060856004601078 2012 d00aApplication of a stochastic window use model in EnergyPlus0 aApplication of a stochastic window use model in EnergyPlus aMadison, WIc08/20123 a

Natural ventilation, used appropriately, has the potential to provide both significant HVAC energy savings, and improvements in occupant satisfaction.

Central to the development of natural ventilation models is the need to accurately represent the behavior of building occupants. The work covered in this paper describes a method of implementing a stochastic window model in EnergyPlus. Simulated window use data from three stochastic window opening models was then compared to measured window opening behavior, collected in a naturally-ventilated office in California. Recommendations regarding the selection of stochastic window use models, and their implementation in EnergyPlus, are presented.

1 aDutton, Spencer, M.1 aZhang, Hui1 aZhai, Yongchao1 aArens, Edward, A.1 aSmires, Youness, Bennani1 aBrunswick, Samuel, L.1 aKonis, Kyle, S.1 aHaves, Philip uhttps://escholarship.org/uc/item/2gm7r78300784nas a2200241 4500008004100000245006200041210006200103260003200165653004300197653003700240653002400277653001500301653000900316653001000325653001500335653003000350653000900380100001600389700001900405700001200424700001700436856008900453 2012 eng d00aComparative research in building energy modeling programs0 aComparative research in building energy modeling programs aChina (in Chinese)c06/201110aadvanced building software: energyplus10abuilding energy modeling program10abuilding simulation10acomparison10adest10adoe-210aenergyplus10asimulation research group10atest1 aZhu, Dandan1 aHong, Tianzhen1 aYan, Da1 aWang, Chuang uhttps://simulationresearch.lbl.gov/publications/comparative-research-building-energy00448nas a2200121 4500008003900000245006800039210006700107260001200174100001600186700001900202700001700221856008800238 2012 d00aComparison of Building Energy Modeling Programs: Building Loads0 aComparison of Building Energy Modeling Programs Building Loads c06/20121 aZhu, Dandan1 aHong, Tianzhen1 aWang, Chuang uhttps://simulationresearch.lbl.gov/publications/comparison-building-energy-modeling01519nas a2200121 4500008003900000245011500039210006900154520103400223100001701257700001801274700002001292856008501312 2012 d00aThe Energy Saving Potential of Membrane-Based Enthalpy Recovery in Vav Systems for Commercial Office Buildings0 aEnergy Saving Potential of MembraneBased Enthalpy Recovery in Va3 a

A design tool to evaluate the heat and mass transfer effectiveness and pressure drop of a membrane-based enthalpy exchanger was developed and then used to optimize the configuration of an enthalpy exchanger for minimum pressure drop and maximum heat recovery effectiveness. Simulation was used in a parametric study to investigate the energy saving potential of the enthalpy recovery system. The case without energy recovery and air side economizer was used as a baseline. Two comparison cases for the implementation of enthalpy recovery with and without air side economizer were simulated in EnergyPlus. A case using a desiccant wheel for energy recovery was also investigated for comparison purposes. The simulation results show significant energy saving benefits from applying a low pressure drop, high effectiveness enthalpy exchanger in two US cities representing a range of humid climates. The sensitivity of the energy savings potential to pressure drop and heat and mass transfer effectivenesses is also presented.

1 aWang, Liping1 aHaves, Philip1 aBreshears, John uhttps://simulationresearch.lbl.gov/publications/energy-saving-potential-membrane00520nas a2200121 4500008004100000245011400041210006900155260003200224100001700256700001800273700002000291856008700311 2012 eng d00aThe Energy Saving Potential of Membrane-Based Enthalpy Recovery in VAV System for Commercial Office Buildings0 aEnergy Saving Potential of MembraneBased Enthalpy Recovery in VA aMadison, Wisconsinc08/20121 aWang, Liping1 aHaves, Philip1 aBreshears, John uhttps://simulationresearch.lbl.gov/publications/energy-saving-potential-membrane-001987nas a2200241 4500008004100000022001400041245008500055210006900140260001200209300001200221490000700233520120100240653003901441653002501480653002001505653001501525653003401540100001801574700002001592700002601612700001801638856008901656 2012 eng d a0360-132300aA framework for simulation-based real-time whole building performance assessment0 aframework for simulationbased realtime whole building performanc c08/2012 a100-1080 v543 a

Most commercial buildings do not perform as well in practice as intended by the design and their performances often deteriorate over time. Reasons include faulty construction, malfunctioning equipment, incorrectly configured control systems and inappropriate operating procedures. One approach to addressing this problems is to compare the predictions of an energy simulation model of the building to the measured performance and analyze significant differences to infer the presence and location of faults. This paper presents a framework that allows a comparison of building actual performance and expected performance in real time. The realization of the framework utilized the EnergyPlus, the Building Controls Virtual Test Bed (BCVTB) and the Energy Management and Control System (EMCS) was developed. An EnergyPlus model that represents expected performance of a building runs in real time and reports the predicted building performance at each time step. The BCVTB is used as the software platform to acquire relevant inputs from the EMCS through a BACnet interface and send them to the EnergyPlus and to a database for archiving. A proof-of-concept demonstration is also presented.

10abuilding controls virtual test bed10abuilding performance10aenergy modeling10aenergyplus10areal-time building simulation1 aPang, Xiufeng1 aWetter, Michael1 aBhattacharya, Prajesh1 aHaves, Philip uhttps://simulationresearch.lbl.gov/publications/framework-simulation-based-real-time01431nas a2200133 4500008003900000245005600039210005300095260001200148520099100160100001701151700001801168700002101186856009001207 2012 d00aAn Improved Simple Chilled Water Cooling Coil Model0 aImproved Simple Chilled Water Cooling Coil Model c08/20123 a

The accurate prediction of cooling and dehumidification coil performance is important in model-based fault detection and in the prediction of HVAC system energy consumption for support of both design and operations. It is frequently desirable to use a simple cooling coil model that does not require detailed specification of coil geometry and material properties. The approach adopted is to match the overall UA of the coil to the rating conditions and to estimate the air-side and water-side components of the UA using correlations developed by Holmes (1982). This approach requires some geometrical information about the coil and the paper investigates the sensitivity of the overall performance prediction to uncertainties in this information, including assuming a fixed ratio of air-side to water-side UA at the rating condition. Finally, simulation results from different coil models are compared, and experimental data are used to validate the improved cooling coil model.

1 aWang, Liping1 aHaves, Philip1 aBuhl, Walter, F. uhttps://simulationresearch.lbl.gov/publications/improved-simple-chilled-water-cooling02242nas a2200181 4500008004100000245007300041210006900114260003300183520159100216653003201807653002401839653002401863653003001887653001801917100001801935700001901953856008801972 2012 eng d00aAn In-Depth Analysis of Space Heating Energy Use in Office Buildings0 aInDepth Analysis of Space Heating Energy Use in Office Buildings aAsilomar, CAbACEEEc08/20123 a

Space heating represents the largest end use in the U.S. buildings and consumes more than 7 trillion Joules of site energy annually [USDOE]. Analyzing building space heating performance and identifying methods for saving energy are quite important. Hence, it is crucial to identify and evaluate key driving factors to space heating energy use to support the design and operation of low energy buildings.

In this study, the prototypical small and large-size office buildings of the USDOE commercial reference buildings, which comply with ASHRAE Standard 90.1-2004, are selected. Key design and operation factors were identified to evaluate their degrees of impact for space heating energy use. Simulation results demonstrate that some of the selected building design and operation parameters have more significant impacts on space heating energy use than others, on the other hand, good operation practice can save more space heating energy than raising design efficiency levels of an office building. Influence of weather data used in simulations on space heating energy is found to be significant. The simulated space heating energy use is further benchmarked against those from similar office buildings in two U.S. commercial buildings databases to better understand the discrepancies.

Simulated results from this study and space heating energy use collected from building databases can both vary in two potentially well overlapped wide ranges depending on details of building design and operation, not necessarily that simulation always under-predicts the reality.

10abuilding energy performance10abuilding simulation10asimulation research10asimulation research group10aspace heating1 aLin, Hung-Wen1 aHong, Tianzhen uhttps://simulationresearch.lbl.gov/publications/depth-analysis-space-heating-energy01650nas a2200157 4500008003900000245005400039210005400093260003000147520113000177100001801307700002201325700002101347700001801368700002201386856008401408 2012 d00aMapping Hvac Systems for Simulation In EnergyPlus0 aMapping Hvac Systems for Simulation In EnergyPlus aMadison, WI, USAc07/20123 a

For building energy simulation tools to be accessible to designers, tool interfaces should present a conventional view of HVAC systems to the user, and then map this view to the internal data model used in the tool. The paper outlines a process that enables design engineers to create HVAC system representations using industry standard terminology and system, icon and typological representations and convert that unified representation into the format required by the whole building energy simulation tool EnergyPlus. This paper describes each stage of the conversion process, which involves transformations between the following representations: 1) engineer's representation, 2) component connectivity representation, 3) representation in the internal data model used in the Simergy graphical user interface for EnergyPlus, and 4) EnergyPlus representation.

The paper also describes mappings between these representations and the development of a rule-based validation and assignment framework required to implement that mapping. In addition, the paper describes the implementation of this process in Simergy.

1 aMaile, Tobias1 aBasarkar, Mangesh1 aO'Donnell, James1 aHaves, Philip1 aSettlemyre, Kevin uhttps://simulationresearch.lbl.gov/publications/mapping-hvac-systems-simulation02060nas a2200277 4500008003900000245009300039210006900132260001200201520117000213653001701383653001801400653001501418653003601433653002301469653001501492100001901507700002301526700001801549700003101567700001701598700001701615700002501632700001701657700002001674856008801694 2012 d00aMonitoring-based HVAC Commissioning of an Existing Office Building for Energy Efficiency0 aMonitoringbased HVAC Commissioning of an Existing Office Buildin c10/20123 a

The performance of Heating, Ventilation and Air Conditioning (HVAC) systems may fail to satisfy design expectations due to improper equipment installation, equipment degradation, sensor failures, or incorrect control sequences. Commissioning identifies and implements cost-effective operational and maintenance measures in buildings to bring them up to the design intent or optimum operation. An existing office building is used as a case study to demonstrate the process of commissioning. Building energy benchmarking tools are applied to evaluate the energy performance for screening opportunities at the whole building level. A large natural gas saving potential was indicated by the building benchmarking results. Faulty operations in the HVAC systems, such as improper operations of air-side economizers, simultaneous heating and cooling, and ineffective optimal start, were identified through trend data analyses and functional testing. The energy saving potential for each commissioning measure is quantified with a calibrated building simulation model. An actual energy saving of 10% was realized after the implementations of cost-effective measures.

10abenchmarking10acommissioning10aenergyplus10afault detection and diagnostics10afunctional testing10atrend data1 aEarni, Shankar1 aWoodworth, Spencer1 aPang, Xiufeng1 aHernandez-Maldonado, Jorge1 aYin, Rongxin1 aWang, Liping1 aGreenberg, Steve, E.1 aFiegel, John1 aRubalcava, Alma uhttps://simulationresearch.lbl.gov/publications/monitoring-based-hvac-commissioning00430nas a2200133 4500008004100000245005000041210005000091300001200141490000600153100001600159700001700175700001800192856008600210 2012 eng d00aReduction of numerical viscosity in FFD model0 aReduction of numerical viscosity in FFD model a234-2470 v61 aZuo, Wangda1 aJin, Mingang1 aChen, Qingyan uhttps://simulationresearch.lbl.gov/publications/reduction-numerical-viscosity-ffd02363nas a2200241 4500008004100000245007600041210006900117260002600186520159800212653002401810653001401834653001001848653002401858653003101882653001801913653003001931100002101961700001401982700001301996700001902009700001402028856007902042 2012 eng d00aA Retrofit Tool for Improving Energy Efficiency of Commercial Buildings0 aRetrofit Tool for Improving Energy Efficiency of Commercial Buil aAsilomar, CAc08/20123 a

Existing buildings will dominate energy use in commercial buildings in the United States for three decades or longer and even in China for the about two decades. Retrofitting these buildings to improve energy efficiency and reduce energy use is thus critical to achieving the target of reducing energy use in the buildings sector. However there are few evaluation tools that can quickly identify and evaluate energy savings and cost effectiveness of energy conservation measures (ECMs) for retrofits, especially for buildings in China. This paper discusses methods used to develop such a tool and demonstrates an application of the tool for a retrofit analysis. The tool builds on a building performance database with pre-calculated energy consumption of ECMs for selected commercial prototype buildings using the EnergyPlus program. The tool allows users to evaluate individual ECMs or a package of ECMs. It covers building envelope, lighting and daylighting, HVAC, plug loads, service hot water, and renewable energy. The prototype building can be customized to represent an actual building with some limitations. Energy consumption from utility bills can be entered into the tool to compare and calibrate the energy use of the prototype building. The tool currently can evaluate energy savings and payback of ECMs for shopping malls in China. We have used the tool to assess energy and cost savings for retrofit of the prototype shopping mall in Shanghai. Future work on the tool will simplify its use and expand it to cover other commercial building types and other countries. 

10abuilding simulation10abuildings10aChina10acommercial building10aenergy efficiency measures10aretrofit tool10asimulation research group1 aLevine, Mark, D.1 aFeng, Wei1 aKe, Jing1 aHong, Tianzhen1 aZhou, Nan uhttp://aceee.org/files/proceedings/2012/data/papers/0193-000098.pdf#page=102446nas a2200277 4500008004100000245004600041210004600087260003100133520169300164653001401857653001101871653002201882653001101904653001001915653001501925653002101940653001401961100001801975700001901993700001302012700001502025700001902040700001802059700001802077856007302095 2012 eng d00aSustainable Campus with PEV and Microgrid0 aSustainable Campus with PEV and Microgrid aPacific Grove, CAc08/20193 a

Market penetration of electric vehicles (EVs) is gaining momentum, as is the move
towards increasingly distributed, clean and renewable electricity sources. EV charging shifts a
significant portion of transportation energy use onto building electricity meters. Hence,
integration strategies for energy-efficiency in buildings and transport sectors are of increasing
importance. This paper focuses on a portion of that integration: the analysis of an optimal
interaction of EVs with a building-serving transformer, and coupling it to a microgrid that
includes PV, a fuel cell and a natural gas micro-turbine. The test-case is the Nanyang
Technological University (NTU), Singapore campus. The system under study is the Laboratory
of Clean Energy Research (LaCER) Lab that houses the award winning Microgrid Energy
Management System (MG-EMS) project. The paper analyses three different case scenarios to
estimate the number of EVs that can be supported by the building transformer serving LaCER.
An approximation of the actual load data collected for the building into different time intervals is
performed for a transformer loss of life (LOL) calculation. The additional EV loads that can be
supported by the transformer with and without the microgrid are analyzed. The numbers of
possible EVs that can be charged at any given time under the three scenarios are also determined.
The possibility of using EV fleet at NTU campus to achieve demand response capability and
intermittent PV output leveling through vehicle to grid (V2G) technology and building energy
management systems is also explored.

10abuildings10acampus10aelectric vehicles10aenergy10aloads10amicrogrids10arenewable energy10atransport1 aKumar, Nandha1 aSivaneasan, B.1 aSo, P.L.1 aGooi, H.B.1 aJadhav, Nilesh1 aSingh, Reshma1 aMarnay, Chris uhttps://aceee.org/files/proceedings/2012/data/papers/0193-000363.pdf00703nas a2200205 4500008003900000022001300039245012000052210006900172260001200241300001400253490000700267653002400274653001500298653002500313653001800338100001700356700002100373700001800394856008500412 2012 d a0378778800aUncertainties in energy consumption introduced by building operations and weather for a medium-size office building0 aUncertainties in energy consumption introduced by building opera c10/2012 a152 - 1580 v5310aBuilding Operations10aenergyplus10aMonte Carlo Analysis10aUncertainties1 aWang, Liping1 aMathew, Paul, A.1 aPang, Xiufeng uhttps://simulationresearch.lbl.gov/publications/uncertainties-energy-consumption01281nas a2200145 4500008004100000245008300041210006900124260002900193520073500222100003100957700002100988700001601009700002001025856009001045 2012 eng d00aValidation and Application of the Room Model of the Modelica Buildings Library0 aValidation and Application of the Room Model of the Modelica Bui aMunich, Germanyc09/20123 a

The Modelica Buildings library contains a package with a model for a thermal zone that computes heat transfer through the building envelope and within a room. It considers various heat transfer phenomena of a room, including conduction, convection, short-wave and long-wave radiation. The first part of this paper describes the physical phenomena considered in the room model. The second part validates the room model by using a standard test suite provided by the American Society of Heating, Refrigerating and Air-Conditioning Engineers (ASHRAE). The third part focuses on an application where the room model is used for simulation-based controls of a window shading device to reduce building energy consumption.

1 aNouidui, Thierry, Stephane1 aPhalak, Kaustubh1 aZuo, Wangda1 aWetter, Michael uhttps://simulationresearch.lbl.gov/publications/validation-and-application-room-model01198nas a2200133 4500008003900000245006900039210006900108260001200177520072300189100003100912700002000943700001600963856008500979 2012 d00aValidation of the Window Model of the Modelica Buildings Library0 aValidation of the Window Model of the Modelica Buildings Library c07/20123 a

This paper describes the validation of the window model of the free open-source Modelica Buildings library. This paper starts by describing the physical modeling assumptions of the window model. The window model can be used to calculate the thermal and angular properties of glazing systems. It can also be used for steady-state simulation of heat transfer mechanism in glazing systems. We present simulation results obtained by comparing the window model with WINDOW 6 the well established simulation tool for steady-state heat transfer in glazing systems. We also present results obtained by comparing the window model with measurements carried out in a test cell at the Lawrence Berkeley National Laboratory.

1 aNouidui, Thierry, Stephane1 aWetter, Michael1 aZuo, Wangda uhttps://simulationresearch.lbl.gov/publications/validation-window-model-modelica00498nas a2200133 4500008004100000245008700041210006900128260001600197300001400213100001700227700001600244700001800260856008600278 2012 eng d00aValidation of three dimensional fast fluid dynamics for indoor airflow simulations0 aValidation of three dimensional fast fluid dynamics for indoor a aBoulder, CO a1055-10621 aJin, Mingang1 aZuo, Wangda1 aChen, Qingyan uhttps://simulationresearch.lbl.gov/publications/validation-three-dimensional-fast00476nas a2200109 4500008004100000245011200041210006900153260001900222100001600241700002000257856008900277 2011 eng d00aAdvanced simulations of building energy and control systems with an example of chilled water plant modeling0 aAdvanced simulations of building energy and control systems with aNanjing, China1 aZuo, Wangda1 aWetter, Michael uhttps://simulationresearch.lbl.gov/publications/advanced-simulations-building-energy00620nas a2200169 4500008004100000245008700041210006900128260003100197100002300228700001800251700001500269700002100284700002100305700002100326700002000347856008300367 2011 eng d00aAn Assessment of the use of Building Energy Performance Simulation in Early Design0 aAssessment of the use of Building Energy Performance Simulation  aSydney, Australiac11/20111 aBazjanac, Vladimir1 aMaile, Tobias1 aRose, Cody1 aO'Donnell, James1 aMrazovic, Natasa1 aMorrissey, Elmer1 aWelle, Benjamin uhttps://simulationresearch.lbl.gov/publications/assessment-use-building-energy01404nas a2200169 4500008003900000245008200039210006900121260001200190520081400202100001801016700002601034700003101060700002001091700001701111700001801128856008801146 2011 d00aBacNet and Analog/Digital Interfaces of the Building Controls Virtual Testbed0 aBacNet and AnalogDigital Interfaces of the Building Controls Vir c11/20113 a

This paper gives an overview of recent developments in the Building Controls Virtual Test Bed (BCVTB), a framework for co-simulation and hardware-in-the-loop.

First, a general overview of the BCVTB is presented. Second, we describe the BACnet interface, a link which has been implemented to couple BACnet devices to the BCVTB. We present a case study where the interface was used to couple a whole building simulation program to a building control system to assess in real-time the performance of a real building. Third, we present the ADInterfaceMCC, an analog/digital interface that allows a USB-based analog/digital converter to be linked to the BCVTB. In a case study, we show how the link was used to couple the analog/digital converter to a building simulation model for local loop control.

1 aHaves, Philip1 aBhattacharya, Prajesh1 aNouidui, Thierry, Stephane1 aWetter, Michael1 aLi, Zhengwei1 aPang, Xiufeng uhttps://simulationresearch.lbl.gov/publications/bacnet-and-analogdigital-interfaces00629nas a2200169 4500008004100000245008300041210006900124260003100193300001500224100003100239700002000270700001700290700001800307700002600325700001800351856009000369 2011 eng d00aBACnet and Analog/Digital Interfaces of the Building Controls Virtual Test Bed0 aBACnet and AnalogDigital Interfaces of the Building Controls Vir aSydney, Australiac11/2011 ap. 294-3011 aNouidui, Thierry, Stephane1 aWetter, Michael1 aLi, Zhengwei1 aPang, Xiufeng1 aBhattacharya, Prajesh1 aHaves, Philip uhttps://simulationresearch.lbl.gov/publications/bacnet-and-analogdigital-interfaces-001832nas a2200229 4500008004100000245007600041210006900117260001200186300001400198490000700212520112800219653001601347653001601363653001301379653001501392653002001407653003201427100001801459700001801477700002101495856008601516 2011 eng d00aCalibrating whole building energy models: An evidence-based methodology0 aCalibrating whole building energy models An evidencebased method c09/2011 a2356-23640 v433 a

This paper reviews existing case studies and methods for calibrating whole building energy models to measured data. This research describes a systematic, evidence-based methodology for the calibration of these models. Under this methodology, parameter values in the final calibrated model reference the source of information used to make changes to the initial model. Thus, the final model is based solely on evidence. Version control software stores a complete record of the calibration process, and the evidence on which the final model is based. Future users can review the changes made throughout the calibration process along with the supporting evidence. In addition to the evidence-based methodology, this paper also describes a new zoning process that represents the real building more closely than the typical core and four perimeter zone approach. Though the methodology is intended to apply to detailed calibration studies with high resolution measured data, the primary aspects of the methodology (evidence-based approach, version control, and zone-typing) are independent of the available measured data.

10acalibration10aMethodology10aretrofit10asimulation10aVersion control10aWhole building energy model1 aRaferty, Paul1 aKeane, Marcus1 aO'Donnell, James uhttps://simulationresearch.lbl.gov/publications/calibrating-whole-building-energy00666nas a2200229 4500008004100000245004000041210003800081260001800119653002400137653001500161653000900176653002000185653001500205653002400220653003000244653001500274100001600289700001700305700001200322700001900334856008300353 2011 eng d00aA Comparison of DeST and EnergyPlus0 aComparison of DeST and EnergyPlus aBeijingc201110abuilding simulation10acomparison10adest10aenergy modeling10aenergyplus10asimulation research10asimulation research group10atest cases1 aZhu, Dandan1 aWang, Chuang1 aYan, Da1 aHong, Tianzhen uhttps://simulationresearch.lbl.gov/publications/comparison-dest-and-energyplus02106nas a2200169 4500008004100000245010100041210006900142260001200211490000600223520151300229653002401742653001801766653002401784653002201808100002001830856008601850 2011 eng d00aCo-simulation of building energy and control systems with the Building Controls Virtual Test Bed0 aCosimulation of building energy and control systems with the Bui c11/20100 v33 a

This article describes the implementation of the Building Controls Virtual Test Bed (BCVTB). The BCVTB is a software environment that allows connecting different simulation programs to exchange data during the time integration, and that allows conducting hardware in the loop simulation. The software architecture is a modular design based on Ptolemy II, a software environment for design and analysis of heterogeneous systems. Ptolemy II provides a graphical model building environment, synchronizes the exchanged data and visualizes the system evolution during run-time. The BCVTB provides additions to Ptolemy II that allow the run-time coupling of different simulation programs for data exchange, including EnergyPlus, MATLAB, Simulink and the Modelica modelling and simulation environment Dymola. The additions also allow executing system commands, such as a script that executes a Radiance simulation. In this article, the software architecture is presented and the mathematical model used to implement the co-simulation is discussed. The simulation program interface that the BCVTB provides is explained. The article concludes by presenting applications in which different state of the art simulation programs are linked for run-time data exchange. This link allows the use of the simulation program that is best suited for the particular problem to model building heat transfer, HVAC system dynamics and control algorithms, and to compute a solution to the coupled problem using co-simulation.

10abuilding simulation10aco-simulation10aintegrated analysis10amodular modelling1 aWetter, Michael uhttps://simulationresearch.lbl.gov/publications/co-simulation-building-energy-and00551nas a2200145 4500008004100000245008000041210006900121260002900190100002300219700001800242700002100260700001500281700002100296856008800317 2011 eng d00aData Enviroments and Processing in Sem-Automated Simulation with EnergyPlus0 aData Enviroments and Processing in SemAutomated Simulation with  aSophia Antipolis, France1 aBazjanac, Vladimir1 aMaile, Tobias1 aO'Donnell, James1 aRose, Cody1 aMrazovic, Natasa uhttps://simulationresearch.lbl.gov/publications/data-enviroments-and-processing-sem00610nas a2200157 4500008004100000245009600041210006900137260003100206100001700237700001800254700002500272700002200297700002100319700002200340856009000362 2011 eng d00aDevelopment of a user interface for the EnergyPlus whole building energy simulation program0 aDevelopment of a user interface for the EnergyPlus whole buildin aSydney, Australiac11/20111 aSee, Richard1 aHaves, Philip1 aSreekanathan, Pramod1 aBasarkar, Mangesh1 aO'Donnell, James1 aSettlemyre, Kevin uhttps://simulationresearch.lbl.gov/publications/development-user-interface-energyplus00768nas a2200241 4500008004100000245005700041210005700098260002300155653004300178653002400221653001500245653001100260653001200271653001300283653001800296653003000314100002200344700001800366700001800384700001700402700001900419856008800438 2011 eng d00aModeling and simulation of HVAC faults in EnergyPlus0 aModeling and simulation of HVAC faults in EnergyPlus aAustraliac11/201110aadvanced building software: energyplus10abuilding simulation10aenergyplus10afaults10afouling10amodeling10asensor offset10asimulation research group1 aBasarkar, Mangesh1 aHaves, Philip1 aPang, Xiufeng1 aWang, Liping1 aHong, Tianzhen uhttps://simulationresearch.lbl.gov/publications/modeling-and-simulation-hvac-faults00466nas a2200133 4500008003900000245005800039210005800097260001200155100002200167700001800189700001700207700001900224856008900243 2011 d00aModeling and simulation of HVAC Results in EnergyPlus0 aModeling and simulation of HVAC Results in EnergyPlus c11/20111 aBasarkar, Mangesh1 aPang, Xiufeng1 aWang, Liping1 aHong, Tianzhen uhttps://simulationresearch.lbl.gov/publications/modeling-and-simulation-hvac-results00521nas a2200133 4500008004100000245007500041210006900116260003100185300001400216100002000230700001600250700003100266856009000297 2011 eng d00aModeling of Heat Transfer in Rooms in the Modelica "Buildings" Library0 aModeling of Heat Transfer in Rooms in the Modelica Buildings Lib aSydney, Australiac11/2011 a1096-11031 aWetter, Michael1 aZuo, Wangda1 aNouidui, Thierry, Stephane uhttps://simulationresearch.lbl.gov/publications/modeling-heat-transfer-rooms-modelica00559nas a2200157 4500008004100000245009200041210006900133260001200202300001400214490000700228100002100235700001800256700001800274700002100292856008800313 2011 eng d00aMulti-Criteria Optimisation using Past, Real Time and Predictive Performance Benchmarks0 aMultiCriteria Optimisation using Past Real Time and Predictive P c04/2011 a1258-12650 v191 aTorrens, Ignacio1 aKeane, Marcus1 aCosta, Andrea1 aO'Donnell, James uhttps://simulationresearch.lbl.gov/publications/multi-criteria-optimisation-using-000504nas a2200121 4500008004100000245012700041210006900168300001200237490000800249100001800257700001900275856008800294 2011 eng d00aPrevention of Compressor Short Cycling in Direct-Expansion (DX) Rooftop Units, Part 1: Theoretical Analysis and Simulation0 aPrevention of Compressor Short Cycling in DirectExpansion DX Roo a666-6760 v1171 aPang, Xiufeng1 aLiu, Mingsheng uhttps://simulationresearch.lbl.gov/publications/prevention-compressor-short-cycling00492nas a2200121 4500008004100000245011300041210006900154300001200223490000800235100001800243700001900261856009000280 2011 eng d00aPrevention of Compressor Short Cycling in Direct-Expansion (DX) Rooftop Units— Part 2: Field Investigation0 aPrevention of Compressor Short Cycling in DirectExpansion DX Roo a677-6850 v1171 aPang, Xiufeng1 aLiu, Mingsheng uhttps://simulationresearch.lbl.gov/publications/prevention-compressor-short-cycling-001677nas a2200181 4500008004100000245010100041210006900142260003100211300001700242520102700259100001801286700002601304700001901330700001801349700002001367700001901387856008901406 2011 eng d00aReal-time Building Energy Simulation using EnergyPlus and the Building Controls Virtual Test Bed0 aRealtime Building Energy Simulation using EnergyPlus and the Bui aSydney, Australiac11/2011 ap. 2890-28963 a

Most commercial buildings do not perform as well in practice as intended by the design and their performances often deteriorate over time. Reasons include faulty construction, malfunctioning equipment, incorrectly configured control systems and inappropriate operating procedures (Haves et al., 2001, Lee et al., 2007). To address this problem, the paper presents a simulation-based whole building performance monitoring tool that allows a comparison of building actual performance and expected performance in real time. The tool continuously acquires relevant building model input variables from existing Energy Management and Control System (EMCS). It then reports expected energy consumption as simulated of EnergyPlus. The Building Control Virtual Test Bed (BCVTB) is used as the software platform to provide data linkage between the EMCS, an EnergyPlus model, and a database. This paper describes the integrated real-time simulation environment. A proof-of-concept demonstration is also presented in the paper.

1 aPang, Xiufeng1 aBhattacharya, Prajesh1 aO'Neill, Zheng1 aHaves, Philip1 aWetter, Michael1 aBailey, Trevor uhttps://simulationresearch.lbl.gov/publications/real-time-building-energy-simulation01476nas a2200157 4500008004100000245009800041210006900139260002100208520088700229653002801116653001201144100002001156700001601176700003101192856009501223 2011 eng d00aRecent developments of the Modelica Buildings library for building energy and control systems0 aRecent developments of the Modelica Buildings library for buildi aDresden, Germany3 a

At the Modelica 2009 conference, we introduced the Buildings library, a freely available Modelica library for building energy and control systems [16]. This paper reports the updates of the library and presents example applications for a range of heating, ventilation and air conditioning (HVAC) systems. Over the past two years, the library has been further developed. The number of HVAC components models has been doubled and various components have been revised to increase numerical robustness. The paper starts with an overview of the library architecture and a description of the main packages. To demonstrate the features of the Buildings library, applications that include multizone airow simulation as well as supervisory and local loop control of a variable air volume (VAV) system are briey described. The paper closes with a discussion of the current development.

10abuilding energy systems10aheating1 aWetter, Michael1 aZuo, Wangda1 aNouidui, Thierry, Stephane uhttps://www.modelica.org/events/modelica2011/Proceedings/pages/papers/12_1_ID_113_a_fv.pdf02272nas a2200169 4500008004100000245007100041210006900112260001200181520171200193100002101905700001701926700001501943700001801958700002301976700001801999856008502017 2011 eng d00aSimModel: A domain data model for whole building energy simulation0 aSimModel A domain data model for whole building energy simulatio c10/20113 a

Many inadequacies exist within industry-standard data models as used by present-day whole-building energy simulation software. Tools such as EnergyPlus and DOE-2 use custom schema definitions (IDD and BDL respectively) as opposed to standardized schema definitions (defined in XSD, EXPRESS, etc.). Non-standard data modes lead to a requirement for application developers to develop bespoke interfaces. Such tools have proven to be error prone in their implementation – typically resulting in information loss.

This paper presents a Simulation Domain Model (SimModel) - a new interoperable XML-based data model for the building simulation domain. SimModel provides a consistent data model across all aspects of the building simulation process, thus preventing information loss. The model accounts for new simulation tool architectures, existing and future systems, components and features. In addition, it is a multi-representation model that enables integrated geometric and MEP simulation configuration data. The SimModel objects ontology moves away from tool-specific, non-standard nomenclature by implementing an industry-validated terminology aligned with Industry Foundation Classes (IFC).

The first implementation of SimModel supports translations from IDD, Open Studio IDD, gbXML and IFC. In addition, the EnergyPlus Graphic User Interface (GUI) employs SimModel as its internal data model. Ultimately, SimModel will form the basis for a new IFC Model View Definition (MVD) that will enable data exchange from HVAC Design applications to Energy Analysis applications. Extensions to SimModel could easily support other data formats and simulations (e.g. Radiance, COMFEN, etc.).

1 aO'Donnell, James1 aSee, Richard1 aRose, Cody1 aMaile, Tobias1 aBazjanac, Vladimir1 aHaves, Philip uhttps://simulationresearch.lbl.gov/publications/simmodel-domain-data-model-whole01748nas a2200145 4500008003900000245008700039210006900126260003100195520120900226100001801435700002301453700002101476700001801497856008701515 2011 d00aA software tool to compare measured and simulated building energy performance data0 asoftware tool to compare measured and simulated building energy  aSydney, Australiac11/20113 a

Building energy performance is often inadequate when compared to design goals. To link design goals to actual operation one can compare measured with simulated energy performance data. Our previously developed comparison approach is the Energy Performance Comparison Methodology (EPCM), which enables the identification of performance problems based on a comparison of measured and simulated performance data. In context of this method, we developed a software tool that provides graphing and data processing capabilities of the two performance data sets. The software tool called SEE IT (Stanford Energy Efficiency Information Tool) eliminates the need for manual generation of data plots and data reformatting. SEE IT makes the generation of time series, scatter and carpet plots independent of the source of data (measured or simulated) and provides a valuable tool for comparing measurements with simulation results. SEE IT also allows assigning data points on a predefined building object hierarchy and supports different versions of simulated performance data. This paper briefly introduces the EPCM, describes the SEE IT tool and illustrates its use in the context of a building case study.

1 aMaile, Tobias1 aBazjanac, Vladimir1 aO'Donnell, James1 aGarr, Matthew uhttps://simulationresearch.lbl.gov/publications/software-tool-compare-measured-and00550nas a2200133 4500008004100000245011300041210006900154260003100223100001800254700001800272700002100290700001800311856008700329 2011 eng d00aSystematic Development of an Operational BIM Utilising Simulation and Performance Data in Building Operation0 aSystematic Development of an Operational BIM Utilising Simulatio aSydney, Australiac11/20111 aCorry, Edward1 aKeane, Marcus1 aO'Donnell, James1 aCosta, Andrea uhttps://simulationresearch.lbl.gov/publications/systematic-development-operational01525nas a2200169 4500008004100000245011000041210006900151260002700220520091900247653000801166653000801174653002201182653002801204100001601232700001801248856008901266 2011 eng d00aValidation of a Fast-Fluid-Dynamics Model for Predicting Distribution of Particles with Low Stokes Number0 aValidation of a FastFluidDynamics Model for Predicting Distribut aAustin, Texasc06/20113 aTo design a healthy indoor environment, it is important to study airborne particle distribution indoors. As an intermediate model between multizone models and computational fluid dynamics (CFD), a fast fluid dynamics (FFD) model can be used to provide temporal and spatial information of particle dispersion in real time. This study evaluated the accuracy of the FFD for predicting transportation of particles with low Stokes number in a duct and in a room with mixed convection. The evaluation was to compare the numerical results calculated by the FFD with the corresponding experimental data and the results obtained by the CFD. The comparison showed that the FFD could capture major pattern of particle dispersion, which is missed in models with well-mixed assumptions. Although the FFD was less accurate than the CFD partially due to its simplification in numeric schemes, it was 53 times faster than the CFD.10acfd10affd10alow stokes number10aparticle transportation1 aZuo, Wangda1 aChen, Qingyan uhttps://simulationresearch.lbl.gov/publications/validation-fast-fluid-dynamics-model00596nas a2200169 4500008004100000245008000041210006900121260000900190653003200199653001500231653002100246653001500267653001200282100001900294700002700313856008600340 2010 eng d00aAssessment of Energy Impact of Window Technologies for Commercial Buildings0 aAssessment of Energy Impact of Window Technologies for Commercia c201010abuilding energy performance10aenergyplus10ashading controls10asimulation10awindows1 aHong, Tianzhen1 aSelkowitz, Stephen, E. uhttps://simulationresearch.lbl.gov/publications/assessment-energy-impact-window-003910nas a2200229 4500008004100000245013300041210006900174260006100243300001200304490000600316520299300322653002403315653004003339653007503379653003403454653001903488653003403507653001003541100001903551700002203570856008803592 2010 eng d00aAssessment of Energy Savings Potential from the Use of Demand Control Ventilation Systems in General Office Spaces in California0 aAssessment of Energy Savings Potential from the Use of Demand Co aBerkeleybLawrence Berkeley National Laboratoryc06/2010 a117-1240 v33 a

Demand controlled ventilation (DCV) was evaluated for general office spaces in California. A medium size office building meeting the prescriptive requirements of the 2008 California building energy efficiency standards (CEC 2008) was assumed in the building energy simulations performed with the EnergyPlus program to calculate the DCV energy savings potential in five typical California climates. Three design occupancy densities and two minimum ventilation rates were used as model inputs to cover a broader range of design variations. The assumed values of minimum ventilation rates in offices without DCV, based on two different measurement methods, were 81 and 28 cfm per occupant. These rates are based on the co‐author's unpublished analyses of data from EPA's survey of 100 U.S. office buildings. These minimum ventilation rates exceed the 15 to 20 cfm per person required in most ventilation standards for offices. The cost effectiveness of applying DCV in general office spaces was estimated via a life cycle cost analyses that considered system costs and energy cost reductions.

The results of the energy modeling indicate that the energy savings potential of DCV is largest in the desert area of California (climate zone 14), followed by Mountains (climate zone 16), Central Valley (climate zone 12), North Coast (climate zone 3), and South Coast (climate zone 6).

The results of the life cycle cost analysis show DCV is cost effective for office spaces if the typical minimum ventilation rates without DCV is 81 cfm per person, except at the low design occupancy of 10 people per 1000 ft2 in climate zones 3 and 6. At the low design occupancy of 10 people per 1000 ft2, the greatest DCV life cycle cost savings is a net present value (NPV) of $0.52/ft2 in climate zone 14, followed by $0.32/ft2 in climate zone 16 and $0.19/ft2 in climate zone 12. At the medium design occupancy of 15 people per 1000 ft2, the DCV savings are higher with a NPV $0.93/ft2 in climate zone 14, followed by $0.55/ft2 in climate zone 16, $0.46/ft2 in climate zone 12, $0.30/ft2 in climate zone 3, $0.16/ft2 in climate zone 3. At the high design occupancy of 20 people per 1000 ft2, the DCV savings are even higher with a NPV $1.37/ft2 in climate zone 14, followed by $0.86/ft2 in climate zone 16, $0.84/ft2 in climate zone 3, $0.82/ft2 in climate zone 12, and $0.65/ft2 in climate zone 6.

DCV was not found to be cost effective if the typical minimum ventilation rate without DCV is 28 cfm per occupant, except at high design occupancy of 20 people per 1000 ft2 in climate zones 14 and 16.

Until the large uncertainties about the base case ventilation rates in offices without DCV are reduced, the case for requiring DCV in general office spaces will be a weak case.

10abuilding simulation10acalifornia building energy standard10aCommercial Building Ventilation and Indoor Environmental Quality Group10ademand controlled ventilation10aenergy savings10aindoor environment department10aother1 aHong, Tianzhen1 aFisk, William, J. uhttps://simulationresearch.lbl.gov/publications/assessment-energy-savings-potential00569nas a2200157 4500008004100000245006300041210006300104260003000167100001900197700001900216700002700235700002600262700001800288700001800306856008700324 2010 eng d00aAutomated Continuous Commissioning of Commercial Buildings0 aAutomated Continuous Commissioning of Commercial Buildings aWashington, D.C.c11/20101 aBailey, Trevor1 aO'Neill, Zheng1 aShashanka, Madhusudana1 aBhattacharya, Prajesh1 aHaves, Philip1 aPang, Xiufeng uhttps://simulationresearch.lbl.gov/publications/automated-continuous-commissioning00396nas a2200133 4500008004100000245002700041210002700068100001800095700001800113700002100131700002000152700001500172856007500187 2010 eng d00aBuildWise Final Report0 aBuildWise Final Report1 aKeane, Marcus1 aCosta, Andrea1 aO'Donnell, James1 aMenzel, Karsten1 aDirk, Alan uhttps://simulationresearch.lbl.gov/publications/buildwise-final-report02428nas a2200217 4500008004100000245013000041210006900171300001200240490000600252520155800258653001401816653003301830653003301863653009601896653001701992653004902009100002802058700002002086700002102106856008302127 2010 eng d00aA comparison of global optimization algorithms with standard benchmark functions and real-world applications using EnergyPlus0 acomparison of global optimization algorithms with standard bench a103-1200 v33 a

There is an increasing interest in the use of computer algorithms to identify combinations of parameters which optimize the energy performance of buildings. For such problems, the objective function can be multi-modal and needs to be approximated numerically using building energy simulation programs. As these programs contain iterative solution algorithms, they introduce discontinuities in the numerical approximation to the objective function. Metaheuristics often work well for such problems, but their convergence to a global optimum cannot be established formally. Moreover, different algorithms tend to be suited to particular classes of optimization problems. To shed light on this issue we compared the performance of two metaheuristics, the hybrid CMA-ES/HDE and the hybrid PSO/HJ, in minimizing standard benchmark functions and real-world building energy optimization problems of varying complexity. From this we find that the CMA-ES/HDE performs well on more complex objective functions, but that the PSO/HJ more consistently identifies the global minimum for simpler objective functions. Both identified similar values in the objective functions arising from energy simulations, but with different combinations of model parameters. This may suggest that the objective function is multi-modal. The algorithms also correctly identified some non-intuitive parameter combinations that were caused by a simplified controls sequence of the building energy system that does not represent actual practice, further reinforcing their utility.

10aalgorithm10aapplication using energyplus10abuilding energy minimization10acovariance matrix adaptation evolution strategy algorithm and hybrid differential evolution10aoptimization10aparticle swarm optimization and hooke-jeeves1 aKämpf, Jérôme, Henri1 aWetter, Michael1 aRobinson, Darren uhttps://simulationresearch.lbl.gov/publications/comparison-global-optimization01832nas a2200157 4500008004100000245015100041210006900192260001200261300001200273490000700285520123900292100001801531700001601549700002001565856008901585 2010 eng d00aCo-simulation for performance prediction of integrated building and HVAC systems - An analysis of solution characteristics using a two-body system0 aCosimulation for performance prediction of integrated building a c08/2010 a957-9700 v183 a

Integrated performance simulation of buildings and heating, ventilation and air-conditioning (HVAC) systems can help in reducing energy consumption and increasing occupant comfort. However, no single building performance simulation (BPS) tool offers sufficient capabilities and flexibilities to analyze integrated building systems and to enable rapid prototyping of innovative building and system technologies. One way to alleviate this problem is to use co-simulation to integrate different BPS tools. Co-simulation approach represents a particular case of simulation scenario where at least two simulators solve coupled differential-algebraic systems of equations and exchange data that couples these equations during the time integration.

This article analyzes how co-simulation influences consistency, stability and accuracy of the numerical approximation to the solution. Consistency and zero-stability are studied for a general class of the problem, while a detailed consistency and absolute stability analysis is given for a simple two-body problem. Since the accuracy of the numerical approximation to the solution is reduced in co-simulation, the article concludes by discussing ways for how to improve accuracy.

1 aTrcka, Marija1 aHensen, Jan1 aWetter, Michael uhttps://simulationresearch.lbl.gov/publications/co-simulation-performance-prediction02003nas a2200193 4500008004100000022001800041245011000059210006900169260004100238520131100279100002201590700001801612700002001630700002001650700002401670700001501694700001801709856008201727 2010 eng d a0-918249-60-000aDevelopment and Testing of Model Predictive Control for a Campus Chilled Water Plant with Thermal Storage0 aDevelopment and Testing of Model Predictive Control for a Campus aAsilomar, California, USAbOmnipress3 a

A Model Predictive Control (MPC) implementation was developed for a university campus chilled water plant. The plant includes three water-cooled chillers and a two million gallon chilled water storage tank. The tank is charged during the night to minimize on-peak electricity consumption and take advantage of the lower ambient wet bulb temperature. A detailed model of the chilled water plant and simplified models of the campus buildings were developed using the equation-based modeling language Modelica. Steady state models of the chillers, cooling towers and pumps were developed, based on manufacturers' performance data, and calibrated using measured data collected and archived by the control system. A dynamic model of the chilled water storage tank was also developed and calibrated. A semi-empirical model was developed to predict the temperature and flow rate of the chilled water returning to the plant from the buildings. These models were then combined and simplified for use in a MPC algorithm that determines the optimal chiller start and stop times and set-points for the condenser water temperature and the chilled water supply temperature. The paper describes the development and testing of the MPC implementation and discusses lessons learned and next steps in further research.

1 aCoffey, Brian, E.1 aHaves, Philip1 aWetter, Michael1 aHencey, Brandon1 aBorrelli, Francesco1 aMa, Yudong1 aBengea, Sorin uhttps://simulationresearch.lbl.gov/publications/development-and-testing-model01485nas a2200133 4500008004100000245008500041210006900126260002000195520097600215100002301191700003101214700001801245856008801263 2010 eng d00aDevelopment of an isothermal 2D zonal air volume model with impulse conservation0 aDevelopment of an isothermal 2D zonal air volume model with impu aAntalya, Turkey3 a

This paper presents a new approach to model air flows with a zonal model. The aim of zonal models is to perform quick simulations of the air distribution in rooms. Therefore an air volume is subdivided into several discrete zones, typically 10 to 100. The zones are connected with flow elements computing the amount of air exchanged between them. In terms of complexity and needed computational time zonal models are a compromise between CFD calculations and the approximation of perfect mixing. In our approach the air flow velocity is used as property of the zones. Thus the distinction between normal zones and jet or plume influenced zones becomes obsolete. The model is implemented in the object oriented and equation based language Modelica. A drawback of the new formulation is that the calculated flow pattern depends on the discretization. Nevertheless, the results show that the new zonal model performs well and is a useful extension to existing models.

1 aVictor, Norrefeldt1 aNouidui, Thierry, Stephane1 aGruen, Gunnar uhttps://simulationresearch.lbl.gov/publications/development-isothermal-2d-zonal-air00514nas a2200133 4500008004100000245009100041210006900132260002000201100001800221700001800239700002100257700001800278856008400296 2010 eng d00aEnergy Monitoring Systems value, issues and recommendations based on five case studies0 aEnergy Monitoring Systems value issues and recommendations based aAntalya, Turkey1 aRaferty, Paul1 aKeane, Marcus1 aO'Donnell, James1 aCosta, Andrea uhttps://simulationresearch.lbl.gov/publications/energy-monitoring-systems-value00492nas a2200121 4500008004100000245011800041210006900159300001200228490000700240100001600247700001800263856008900281 2010 eng d00aFast and informative flow simulation in a building by using fast fluid dynamics model on graphics processing unit0 aFast and informative flow simulation in a building by using fast a747-7570 v451 aZuo, Wangda1 aChen, Qingyan uhttps://simulationresearch.lbl.gov/publications/fast-and-informative-flow-simulation00394nas a2200109 4500008004100000245005200041210005200093260002100145100001600166700001800182856008400200 2010 eng d00aFast simulation of smoke transport in buildings0 aFast simulation of smoke transport in buildings aBeograd, Serbian1 aZuo, Wangda1 aChen, Qingyan uhttps://simulationresearch.lbl.gov/publications/fast-simulation-smoke-transport00475nas a2200133 4500008004100000245007200041210006900113260001700182300001000199100001600209700001600225700001800241856008200259 2010 eng d00aImpact of time-splitting schemes on the accuracy of FFD simulations0 aImpact of timesplitting schemes on the accuracy of FFD simulatio aSyracuse, NY a55-601 aHu, Jianjun1 aZuo, Wangda1 aChen, Qingyan uhttps://simulationresearch.lbl.gov/publications/impact-time-splitting-schemes00555nas a2200157 4500008004100000245009400041210006900135300001200204490000800216100001900224700001900243700001500262700001600277700001800293856008600311 2010 eng d00aImpacts of Static Pressure Reset on VAV System Air Leakage, Fan Power, and Thermal Energy0 aImpacts of Static Pressure Reset on VAV System Air Leakage Fan P a428-4360 v1161 aLiu, Mingsheng1 aFeng, Jingjuan1 aWang, Zhan1 aZheng, Keke1 aPang, Xiufeng uhttps://simulationresearch.lbl.gov/publications/impacts-static-pressure-reset-vav00464nas a2200133 4500008004100000245007000041210006900111300000900180490000700189100001600196700001600212700001800228856008400246 2010 eng d00aImprovements on FFD modeling by using different numerical schemes0 aImprovements on FFD modeling by using different numerical scheme a1-160 v581 aZuo, Wangda1 aHu, Jianjun1 aChen, Qingyan uhttps://simulationresearch.lbl.gov/publications/improvements-ffd-modeling-using00460nas a2200121 4500008004100000245008000041210006900121260001700190300001200207100001600219700001800235856008500253 2010 eng d00aImprovements on the fast fluid dynamics model for indoor airflow simulation0 aImprovements on the fast fluid dynamics model for indoor airflow aNew York, NY a539-5461 aZuo, Wangda1 aChen, Qingyan uhttps://simulationresearch.lbl.gov/publications/improvements-fast-fluid-dynamics01213nas a2200169 4500008004100000245008300041210006900124260003800193520061000231100001500841700002400856700002000880700002200900700001800922700001800940856008500958 2010 eng d00aModel Predictive Control of Thermal Energy Storage in Building Cooling Systems0 aModel Predictive Control of Thermal Energy Storage in Building C aBaltimore, Maryland, USAc06/20103 aA model-based predictive control (MPC) is designed for optimal thermal energy storage in building cooling systems. We focus on buildings equipped with a water tank used for actively storing cold water produced by a series of chillers. Typically the chillers are operated at night to recharge the storage tank in order to meet the building demands on the following day. In this paper, we build on our previous work, improve the building load model, and present experimental results. The experiments show that MPC can achieve reductionin the central plant electricity cost and improvement of its efficiency.1 aMa, Yudong1 aBorrelli, Francesco1 aHencey, Brandon1 aCoffey, Brian, E.1 aBengea, Sorin1 aHaves, Philip uhttps://simulationresearch.lbl.gov/publications/model-predictive-control-thermal01850nas a2200145 4500008004100000245007900041210006900120520131700189100002001506700002501526700002401551700001801575700002201593856008901615 2010 eng d00aModeling and Measurement Constraints in Fault Diagnostics for HVAC Systems0 aModeling and Measurement Constraints in Fault Diagnostics for HV3 aMany studies have shown that energy savings of five to fifteen percent are achievable in commercial buildings by detecting and correcting building faults, and optimizing building control systems. However,in spite of good progress in developing tools for determining HVAC diagnostics, methods to detect faults in HVAC systems are still generally undeveloped. Most approaches use numerical filtering or parameter estimation methods to compare data from energy meters and building sensors to predictions from mathematical or statistical models. They are effective when models are relatively accurate and data contain few errors. In this paper, we address the case where models are imperfect and data are variable, uncertain, and can contain error. We apply a Bayesian updating approach that is systematic in managing and accounting for most forms of model and data errors. The proposed method uses both knowledge of first principle modeling and empirical results to analyze the system performance within the boundaries defined by practical constraints. We demonstrate the approach by detecting faults in commercial building air handling units. We find that the limitations that exist in air handling unit diagnostics due to practical constraints can generally be effectively addressed through the proposed approach.1 aNajafi, Massieh1 aAuslander, David, M.1 aBartlett, Peter, L.1 aHaves, Philip1 aSohn, Michael, D. uhttps://simulationresearch.lbl.gov/publications/modeling-and-measurement-constraints00423nas a2200121 4500008004100000245006300041210006300104300001200167490000700179100001600186700001800202856008100220 2010 eng d00aSimulations of air distribution in buildings by FFD on GPU0 aSimulations of air distribution in buildings by FFD on GPU a783-7960 v161 aZuo, Wangda1 aChen, Qingyan uhttps://simulationresearch.lbl.gov/publications/simulations-air-distribution00472nas a2200121 4500008004100000245007400041210006900115100002000184700002500204700001800229700002200247856008100269 2010 eng d00aA Statistical Pattern Analysis Framework for Rooftop Unit Diagnostics0 aStatistical Pattern Analysis Framework for Rooftop Unit Diagnost1 aNajafi, Massieh1 aAuslander, David, M.1 aHaves, Philip1 aSohn, Michael, D. uhttps://simulationresearch.lbl.gov/publications/statistical-pattern-analysis02269nas a2200169 4500008004100000020001800041245011700059210006900176260004100245520162500286100002201911700002201933700001801955700002201973700001801995856008602013 2010 eng d a0-918249-60-000aSystems Approach to Energy Efficient Building Operation: Case Studies and Lessons Learned in a University Campus0 aSystems Approach to Energy Efficient Building Operation Case Stu aAsilomar, California, USAbOmnipress3 a

This paper reviews findings from research conducted at a university campus to develop a robust systems approach to monitor and continually optimize building energy performance. The field analysis, comprising three projects, included detailed monitoring, model-based analysis of system energy performance, and implementation of optimized control strategies for both district and building-scale systems. One project used models of the central cooling plant and campus building loads, and weather forecasts to analyze and optimize the energy performance of a district cooling system, comprising chillers, pumps and a thermal energy storage system. Fullscale implementation of policies devised with a model predictive control approach produced energy savings of about 5%, while demonstrating that the heuristic policies implemented by the operators were close to optimal during peak cooling season and loads. Research was also conducted to evaluate whole building monitoring and control methods. A second project performed in a campus building combined sub-metered end-use data, performance benchmarks, energy simulations and thermal load estimators to create a web-based energy performance visualization tool prototype. This tool provides actionable energy usage information to aid in facility operation and to enable performance improvement. In a third project, an alternative to demand controlled ventilation enabled by direct measurements of building occupancy levels was assessed. Simulations were used to show 5-15% reduction in building HVAC system energy usage when using estimates of actual occupancy levels.

1 aNarayanan, Satish1 aApte, Michael, G.1 aHaves, Philip1 aPiette, Mary, Ann1 aElliott, John uhttps://simulationresearch.lbl.gov/publications/systems-approach-energy-efficient02004nas a2200301 4500008004100000022001400041245013400055210006900189260001200258300001100270490000700281520102100288653001501309653001801324653002601342653003601368653003201404653001501436653002401451100001401475700002401489700002201513700002001535700001601555700002101571700002101592856008901613 2009 eng d a1573-198700aAnisotropy invariant Reynolds stress model of turbulence (AIRSM) and its application on attached and separated wall-bounded flows0 aAnisotropy invariant Reynolds stress model of turbulence AIRSM a c07/2009 a81-1030 v833 a

Numerical predictions with a differential Reynolds stress closure, which in its original formulation explicitly takes into account possible states of turbulence on the anisotropy-invariant map, are presented. Thus the influence of anisotropy of turbulence on the modeled terms in the governing equations for the Reynolds stresses is accounted for directly. The anisotropy invariant Reynolds stress model (AIRSM) is implemented and validated in different finite-volume codes. The standard wall-function approach is employed as initial step in order to predict simple and complex wall-bounded flows undergoing large separation. Despite the use of simple wall functions, the model performed satisfactory in predicting these flows. The predictions of the AIRSM were also compared with existing Reynolds stress models and it was found that the present model results in improved convergence compared with other models. Numerical issues involved in the implementation and application of the model are also addressed.

10aAnisotrpoy10aInvariant map10aReynolds stress model10aReynolds-averaged Navier-Stokes10aSeparated wall-bounded flow10aTurbulence10aTurbulence modeling1 aKumar, V.1 aFrohnapfel, Bettina1 aJovanović, Jovan1 aBreuer, Michael1 aZuo, Wangda1 aHadzić, Ibrahim1 aLechner, Richard uhttps://simulationresearch.lbl.gov/publications/anisotropy-invariant-reynolds-stress01856nas a2200133 4500008004100000245009800041210006900139260002400208520133300232100001701565700003101582700002101613856008801634 2009 eng d00aApplication of software tools for moisture protection of buildings in different climate zones0 aApplication of software tools for moisture protection of buildin aSisimiut, Groenland3 a

The application of software tools for moisture protection of buildings in different climatic zones is demonstrated in this paper. The basics of the programs are presented together with a typical application for a problem specific for the chosen climatic zone. A 1-D calculation has been performed for tropical climate zone with the improvement of a flat roof in Bangkok as an example. For half timbered buildings, which are common in the temperate zone with the 2-D model an infill insulation and its benefits are demonstrated. Finally the combined appliance of the whole building model and the mould risk prognosis model is shown in detail as a special case for the cold climate zone: In heated buildings of cold climate zones the internal climate with its low relative humidity in wintertime often causes discomfort and health problems for the occupants. In case of using air humidifier the risk of mould growth increases. Instead of an uncontrolled humidifying of the dry air an innovativecontrol system using a thermal bridge, which switches the humidifier off when condensation occurs is presented. To quantify the improvement in the comfort while preventing the risk of mould growth for a typical building comparative calculations of the resulting inner climates and its consequences on comfort have been performed.

1 aKrus, Martin1 aNouidui, Thierry, Stephane1 aSedlbauer, Klaus uhttps://simulationresearch.lbl.gov/publications/application-software-tools-moisture00473nas a2200121 4500008003900000245008000039210006900119260001200188100001900200700002700219700002100246856008400267 2009 d00aAssessment of Energy Impact of Window Technologies for Commercial Buildings0 aAssessment of Energy Impact of Window Technologies for Commercia c10/20091 aHong, Tianzhen1 aSelkowitz, Stephen, E.1 aYazdanian, Mehry uhttps://simulationresearch.lbl.gov/publications/assessment-energy-impact-window00462nas a2200145 4500008004100000245004900041210004900090260001200139300001400151490000700165100001700172700002000189700001900209856008800228 2009 eng d00aCase study of zero energy house design in UK0 aCase study of zero energy house design in UK c11/2009 a1215-12220 v411 aWang, Liping1 aGwilliam, Julie1 aJones, Phillip uhttps://simulationresearch.lbl.gov/publications/case-study-zero-energy-house-design02303nas a2200169 4500008004100000245008100041210006900122300001200191490000800203520174400211100001401955700001901969700001801988700001502006700002202021856009002043 2009 eng d00aCCLEP Reduces Energy Consumption by More than 50% for a Luxury Shopping Mall0 aCCLEP Reduces Energy Consumption by More than 50 for a Luxury Sh a492-5010 v1153 a

The Continuous Commissioning Leading Project (CCLEP) process is an ongoing process to apply system optimization theory and advanced technologies to commercial retrofit projects. It was developed by Liu et al (2006) through a U.S. Department of Energy grant to the University of Nebraska and the Omaha Public Power District (OPPD) for continuous commissioning applications in commercial retrofit projects. The CCLEP process, procedures and seven case study results have already been presented (Liu et al 2006).

CCLEP was applied to a luxury shopping mall and office building. The case study building has ten single fan dual-duct VAV AHUs, 123 dual-duct pneumatic controller pressure independent terminal boxes, and a central heating and cooling plant. Major retrofit efforts include upgrading pneumatic to DDC controls for all AHUs, installing main hot deck dampers, replacing the boiler, installing VFD on fans and pumps, and installing Fan Airflow Stations (FAS) and Pump Waterflow Stations (PWS). This paper presents the optimal control strategies, which include main hot deck damper control, supply fan control integrated with FAS, return fan control, optimal control for terminal boxes, chilled water temperature and chilled water pump speed control, hot water temperature and hot water pump control. The measured hourly utility data after CCLEP show that annual HVAC electricity consumption is reduced by 56% and gas use is reduced by 36%.

This paper demonstrates the energy savings and system performance improvement through retrofits and optimal system control. This paper will present the case study building information, CCLEP major retrofits, CCLEP optimal control strategies, CCLEP results and conclusions

1 aWu, Lixia1 aLiu, Mingsheng1 aPang, Xiufeng1 aWang, Gang1 aLewis, Thomas, G. uhttps://simulationresearch.lbl.gov/publications/cclep-reduces-energy-consumption-more01425nas a2200205 4500008004100000245008800041210006900129260000900198300001200207490000700219520077000226653001600996653002901012653001001041653002501051653002201076653001701098100001901115856008501134 2009 eng d00aA close look at the China design standard for energy efficiency of public buildings0 aclose look at the China design standard for energy efficiency of c2009 a426-4350 v413 a

This paper takes a close look at the China national standard GB50189-2005, Design Standard for Energy Efficiency of Public Buildings, which was enforced on July 1, 2005. The paper first reviews the standard, then compares the standard with ASHRAE Standard 90.1-2004 to identify discrepancies in code coverage and stringency, and recommends some energy conservation measures that can be evaluated in the design of public buildings to achieve energy savings beyond the standard. The paper also highlights several important features of 90.1-2004 that may be considered as additions to the GB50189-2005 standard during the next revision. At the end the paper summarizes the latest developments in building energy standards and rating systems in China and the US.

10aASHRAE 90.110abuilding energy standard10aChina10acommercial buildings10aenergy efficiency10agb50189-20051 aHong, Tianzhen uhttps://simulationresearch.lbl.gov/publications/close-look-china-design-standard01692nas a2200205 4500008004100000245011400041210006900155260000900224300001200233490000700245520103500252653002401287653001001311653002201321653000901343653000801352100001801360700001901378856008901397 2009 eng d00aComparison of energy efficiency between variable refrigerant flow systems and ground source heat pump systems0 aComparison of energy efficiency between variable refrigerant flo c2009 a584-5890 v423 a

With the current movement towards net zero energy buildings, many technologies are promoted with emphasis on their superior energy efficiency. The variable refrigerant flow (VRF) and ground source heat pump (GSHP) systems are probably the most competitive technologies among these. However, there are few studies reporting the energy efficiency of VRF systems compared with GSHP systems. In this article, a preliminary comparison of energy efficiency between the air-source VRF and GSHP systems is presented. The computer simulation results show that GSHP system is more energy efficient than the air-source VRF system for conditioning a small office building in two selected US climates. In general, GSHP system is more energy efficient than the air-source VRV system, especially when the building has significant heating loads. For buildings with less heating loads, the GSHP system could still perform better than the air-source VRF system in terms of energy efficiency, but the resulting energy savings may be marginal.

10abuilding simulation10adoe-210aenergy efficiency10agshp10avrf1 aLiu, Xiaobing1 aHong, Tianzhen uhttps://simulationresearch.lbl.gov/publications/comparison-energy-efficiency-between01687nas a2200193 4500008004100000245006900041210006800110300001200178490000600190520103000196653003601226653001801262653002001280653005601300100001801356700001601374700002001390856008301410 2009 eng d00aCo-simulation of innovative integrated HVAC systems in buildings0 aCosimulation of innovative integrated HVAC systems in buildings a209-2300 v23 a

Integrated performance simulation of buildings HVAC systems can help in reducing energy consumption and increasing occupant comfort. However, no single building performance simulation (BPS) tool offers sufficient capabilities and flexibilities to analyze integrated building systems and to enable rapid prototyping of innovative building and system technologies. One way to alleviate this problem is to use co-simulation, as an integrated approach to simulation. This article elaborates on issues important for co-simulation realization and discusses multiple possibilities to justify the particular approach implemented in the here described co-simulation prototype. The prototype is validated with the results obtained from the traditional simulation approach. It is further used in a proof-of-concept case study to demonstrate the applicability of the method and to highlight its benefits. Stability and accuracy of different coupling strategies are analyzed to give a guideline for the required coupling time step.

10abuilding performance simulation10aco-simulation10ahvac simulation10ainnovative building system modelling and simulation1 aTrcka, Marija1 aHensen, Jan1 aWetter, Michael uhttp://www.informaworld.com/smpp/section?content=a913244253&fulltext=71324092800575nas a2200133 4500008004100000245017900041210006900220260001200289300001100301490000700312100001700319700002100336856008400357 2009 eng d00aCoupled simulations for naturally ventilated rooms between building simulation (BS) and computational fluid dynamics (CFD) for better prediction of indoor thermal environment0 aCoupled simulations for naturally ventilated rooms between build c01/2009 a95-1120 v441 aWang, Liping1 aWong, Nyuk, Hien uhttps://simulationresearch.lbl.gov/publications/coupled-simulations-naturally-000423nas a2200109 4500008004100000245006700041210006700108260001700175100001600192700001800208856008700226 2009 eng d00aFast parallelized flow simulations on graphic processing units0 aFast parallelized flow simulations on graphic processing units aBusan, Korea1 aZuo, Wangda1 aChen, Qingyan uhttps://simulationresearch.lbl.gov/publications/fast-parallelized-flow-simulations01686nas a2200133 4500008004100000050001500041245005900056210005700115300001200172490000800184520125400192100002001446856008601466 2009 eng d aLBNL-2077E00aGeneric Optimization Program User Manual Version 3.0.00 aGeneric Optimization Program User Manual Version 300 a380-3910 v1133 a

A software tool that automates the analysis of functional tests for air-handling units is described. The tool compares the performance observed during manual tests with the performance predicted by simple models of the components under test that are configured using design information and catalog data. Significant differences between observed and expected performance indicate the presence of faults. Fault diagnosis is performed by analyzing the variation of these differences with operating point using expert rules and fuzzy inferencing.

The tool has a convenient user interface to facilitate manual entry of measurements made during a test. A graphical display compares the measured and expected performance, highlighting significant differences that indicate the presence of faults. The tool is designed to be used by commissioning providers conducting functional tests as part of either new building commissioning or retro-commissioning, as well as by building owners and operators conducting routine tests to check the performance of their HVAC systems. The paper describes the input data requirements of the tool, the software structure, the graphical interface, and summarizes the development and testing process used.

1 aWetter, Michael uhttps://simulationresearch.lbl.gov/publications/generic-optimization-program-user00409nas a2200121 4500008004100000245004600041210004600087260001800133300001200151100001600163700001800179856009000197 2009 eng d00aHigh performance computing for indoor air0 aHigh performance computing for indoor air aGlasgow, U.K. a244-2491 aZuo, Wangda1 aChen, Qingyan uhttps://simulationresearch.lbl.gov/publications/high-performance-computing-indoor-air01911nas a2200145 4500008004100000245011700041210006900158260003100227300001200258520137900270100001801649700002001667700001601687856006201703 2009 eng d00aAn implementation of co-simulation for performance prediction of innovative integrated HVAC systems in buildings0 aimplementation of cosimulation for performance prediction of inn aGlasgow, Scotlandc07/2009 a724-7313 aIntegrated performance simulation of buildings and heating, ventilation and air-conditioning (HVAC)systems can help reducing energy consumption and increasing level of occupant comfort. However, no singe building performance simulation (BPS) tool offers sufficient capabilities and flexibilities to accommodate the ever-increasing complexity and rapid innovations in building and system technologies. One way to alleviate this problem is to use co-simulation. The co-simulation approach represents a particular case of simulation scenario where at least two simulators solve coupled differential-algebraic systems of equations and exchange data that couples these equations during the time integration. This paper elaborates on issues important for co-simulation realization and discusses multiple possibilities to justify the particular approach implemented in a co-simulation prototype. The prototype is verified and validated against the results obtained from the traditional simulation approach. It is further used in a case study for the proof-of-concept, to demonstrate the applicability of the method and to highlight its benefits. Stability and accuracy of different coupling strategies are analyzed to give a guideline for the required coupling frequency. The paper concludes by defining requirements and recommendations for generic co-simulation implementations.1 aTrcka, Marija1 aWetter, Michael1 aHensen, Jan uhttp://www.ibpsa.org/proceedings/BS2009/BS09_0724_731.pdf02419nas a2200157 4500008004100000245007800041210006900119260001200188300001200200490000800212520190100220100001902121700001902140700001802159856008402177 2009 eng d00aImproving Control and Operation of a Single Duct VAV System through CCLEP0 aImproving Control and Operation of a Single Duct VAV System thro c07/2009 a760-7680 v1153 a

With the energy crisis of the early 1970s came the realization that buildings could be made much more efficient without sacrificing comfort. Over the last 30 years, use of variable air volume systems has become common practice. Many variable air volume (VAV) systems with pneumatic controls were installed in the 1980s and are still in use. However, these systems often have outdated control strategies and deficient mechanical systems are deficient, which may cause occupant discomfort and excess energy consumption.

An ASHRAE committee proposed building commissioning in 1988 to ensure that system performance met design specifications. Continuous Commissioning (CC[R]) technology was developed and implemented in 1992. CC is an ongoing process to resolve operating problems, improve comfort, optimize energy use and identify retrofits for existing commercial and institutional buildings and central plant facilities [1-5]. Since 1999, the Energy Systems Laboratory (ESL) at the University of Nebraska has conducted extensive research to implement optimal system control during the design phase and finalize the optimal setpoints after system installation. ESL researchers have developed and implemented the Continuous Commissioning Leading Energy Project (CCLEP) process with federal and industry support. The CCLEP process has two stages: the contracting stage and the implementation stage. During the contracting stage, a comprehensive technical evaluation is performed. The CCLEP implementation stage involves planning, retrofit and trouble shooting, and optimization and follow-up. The CCLEP process, procedures and seven case study results are presented in [6].

This paper presents information on the case study facility, existing and improved control sequences, and building performance improvement and energy consumption measures before and after CCLEP implementation

1 aCho, Young-Hum1 aLiu, Mingsheng1 aPang, Xiufeng uhttps://simulationresearch.lbl.gov/publications/improving-control-and-operation01151nas a2200145 4500008004100000245008900041210006900130260002200199520065200221100001800873700001800891700001800909700002100927856005700948 2009 eng d00aKey Factors - Methodology for Enhancement and Support of Building Energy Performance0 aKey Factors Methodology for Enhancement and Support of Building  aGlasgow, Scotland3 a

This paper presents the Key Factors methodology that supports energy managers in determining the optimal building operation strategy in relation to both energy consumption and thermal comfort. The methodology is supported by the utilisation of calibrated building energy simulation models that match measured data gathered by an extensive measurement framework. The paper outlines the proposed methodology defining the underpinning concepts and illustrating the performance metrics required to capture the effect of different building operation strategies. A brief case study is discussed to demonstrate the application of the methodology.

1 aCosta, Andrea1 aKeane, Marcus1 aRaferty, Paul1 aO'Donnell, James uhttp://zuse.ucc.ie/iruse/papersNew/AndreaGlasgow.pdf01678nas a2200133 4500008004100000245008400041210006900125250000700194260002500201490000700226520121900233100002001452856007201472 2009 eng d00aModelica Library for Building Heating, Ventilation and Air-Conditioning Systems0 aModelica Library for Building Heating Ventilation and AirConditi a44 aComo, Italyc09/20090 v433 a

The Buildings library is a freely available Modelica library that is based on Modelica.Fluid. It contains component models for building heating, ventilation and air conditioning systems. It also contains an interface that allows co-simulation with the Ptolemy software framework for concurrent, real-time, embedded systems developed by the University of California at Berkeley. The primary applications are controls design, energy analysis and model-based operation. The library has been used to model hydronic space heating systems, variable air volume flow systems and it has been linked to the EnergyPlus building energy simulation program for co-simulation using Ptolemy II. The library contains dynamic and steady-state component models that are applicable for analyzing fast transients when designing control algorithms and for conducting annual simulations when assessing energy performance. For most models, dimensional analysis is used to compute the performance for operating points that differ from nominal conditions. This allows parameterizing models in the absence of detailed geometrical information which is often impractical to obtain during the conceptual design phase of building systems.

1 aWetter, Michael uhttp://www.ep.liu.se/ecp_article/index.en.aspx?issue=043;article=4401978nas a2200133 4500008004100000245007500041210006900116260003100185300001200216520152100228653001301749100002001762856006201782 2009 eng d00aA Modelica-based model library for building energy and control systems0 aModelicabased model library for building energy and control syst aGlasgow, Scotlandc07/2009 a652-6593 a

This paper describes an open-source library with component models for building energy and control systems that is based on Modelica, an equation-based object oriented language that is well positioned to become the standard for modeling of dynamic systems in various industrial sectors. The library is currently developed to support computational science and engineering for innovative building energy and control systems. Early applications will include controls design and analysis, rapid prototyping to support innovation of new building systems and the use of models during operation for controls, fault detection and diagnostics. This paper discusses the motivation for selecting an equation-based object-oriented language. It presents the architecture of the library and explains how base model scan be used to rapidly implement new models. To demonstrate the capability of analyzing novel energy and control systems, the paper closes with an example where we compare the dynamic performance of a conventional hydronic heating system with thermostatic radiator valves to an innovative heating system. In the new system, instead of a centralized circulation pump, each of the 18 radiators has a pump whose speed is controlled using a room temperature feedback loop, and the temperature of the boiler is controlled based on the speed of the radiator pump. All flows are computed by solving for the pressure distribution in the piping network, and the controls include continuous and discrete time controls.

10amodelica1 aWetter, Michael uhttp://www.ibpsa.org/proceedings/BS2009/BS09_0652_659.pdf01955nas a2200133 4500008004100000245011800041210006900159300001200228490000600240520145900246653001301705100002001718856008301738 2009 eng d00aModelica-based Modeling and Simulation to Support Research and Development in Building Energy and Control Systems0 aModelicabased Modeling and Simulation to Support Research and De a143-1610 v23 aTraditional building simulation programs possess attributes that make them difficult to use for the design and analysis of building energy and control systems and for the support of model-based research and development of systems that may not already be implemented in these programs. This paper presents characteristic features of such applications, and it shows how equation-based object-oriented modeling can meet requirements that arise in such applications. Next, the implementation of an open-source component model library for building energy systems is presented. The library has been developed using the equation-based object-oriented Modelica modeling language. Technical challenges of modeling and simulating such systems are discussed. Research needs are presented to make this technology accessible to user groups that have more stringent requirements with respect to the numerical robustness of simulation than a research community may have. Two examples are presented in which models from the here described library were used. The first example describes the design of a controller for a nonlinear model of a heating coil using model reduction and frequency domain analysis. The second example describes the tuning of control parameters for a static pressure reset controller of a variable air volume flow system. The tuning has been done by solving a non-convex optimization problem that minimizes fan energy subject to state constraints.10amodelica1 aWetter, Michael uhttp://www.informaworld.com/smpp/section?content=a911401852&fulltext=71324092800477nas a2200145 4500008004100000245004300041210003000084260002700114100001700141700001500158700002300173700002600196700001500222856009400237 2009 eng d00a“The Monitoring,” Panel: Chill-Off0 aMonitoring Panel ChillOff aSunnyvale, CAc10/20091 aNelson, Dean1 aDay, Brian1 aBell, Geoffrey, C.1 aBhattacharya, Prajesh1 aRyan, Mike uhttps://simulationresearch.lbl.gov/publications/%E2%80%9C-monitoring%E2%80%9D-panel-chill00500nas a2200121 4500008004100000245010400041210006900145100002100214700001800235700002100253700001800274856008600292 2009 eng d00aMulti-criteria optimisation using past, historical, real time and predictive performance benchmarks0 aMulticriteria optimisation using past historical real time and p1 aTorrens, Ignacio1 aKeane, Marcus1 aO'Donnell, James1 aCosta, Andrea uhttps://simulationresearch.lbl.gov/publications/multi-criteria-optimisation-using00608nas a2200157 4500008004100000022001400041245013400055210006900189300001200258490000700270100003100277700002100308700002900329700001700358856007500375 2009 eng d a0171-544500aNeue objektorientierte hygrothermische Modell-Bibliothek zur Ermittlung des hygrothermischen und hygienischen Komforts in Räumen0 aNeue objektorientierte hygrothermische ModellBibliothek zur Ermi a271-2780 v311 aNouidui, Thierry, Stephane1 aSedlbauer, Klaus1 aNytsch-Geusen, Christoph1 aKießl, Kurt uhttps://simulationresearch.lbl.gov/publications/neue-objektorientierte00577nas a2200157 4500008004100000245008700041210006900128260002100197100001500218700002300233700001700256700001800273700001800291700002100309856008900330 2009 eng d00aPervasive Knowledge-Based Networking for Maintenance Inspection in Smart Buildings0 aPervasive KnowledgeBased Networking for Maintenance Inspection i aBarcelona, Spain1 aMara, Paul1 aO'Sullivan, Declan1 aBrennan, Rob1 aKeane, Marcus1 aMcGlinn, Kris1 aO'Donnell, James uhttps://simulationresearch.lbl.gov/publications/pervasive-knowledge-based-networking00439nas a2200121 4500008004100000245007400041210006900115300001000184490000700194100001600201700001800217856008200235 2009 eng d00aReal time or faster-than-real-time simulation of airflow in buildings0 aReal time or fasterthanrealtime simulation of airflow in buildin a33-440 v191 aZuo, Wangda1 aChen, Qingyan uhttps://simulationresearch.lbl.gov/publications/real-time-or-faster-real-time02060nas a2200217 4500008004100000245010500041210006900146260000900215300001200224490000600236520133500242653001601577653002401593653002301617653002201640653003001662653002901692100001501721700001901736856008701755 2009 eng d00aSimulation-based assessment of the energy savings benefits of integrated control in office buildings0 aSimulationbased assessment of the energy savings benefits of int c2009 a239-2510 v23 a

The purpose of this study is to use existing simulation tools to quantify the energy savings benefits of integrated control in office buildings. An EnergyPlus medium office benchmark simulation model (V1.0_3.0) developed by the Department of Energy (DOE) was used as a baseline model for this study. The baseline model was modified to examine the energy savings benefits of three possible control strategies compared to a benchmark case across 16 DOE climate zones. Two controllable subsystems were examined: (1) dimming of electric lighting, and (2) controllable window transmission. Simulation cases were run in EnergyPlus V3.0.0 for building window-to-wall ratios (WWR) of 33% and 66%. All three strategies employed electric lighting dimming resulting in lighting energy savings in building perimeter zones ranging from 64% to 84%. Integrated control of electric lighting and window transmission resulted in heating, ventilation, and air conditioning (HVAC) energy savings ranging from –1% to 40%. Control of electric lighting and window transmission with HVAC integration (seasonal schedule of window transmission control) resulted in HVAC energy savings ranging from 3% to 43%. HVAC energy savings decreased moving from warm climates to cold climates and increased when moving from humid, to dry, to marine climates.

10adaylighting10aenergy conservation10aenergy consumption10aenergy efficiency10aenergy management systems10alighting control systems1 aShen, Eric1 aHong, Tianzhen uhttps://simulationresearch.lbl.gov/publications/simulation-based-assessment-energy02217nas a2200217 4500008004100000020002200041245006700063210006400130250000700194260006500201490000700266520151600273653001301789100002101802700002301823700001801846700002001864700002301884700002001907856007201927 2009 eng d a978-91-7393-513-500aStandardization of thermo-fluid modeling in Modelica.Fluid 1.00 aStandardization of thermofluid modeling in ModelicaFluid 10 a13 aComo, ItalybLinköping University Electronic Pressc09/20090 v433 a

This article discusses the Modelica.Fluid library that has been included in the Modelica Standard Library 3.1. Modelica.Fluid provides interfaces and basic components for the device-oriented modeling of one dimensional thermo-fluid flow in networks containing vessels; pipes; fluid machines; valves and fittings.

A unique feature of Modelica.Fluid is that the component equations and the media models as well as pressure loss and heat transfer correlations are decoupled from each other. All components are implemented such that they can be used for media from the Modelica.Media library. This means that an incompressible or compressible medium; a single or a multiple substance medium with one or more phases might be used with one and the same model as long as the modeling assumptions made hold. Furthermore;

trace substances are supported. Modeling assumptions can be configured globally in an outer System object. This covers in particular the initialization; uni- or bi-directional flow; and dynamic or steady-state formulation of mass; energy; and momentum balance. All assumptions can be locally refined for every component.

While Modelica.Fluid contains a reasonable set of component models; the goal of the library is not to provide a comprehensive set of models; but rather to provide interfaces and best practices for the treatment of issues such as connector design and implementation of energy; mass and momentum balances. Applications from various domains are presented.

10amodelica1 aFranke, Rüdiger1 aCasella, Francesco1 aOtter, Martin1 aProelss, Katrin1 aSielemann, Michael1 aWetter, Michael uhttp://www.ep.liu.se/ecp_article/index.en.aspx?issue=043;article=1300537nas a2200145 4500008004100000022001500041245012400056210006900180260001500249100002100264700001700285700001900302700002100321856004900342 2009 eng d aLBNL-2819E00aTechnical Assistance to Beichuan Reconstruction: Creating and Designing Low- to Zero-carbon Communities in New Beichuan0 aTechnical Assistance to Beichuan Reconstruction Creating and Des bLBNLc20091 aXu, Tengfang, T.1 aWang, Chuang1 aHong, Tianzhen1 aLevine, Mark, D. uhttp://www.escholarship.org/uc/item/0vv4m1gb01592nas a2200169 4500008004100000245013000041210006900171490000900240520096100249100002201210700001801232700002701250700002101277700002101298700001801319856008501337 2009 eng d00aTowards a Very Low Energy Building Stock: Modeling the US Commercial Building Stock to Support Policy and Innovation Planning0 aTowards a Very Low Energy Building Stock Modeling the US Commerc0 v37:53 a

This paper describes the origin, structure and continuing development of a model of time varying energy consumption in the US commercial building stock. The model is based on a flexible structure that disaggregates the stock into various categories (e.g. by building type, climate, vintage and life-cycle stage) and assigns attributes to each of these (e.g. floor area and energy use intensity by fuel type and end use), based on historical data and user-defined scenarios for future projections. In addition to supporting the interactive exploration of building stock dynamics, the model has been used to study the likely outcomes of specific policy and innovation scenarios targeting very low future energy consumption in the building stock. Model use has highlighted the scale of the challenge of meeting targets stated by various government and professional bodies, and the importance of considering both new construction and existing buildings.

1 aCoffey, Brian, E.1 aBorgeson, Sam1 aSelkowitz, Stephen, E.1 aApte, Joshua, S.1 aMathew, Paul, A.1 aHaves, Philip uhttps://simulationresearch.lbl.gov/publications/towards-very-low-energy-building00509nas a2200133 4500008004100000245007900041210006900120260001200189100002000201700002500221700002400246700001800270856008700288 2008 eng d00aApplication of Machine Learning in Fault Diagnostics of Mechanical Systems0 aApplication of Machine Learning in Fault Diagnostics of Mechanic c10/20081 aNajafi, Massieh1 aAuslander, David, M.1 aBartlett, Peter, L.1 aHaves, Philip uhttps://simulationresearch.lbl.gov/publications/application-machine-learning-fault02680nas a2200133 4500008004100000245008800041210006900129260003600198520216900234100001802403700002202421700002002443856008302463 2008 eng d00aBenchmarking and Equipment and Controls Assessment for a ‘Big Box’ Retail Chain0 aBenchmarking and Equipment and Controls Assessment for a Big Box aAsilomar, California, USAc20083 a

The paper describes work to enable improved energy performance of existing and new retail stores belonging to a national chain and thereby also identify measures and tools that would improve the performance of ‘big box' stores generally. A detailed energy simulation model of a standard store design was developed and used to:

The core enabling task of the project was to develop an energy model of the current standard design using the EnergyPlus simulation program. For the purpose of verification of the model against actual utility bills, the model was reconfigured to represent twelve existing stores (seven relatively new stores and five older stores) in different US climates and simulations were performed using weather data obtained from the National Weather Service. The results of this exercise, which showed generally good agreement between predicted and measured total energy use, suggest that dynamic benchmarking based on energy simulation would be an effective tool for identifying operational problems that affect whole building energy use. The models of the seven newer stores were then configured with manufacturers' performance data for the equipment specified in the current design and used to assess the energy and cost benefits of increasing the efficiency of selected HVAC, lighting and envelope components. The greatest potential for cost-effective energy savings appears to be a substantial increase in the efficiency of the blowers in the roof top units and improvements in the efficiency of the lighting. The energy benefits of economizers on the roof-top units were analyzed and found to be very sensitive to the operation of the exhaust fans used to control building pressurization.

1 aHaves, Philip1 aCoffey, Brian, E.1 aWilliams, Scott uhttps://simulationresearch.lbl.gov/publications/benchmarking-and-equipment-and01364nas a2200229 4500008004100000245006400041210006400105260000900169300001200178490000600190520067400196653002200870653001000892653001500902653002300917100001900940700002100959700001800980700002700998700002001025856008901045 2008 eng d00aComparing computer run time of building simulation programs0 aComparing computer run time of building simulation programs c2008 a210-2130 v13 a

This paper presents an approach to comparing computer run time of building simulation programs. The computing run time of a simulation program depends on several key factors, including the calculation algorithm and modeling capabilities of the program, the run period, the simulation time step, the complexity of the energy models, the run control settings, and the software and hardware configurations of the computer that is used to make the simulation runs. To demonstrate the approach, simulation runs are performed for several representative DOE-2.1E and EnergyPlus energy models. The computer run time of these energy models are then compared and analyzed.

10acomputer run time10adoe-210aenergyplus10asimulation program1 aHong, Tianzhen1 aBuhl, Walter, F.1 aHaves, Philip1 aSelkowitz, Stephen, E.1 aWetter, Michael uhttps://simulationresearch.lbl.gov/publications/comparing-computer-run-time-building00674nas a2200205 4500008004100000245008400041210006900125260000900194490001500203653001600218653001000234653002300244653001500267653001500282100001900297700002100316700002100337700002100358856008900379 2008 eng d00aComparisons of HVAC Simulations between EnergyPlus and DOE-2.2 for data centers0 aComparisons of HVAC Simulations between EnergyPlus and DOE22 for c20090 v115 Part 110adata center10adoe-210aenergy performance10aenergyplus10asimulation1 aHong, Tianzhen1 aSartor, Dale, A.1 aMathew, Paul, A.1 aYazdanian, Mehry uhttps://simulationresearch.lbl.gov/publications/comparisons-hvac-simulations-between00443nas a2200097 4500008004100000245009700041210006900138260002500207100002600232856008700258 2008 eng d00aConvergence of IT and Facilities Real-Time and Historic Data Leads to Data Center Efficiency0 aConvergence of IT and Facilities RealTime and Historic Data Lead aOrlando, FLc05/20081 aBhattacharya, Prajesh uhttps://simulationresearch.lbl.gov/publications/convergence-it-and-facilities-real00466nas a2200133 4500008004100000245007100041210006900112260001200181300001200193490000700205100001700212700002100229856008200250 2008 eng d00aCoupled simulations for naturally ventilated residential buildings0 aCoupled simulations for naturally ventilated residential buildin c05/2008 a386-3980 v171 aWang, Liping1 aWong, Nyuk, Hien uhttps://simulationresearch.lbl.gov/publications/coupled-simulations-naturally00965nas a2200181 4500008004100000020002300041245006700064210006700131260002500198520039100223653001100614653001700625653001700642100001900659700001900678700002100697856006500718 2008 eng d a978-0-86341-894-5 00aDesign of Underlying Network Infrastructure of Smart Buildings0 aDesign of Underlying Network Infrastructure of Smart Buildings aSeattle, WAc07/20083 a

Wireless Building Management Systems (BMS) are an attractive option when it comes to building retrofitting due to the cost constraints introduced by wired systems. A crucial part of the wireless BMS is the initial planning stage, this process can be impossible for a designer to undertake, therefore highlighting the requirement for a software design tool to aid in this process.

10adesign10aoptimisation10aWireless BMS1 aMcGibney, Alan1 aKlepal, Martin1 aO'Donnell, James uhttp://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=462979000545nas a2200181 4500008004100000022001400041245005700055210005700112260001500169653002400184653002000208653001500228653001300243100001900256700002100275700001800296856004900314 2008 eng d aLBNL-822E00aEnergyPlus Analysis Capabilities for Use in Title 240 aEnergyPlus Analysis Capabilities for Use in Title 24 bLBNLc200810abuilding simulation10acode compliance10aenergyplus10atitle 241 aHong, Tianzhen1 aBuhl, Walter, F.1 aHaves, Philip uhttp://www.escholarship.org/uc/item/0z78090x00392nas a2200133 4500008004100000022003300041245003300074210003300107260001500140100001900155700002100174700001800195856004500213 2008 eng d aLBNL-1311E, CEC-500-2008-09400aEnergyPlus Run Time Analysis0 aEnergyPlus Run Time Analysis bLBNLc20081 aHong, Tianzhen1 aBuhl, Walter, F.1 aHaves, Philip uhttp://escholarship.org/uc/item/36h4m5z001212nas a2200145 4500008004100000245009100041210006900132260001200201520069300213100002000906700002500926700002400951700001800975856007300993 2008 eng d00aFault Diagnostics and Supervised Testing: How Fault Diagnostic tools can be Proactive?0 aFault Diagnostics and Supervised Testing How Fault Diagnostic to c11/20083 aThe topic of fault detection and diagnostics (FDD) is studied from the perspective of proactive testing. Unlike most research focus in the diagnosis area in which system outputs are analyzed for diagnosis purposes, in this paper the focus is on the other side of the problem: manipulating system inputs for better diagnosis reasoning. In other words, the question of how diagnostic mechanisms can direct system inputs for better diagnosis analysis is addressed here. It is shown how the problem can be formulated as decision making problem coupled with a Bayesian Network based diagnostic mechanism. The developed mechanism is applied to the problem of supervised testing in HVAC systems.1 aNajafi, Massieh1 aAuslander, David, M.1 aBartlett, Peter, L.1 aHaves, Philip uhttp://www.actapress.com/Content_of_Proceeding.aspx?proceedingID=50300440nas a2200109 4500008004100000245006000041210006000101260002000161100002900181700003100210856008900241 2008 eng d00aGebäudesimulation mit adaptiven Modellierungsansätzen0 aGebäudesimulation mit adaptiven Modellierungsansätzen aKassel, Germany1 aNytsch-Geusen, Christoph1 aNouidui, Thierry, Stephane uhttps://simulationresearch.lbl.gov/publications/geb%C3%A4udesimulation-mit-adaptiven00431nas a2200097 4500008004100000245008800041210006900129260002900198100002300227856008300250 2008 eng d00aIFC BIM-based Methodology for Semi-Automated Building Energy Performance Simulation0 aIFC BIMbased Methodology for SemiAutomated Building Energy Perfo aSantiago, Chilec07/20081 aBazjanac, Vladimir uhttps://simulationresearch.lbl.gov/publications/ifc-bim-based-methodology-semi00568nas a2200145 4500008004100000245009800041210006900139260002800208100001900236700002100255700002000276700001800296700001800314856009000332 2008 eng d00aIntegrating the Specification, Acquisition and Processing of Building Performance Information0 aIntegrating the Specification Acquisition and Processing of Buil aBeijing, Chinac10/20081 aKeller, Martin1 aO'Donnell, James1 aMenzel, Karsten1 aKeane, Marcus1 aGökçe, Ufuk uhttps://simulationresearch.lbl.gov/publications/integrating-specification-acquisition00424nas a2200097 4500008004100000245007500041210006900116260003100185100002000216856009000236 2008 eng d00aA Modelica-Based Model Library for Building Energy and Control Systems0 aModelicaBased Model Library for Building Energy and Control Syst aGlasgow, Scotlandc07/20081 aWetter, Michael uhttps://simulationresearch.lbl.gov/publications/modelica-based-model-library-building01943nas a2200121 4500008004100000245009400041210006900135260002600204520146700230100002001697700001801717856008601735 2008 eng d00aA Modular Building Controls Virtual Test Bed for the Integration of Heterogeneous Systems0 aModular Building Controls Virtual Test Bed for the Integration o aBerkeley, CAc08/20083 a

This paper describes the Building Controls Virtual Test Bed (BCVTB) that is currently under development at Lawrence Berkeley National Laboratory. An earlier prototype linked EnergyPlus with controls hardware through embedded SPARK models and demonstrated its value in more cost-effective envelope design and improved controls sequences for the San Francisco Federal Building. The BCVTB presented here is a more modular design based on a middleware that we built using Ptolemy II, a modular software environment for design and analysis of heterogeneous systems. Ptolemy II provides a graphical model building environment, synchronizes the exchanged data and visualizes the system evolution during run-time. Our additions to Ptolemy II allow users to couple to Ptolemy II a prototype version of EnergyPlus, MATLAB/Simulink or other simulation programs for data exchange during run-time. In future work we will also implement a BACnet interface that allows coupling BACnet compliant building automation systems to Ptolemy II. We will present the architecture of the BCVTB and explain how users can add their own simulation programs to the BCVTB. We will then present an example application in which the building envelope and the HVAC system was simulated in EnergyPlus, the supervisory control logic was simulated in MATLAB/Simulink and Ptolemy II was used to exchange data during run-time and to provide real-time visualization as the simulation progresses.

1 aWetter, Michael1 aHaves, Philip uhttps://simulationresearch.lbl.gov/publications/modular-building-controls-virtual02149nas a2200181 4500008004100000022002200041245021800063210006900281260002400350300001500374490000600389520138300395100003101778700002901809700001801838700002101856856009001877 2008 eng d a978-87-7877-265-700aObject-oriented hygrothermal building physics library as a tool to predict and to ensure a thermal and hygric indoor comfort in building construction by using a Predicted-Mean-Vote (PMV) control ventilation system0 aObjectoriented hygrothermal building physics library as a tool t aCopenhagen, Denmark app.825-8320 v23 a

The indoor temperature and humidity conditions of the building envelope are important parameters for the evaluation of the thermal and hygric indoor comfort. In the research project GENSIM a new hygrothermal building library, based on the object- and equation-oriented model description language Modelica® has been developed by the Fraunhofer Institutes IBP and FIRST. This library includes many models as for instance a hygrothermal wall model, an air volume model, a zone model, a window model and an environment model. Due to the object-oriented modelling approach, some models of this library can be configured to a complex hygrothermal room model, which can predict the time dependent indoor temperature and humidity conditions in a building construction. In this paper we will introduce in a first step the object-oriented hygrothermal room model of this library. In a second step, the validation of the room model with some field experiments will be shown. In a third step we willpresent some simulation results, we obtained by coupling the room model with an implemented Predicted-Mean-Vote (PMV) control ventilation system to predict and to ensure a thermal and hygric indoor comfort in one case study. In the conclusion, the possible range of future applications of this new hygrothermal building physics library and demands for further research are indicated.

1 aNouidui, Thierry, Stephane1 aNytsch-Geusen, Christoph1 aHolm, Andreas1 aSedlbauer, Klaus uhttps://simulationresearch.lbl.gov/publications/object-oriented-hygrothermal-building01442nas a2200145 4500008004100000245008800041210006900129260001000198520092700208100002001135700002501155700002401180700001801204856007401222 2008 eng d00aOvercoming the Complexity of Diagnostic Problems due to Sensor Network Architecture0 aOvercoming the Complexity of Diagnostic Problems due to Sensor N c11/083 a

In fault detection and diagnostics, limitations coming from the sensor network architecture are one of the main challenges in evaluating a system's health status. Usually the design of the sensor network architecture is not solely based on diagnostic purposes, other factors like controls, financial constraints, and practical limitations are also involved. As a result, it quite common to have one sensor (or one set of sensors) monitoring the behaviour of two or more components. This can significantly extend the complexity of diagnostic problems. In this paper a systematic approach is presented to deal with such complexities. It is shown how the problem can be formulated as a Bayesian network based diagnostic mechanism with latent variables. The developed approach is also applied to the problem of fault diagnosis in HVAC systems, an application area with considerable modeling and measurement constraints.

1 aNajafi, Massieh1 aAuslander, David, M.1 aBartlett, Peter, L.1 aHaves, Philip uhttps://www.actapress.com/Content_Of_Proceeding.aspx?ProceedingID=50302848nas a2200145 4500008004100000024002000041245004500061210004500106260002400151520237200175100002102547700002202568700002202590856009002612 2008 eng d aESL-HH-08-12-2700aReducing Energy Use In Florida Buildings0 aReducing Energy Use In Florida Buildings aDallas, TXc12/20083 a

The 2007 Florida Building Code (ICC, 2008) requires building designers and architects to achieve a minimum energy efficiency rating for commercial buildings located throughout Florida. Although the Florida Building Code is strict in the minimum requirements for new construction, several aspects of building construction can be further improved through careful thought and design. This report outlines several energy saving features that can be used to ensure that new buildings meet a new target goal of 85% energy use compared to the 2007 energy code in order to achieve Governor Crist's executive order to improve the energy code by 15%.

To determine if a target goal of 85% building energy use is attainable, a computer simulation study was performed to determine the energy saving features available which are, in most cases, stricter than the current Florida Building Code. The energy savings features include improvements to building envelop, fenestration, lighting and equipment, and HVAC efficiency. The imp acts of reducing outside air requirements and employing solar water heating were also investigated. Th e purpose of the energy saving features described in this document is intended to provide a simple, prescriptive method for reducing energy consumption using the methodology outlined in ASHRAE Standard 90.1 (ASHRAE, 2007).

There are two difficulties in trying to achieve savings in non-residential structures. First, there is significant energy use caused by internal loads for people and equipment and it is difficult to use the energy code to achieve savings in this area relative to a baseline. Secondly, the ASHRAE methodology uses some of the same features that are proposed for the new building, so it may be difficult to claim savings for some strategies that will produce savings such as improved ventilation controls, reduced window area, or reduced plug loads simply because the methodology applies those features to the comparison reference building.

Several measures to improve the building envelope characteristics were simulated. Simply using the selected envelope measures resulted in savings of less than 10% for all building types. However, if such measures are combined with aggressive lighting reductions and improved efficiency HVAC equipment and controls, a target savings of 15% is easily attainable.

1 aRaustad, Richard1 aBasarkar, Mangesh1 aVieira, Robin, K. uhttps://simulationresearch.lbl.gov/publications/reducing-energy-use-florida-buildings00539nas a2200121 4500008004100000245012700041210006900168260003100237100002100268700001800289700002300307856008700330 2008 eng d00aSpecification of an Information Delivery Tool to Support Optimal Holistic Environmental and Energy Management in Buildings0 aSpecification of an Information Delivery Tool to Support Optimal aBerkeley, CA, USAc07/20081 aO'Donnell, James1 aKeane, Marcus1 aBazjanac, Vladimir uhttps://simulationresearch.lbl.gov/publications/specification-information-delivery00357nas a2200097 4500008004100000245004500041210004500086260001200131100002600143856009000169 2008 eng d00aUnlocking Historical Data in Critical IT0 aUnlocking Historical Data in Critical IT c12/20081 aBhattacharya, Prajesh uhttps://simulationresearch.lbl.gov/publications/unlocking-historical-data-critical-it00454nas a2200133 4500008004100000245004100041210004100082260003100123100002000154700001800174700002500192700002300217856008000240 2008 eng d00aUsing SPARK as a Solver for Modelica0 aUsing SPARK as a Solver for Modelica aBerkeley, CA, USAc07/20081 aWetter, Michael1 aHaves, Philip1 aMoshier, Michael, A.1 aSowell, Edward, F. uhttps://simulationresearch.lbl.gov/publications/using-spark-solver-modelica01363nas a2200145 4500008004100000245004100041210004100082260003100123520089400154100002001048700001801068700002501086700002301111856008301134 2008 eng d00aUsing SPARK as a solver for Modelica0 aUsing SPARK as a solver for Modelica aBerkeley, CA, USAc08/20083 a

Modelica is an object-oriented acausal modeling language that is well positioned to become a de-facto standard for expressing models of complex physical systems. To simulate a model expressed in Modelica, it needs to be translated into executable code. For generating run-time efficient code, such a translation needs to employ algebraic formula manipulations. As the SPARK solver has been shown to be competitive for generating such code but currently cannot be used with the Modelica language, we report in this paper how SPARK's symbolic and numerical algorithms can be implemented in OpenModelica, an open-source implementation of a Modelica modeling and simulation environment. We also report benchmark results that show that for our air flow network simulation benchmark, the SPARK solver is competitive with Dymola, which is believed to provide the best solver for Modelica.

1 aWetter, Michael1 aHaves, Philip1 aMoshier, Michael, A.1 aSowell, Edward, F. uhttp://www.ibpsa.us/simbuild2008/technical_sessions/SB08-DOC-TS03-1-Wetter.pdf00514nas a2200121 4500008004100000245011700041210006900158260001700227100002100244700001800265700002300283856008600306 2008 eng d00aUtilisation of Whole Building Energy Simulation Output to Provide Optimum Decision Support for Building Managers0 aUtilisation of Whole Building Energy Simulation Output to Provid aBerkeley, CA1 aO'Donnell, James1 aKeane, Marcus1 aBazjanac, Vladimir uhttps://simulationresearch.lbl.gov/publications/utilisation-whole-building-energy00473nas a2200097 4500008004100000245012400041210006900165260002800234100002500262856008800287 2007 eng d00aAdvanced Zone Simulation in EnergyPlus: Incorporation of Variable Properties and Phase Change Material (PCM) Capability0 aAdvanced Zone Simulation in EnergyPlus Incorporation of Variable aBeijing, Chinac09/20071 aPedersen, Curtis, O. uhttps://simulationresearch.lbl.gov/publications/advanced-zone-simulation-energyplus00356nas a2200097 4500008004100000245004300041210004300084260002800127100001500155856008800170 2007 eng d00aAirflow Network Modeling in EnergyPlus0 aAirflow Network Modeling in EnergyPlus aBeijing, Chinac09/20071 aGu, Lixing uhttps://simulationresearch.lbl.gov/publications/airflow-network-modeling-energyplus01584nas a2200169 4500008004100000245014200041210006900183260001800252520098100270653001301251653002301264653002501287653001201312100001801324700001301342856005901355 2007 eng d00aThe Building Controls Virtual Test Bed – a Simulation Environment for Developing and Testing Control Algorithms, Strategies and Systems0 aBuilding Controls Virtual Test Bed a Simulation Environment for  aBejing, China3 a

The paper describes the design of a Building Controls Virtual Test Bed (BCVTB), a simulation environment for the development of control algorithms and strategies for the major energy systems in buildings, HVAC, lighting, active facades and on-site generation. The BCVTB is based on the whole building energy simulation program EnergyPlus and includes both the pure simulation and the hardware-in-the-loop methods of implementing the controls. For convenience and scalability, the design of the hardware-in-the-loop interface for supervisory controls uses BACnet rather than the analog interface used for local loop control. The paper concludes with a case study of the use of a prototype implementation of the BCVTB to precommission the building control system for the naturally-ventilated San Francisco Federal Building. A number of problems were found with the control program, demonstrating the value of the precommissioning and the effectiveness of the technique.

10acontrols10adevelopment system10ahardware-in-the-loop10atesting1 aHaves, Philip1 aXu, Peng uhttp://www.ibpsa.org/proceedings/BS2007/p748_final.pdf00487nas a2200121 4500008004100000245008500041210006900126260002800195100001800223700002000241700001600261856008800277 2007 eng d00aComparison of Co-Simulation Approaches for Building and HVAC/R System Simulation0 aComparison of CoSimulation Approaches for Building and HVACR Sys aBeijing, Chinac09/20071 aTrcka, Marija1 aWetter, Michael1 aHensen, Jan uhttps://simulationresearch.lbl.gov/publications/comparison-co-simulation-approaches01771nas a2200145 4500008004100000245008900041210006900130260002800199300001400227520127100241100001801512700002001530700001601550856005901566 2007 eng d00aComparison of co-simulation approaches for building and HVAC/R system simulation.
0 aComparison of cosimulation approaches for building and HVACR sys aBeijing, Chinac09/2007 a1418-14253 aAppraisal of modern performance-based energy codes, as well as heating, ventilation, air- conditioning and refrigeration (HVAC/R) system*design require use of an integrated building and system performance simulation program. However, the required scope of the modeling library of such integrated tools often goes beyond those offered in available simulation programs. One remedy for this situation would be to develop the required models in an existing simulation program. However, due to the lack of model interoperability, the model would not be available in other simulation programs. We suggest co-simulation for HVAC/R system simulation as an approach to alleviate the above issues. In co-simulation, each subsystem is modeled and simulated in the appropriate simulation program, potentially on different computers, and intermediate results are communicated over the network during execution time. We discuss different co-simulation approaches and give insights into specific prototypes. Based on the prototypes, we compare the approaches in terms of accuracy, stability and execution time, using a simple case study. We finish with results discussions and recommendations on how to perform co-simulation to maintain the required accuracy of simulation results.1 aTrcka, Marija1 aWetter, Michael1 aHensen, Jan uhttp://www.ibpsa.org/proceedings/BS2007/p503_final.pdf00500nas a2200133 4500008004100000245009200041210006900133260001800202300000800220100001800228700001600246700001600262856008800278 2007 eng d00aComputational fluid dynamics for indoor environment modeling: past, present, and future0 aComputational fluid dynamics for indoor environment modeling pas aSendai, Japan a1-91 aChen, Qingyan1 aZhang, Zhao1 aZuo, Wangda uhttps://simulationresearch.lbl.gov/publications/computational-fluid-dynamics-indoor00514nas a2200133 4500008004100000245007300041210006900114260002800183100002100211700002000232700002100252700002000273856008700293 2007 eng d00aComputer Model of a University Building Using the EnergyPlus Program0 aComputer Model of a University Building Using the EnergyPlus Pro aBeijing, Chinac09/20071 aMonfet, Danielle1 aZmeureanu, Radu1 aCharneux, Roland1 aLemire, Nicolas uhttps://simulationresearch.lbl.gov/publications/computer-model-university-building00471nas a2200109 4500008004100000245011200041210006900153260001200222100001700234700002100251856008900272 2007 eng d00aA convenient coupled simulation method for thermal environment prediction in naturally ventilated buildings0 aconvenient coupled simulation method for thermal environment pre c09/20071 aWang, Liping1 aWong, Nyuk, Hien uhttps://simulationresearch.lbl.gov/publications/convenient-coupled-simulation-method00580nas a2200157 4500008004100000245008000041210006900121260002600190100001800216700001800234700001500252700002000267700002300287700002600310856008600336 2007 eng d00aCoverage Problem for Sensors Embedded in Temperature Sensitive Environments0 aCoverage Problem for Sensors Embedded in Temperature Sensitive E aAnchorage, ALc5/20071 aSen, Arunabha1 aDas, Nibedita1 aZhou, Ling1 aShen, Bao, Hong1 aMurthy, Sudheendra1 aBhattacharya, Prajesh uhttps://simulationresearch.lbl.gov/publications/coverage-problem-sensors-embedded00417nas a2200109 4500008004100000245006400041210006400105260001200169100001700181700002000198856008900218 2007 eng d00aDiscussion of strategies for UK zero energy building design0 aDiscussion of strategies for UK zero energy building design c09/20071 aWang, Liping1 aGwilliam, Julie uhttps://simulationresearch.lbl.gov/publications/discussion-strategies-uk-zero-energy00430nas a2200121 4500008004100000245004800041210004800089260002800137100001900165700001900184700001800203856008700221 2007 eng d00aEconomizer Control Using Mixed Air Enthalpy0 aEconomizer Control Using Mixed Air Enthalpy aSan Francisco, CAc20071 aFeng, Jingjuan1 aLiu, Mingsheng1 aPang, Xiufeng uhttps://simulationresearch.lbl.gov/publications/economizer-control-using-mixed-air00503nas a2200121 4500008004100000245008100041210006900122260002800191100002500219700003100244700002000275856008600295 2007 eng d00aEnergy Index Evaluation of Buildings in Function of the External Temperature0 aEnergy Index Evaluation of Buildings in Function of the External aBeijing, Chinac09/20071 aPapa, Renata, Pietra1 aJota, Patricia, Romeiro da1 aAssis, Eleonora uhttps://simulationresearch.lbl.gov/publications/energy-index-evaluation-buildings00740nas a2200205 4500008004100000245006200041210006200103260007500165100002100240700002400261700001300285700002400298700002100322700002200343700002100365700001400386700002100400700002700421856008600448 2007 eng d00aEnergy Performance of Underfloor Air Distribution Systems0 aEnergy Performance of Underfloor Air Distribution Systems bCalifornia Energy Commission - Public Interest Energy Research Program1 aBauman, Fred, S.1 aWebster, Thomas, L.1 aJin, Hui1 aLukaschek, Wolfgang1 aBenedek, Corinne1 aArens, Edward, A.1 aLinden, Paul, F.1 aLui, Anna1 aBuhl, Walter, F.1 aDickerhoff, Darryl, J. uhttps://simulationresearch.lbl.gov/publications/energy-performance-underfloor-air00518nas a2200145 4500008004100000245009100041210006900132260001200201300001200213490000700225100001700232700002100249700001300270856008900283 2007 eng d00aFacade design optimization for naturally ventilated residential buildings in Singapore0 aFacade design optimization for naturally ventilated residential  c08/2007 a954-9610 v391 aWang, Liping1 aWong, Nyuk, Hien1 aLi, Shuo uhttps://simulationresearch.lbl.gov/publications/facade-design-optimization-naturally00576nas a2200133 4500008004100000245013000041210006900171260002800240100002100268700001900289700002400308700002100332856008900353 2007 eng d00aGlobal Efficiency of Direct Flow Vacuum Collectors in Autonomous Solar Desiccant Cooling: Simulation and Experimental Results0 aGlobal Efficiency of Direct Flow Vacuum Collectors in Autonomous aBeijing, Chinac09/20071 aBourdoukan, Paul1 aWurtz, Etienne1 aSpérandio, Maurice1 aJoubert, Patrice uhttps://simulationresearch.lbl.gov/publications/global-efficiency-direct-flow-vacuum00542nas a2200133 4500008004100000245014400041210006900185260001200254300001400266490000700280100001700287700002100304856008300325 2007 eng d00aThe impacts of facade and ventilation strategies on indoor thermal environment for a naturally ventilated residential building in Singapore0 aimpacts of facade and ventilation strategies on indoor thermal e c12/2007 a4006-40150 v421 aWang, Liping1 aWong, Nyuk, Hien uhttps://simulationresearch.lbl.gov/publications/impacts-facade-and-ventilation00519nas a2200133 4500008004100000245009500041210006900136260002500205100001400230700001900244700001500263700001800278856008900296 2007 eng d00aIntegrated Static Pressure Reset with Fan Air Flow Station in Dual-duct VAV System Control0 aIntegrated Static Pressure Reset with Fan Air Flow Station in Du aLong Beach, CAc20071 aWu, Lixia1 aLiu, Mingsheng1 aWang, Gang1 aPang, Xiufeng uhttps://simulationresearch.lbl.gov/publications/integrated-static-pressure-reset-fan00524nas a2200133 4500008004100000245012700041210006900168260000900237300001200246490000700258100001700265700002100282856008700303 2007 eng d00aInvestigation of the possibility of applying natural ventilation for thermal comfort in residential buildings in Singapore0 aInvestigation of the possibility of applying natural ventilation c2007 a190-1990 v501 aWang, Liping1 aWong, Nyuk, Hien uhttps://simulationresearch.lbl.gov/publications/investigation-possibility-applying00592nas a2200145 4500008004100000245011600041210006900157260002800226100002300254700001700277700002000294700002300314700002200337856008700359 2007 eng d00aPotential of Buried Pipes Systems and Derived Techniques for Passive Cooling of Buildings in Brazilian Climates0 aPotential of Buried Pipes Systems and Derived Techniques for Pas aBeijing, Chinac09/20071 aHollmuller, Pierre1 aCarlo, Joyce1 aOrdenes, Martin1 aWestphal, Fernando1 aLamberts, Roberto uhttps://simulationresearch.lbl.gov/publications/potential-buried-pipes-systems-and00400nas a2200121 4500008004100000245004600041210004600087260001800133300001200151100001600163700001800179856008100197 2007 eng d00aReal time airflow simulation in buildings0 aReal time airflow simulation in buildings aSendai, Japan a459-4661 aZuo, Wangda1 aChen, Qingyan uhttps://simulationresearch.lbl.gov/publications/real-time-airflow-simulation01795nas a2200181 4500008004100000050001500041245009300056210006900149260001200218300001200230490000800242520124800250100001801498700001701516700002001533700001301553856004701566 2007 eng d aLBNL-6097900aA Semi-automated Commissioning Tool for VAV Air Handling Units: Functional Test Analyzer0 aSemiautomated Commissioning Tool for VAV Air Handling Units Func c01/2007 a380-3910 v1133 a

A software tool that automates the analysis of functional tests for air-handling units is described. The tool compares the performance observed during manual tests with the performance predicted by simple models of the components under test that are configured using design information and catalog data. Significant differences between observed and expected performance indicate the presence of faults. Fault diagnosis is performed by analyzing the variation of these differences with operating point using expert rules and fuzzy inferencing.

The tool has a convenient user interface to facilitate manual entry of measurements made during a test. A graphical display compares the measured and expected performance, highlighting significant differences that indicate the presence of faults. The tool is designed to be used by commissioning providers conducting functional tests as part of either new building commissioning or retro-commissioning, as well as by building owners and operators conducting routine tests to check the performance of their HVAC systems. The paper describes the input data requirements of the tool, the software structure, the graphical interface, and summarizes the development and testing process used.

1 aHaves, Philip1 aKim, Moosung1 aNajafi, Massieh1 aXu, Peng uhttp://gaia.lbl.gov/btech/papers/60979.pdf00385nas a2200097 4500008004100000245006100041210005600102260002800158100001500186856008600201 2007 eng d00aA Simplified Hot Water Distribution System Model (DOE-2)0 aSimplified Hot Water Distribution System Model DOE2 aBeijing, Chinac09/20071 aGu, Lixing uhttps://simulationresearch.lbl.gov/publications/simplified-hot-water-distribution00501nas a2200133 4500008004100000245006700041210006700108260002800175100002100203700002400224700002000248700001500268856008400283 2007 eng d00aSimulation Enhanced Prototyping of an Experimental Solar House0 aSimulation Enhanced Prototyping of an Experimental Solar House aBeijing, Chinac09/20071 aChoudhary, Ruchi1 aAugenbroe, Godfried1 aGentry, Russell1 aHu, Huafen uhttps://simulationresearch.lbl.gov/publications/simulation-enhanced-prototyping00465nas a2200121 4500008004100000245005800041210005800099260002800157100002100185700002500206700002300231856008900254 2007 eng d00aSimulation of Energy Management Systems in EnergyPlus0 aSimulation of Energy Management Systems in EnergyPlus aBeijing, Chinac09/20071 aEllis, Peter, G.1 aTorcellini, Paul, A.1 aCrawley, Drury, B. uhttps://simulationresearch.lbl.gov/publications/simulation-energy-management-systems00469nas a2200121 4500008004100000245007900041210006900120260002800189100001600217700001600233700001800249856008000267 2007 eng d00aThe Study of a Simple HVAC Interface of EnergyPlus in the Chinese Language0 aStudy of a Simple HVAC Interface of EnergyPlus in the Chinese La aBeijing, Chinac09/20071 aLiu, Junjie1 aLi, Wenshen1 aZhou, Xiaojie uhttps://simulationresearch.lbl.gov/publications/study-simple-hvac-interface00475nas a2200121 4500008004100000245006500041210006500106260002800171100002300199700001800222700003100240856008200271 2007 eng d00aUse of Simulation Tools for Managing Buildings Energy Demand0 aUse of Simulation Tools for Managing Buildings Energy Demand aBeijing, Chinac09/20071 aHernandez, Alberto1 aNeto, Flávio1 aFiorelli, Augusto, Sanzovo uhttps://simulationresearch.lbl.gov/publications/use-simulation-tools-managing02091nas a2200217 4500008004100000245011800041210006900159260001200228300001200240490000700252520134800259653003201607653003001639653001801669653001501687100002701702700001801729700002101747700002101768856008401789 2007 eng d00aUsing Indicators to Profile Energy Consumption and Inform Energy Policy in a University - A Case Study in Ireland0 aUsing Indicators to Profile Energy Consumption and Inform Energy c08/2007 a913-9220 v393 a

The services sector has the least amount of energy end use data available, which poses significant challenges to companies within the sector attempting to benchmark their energy performance and inform energy management decisions. This paper explores through a case study analysis the use of simple performance indicators and how additional data and new metrics can greatly enhance the understanding of energy trends and in particular the assessment of building energy performance. The country chosen for the analysis is Ireland, where the services sector has experienced high energy demand growth since 1990 (4.1% annually) compared with the EU-15 (1.5% annually). Despite this growth, the available energy data is poor, in particular for the public service sub-sectors. The case study chosen is an institution within the education sub-sector, University College Cork. The paper presents some simple energy performance indicators that have been used to date to inform energy policy. The paper then introduces new approaches and tools for assessing energy performance in buildings and how these may be utilised to improve the energy policy decision making and energy management. It discusses how these approaches are been implemented for buildings with separate functions, presents some initial results and discusses future planned work.

10abuilding energy performance10aEnergy in services sector10aenergy policy10aUniversity1 aGallachóir, Brian, Ó1 aKeane, Marcus1 aMorrissey, Elmer1 aO'Donnell, James uhttps://simulationresearch.lbl.gov/publications/using-indicators-profile-energy00426nas a2200121 4500008004100000245005500041210005500096260001900151300001200170100001600182700001800198856008800216 2007 eng d00aValidation of fast fluid dynamics for room airflow0 aValidation of fast fluid dynamics for room airflow aBeijing, China a980-9831 aZuo, Wangda1 aChen, Qingyan uhttps://simulationresearch.lbl.gov/publications/validation-fast-fluid-dynamics-room00483nas a2200121 4500008004100000245008300041210006900124260002800193100001900221700001800240700001900258856008400277 2007 eng d00aVAV System Optimization through Continuous Commissioning in an Office Building0 aVAV System Optimization through Continuous Commissioning in an O aSan Francisco, CAc20071 aCho, Young-Hum1 aPang, Xiufeng1 aLiu, Mingsheng uhttps://simulationresearch.lbl.gov/publications/vav-system-optimization-through00792nas a2200229 4500008004100000245009200041210006900133300001300202100002900215700001700244700001900261700002000280700001800300700002100318700002200339700001900361700002100380700002300401700003100424700002200455856008500477 2006 eng d00aAdvanced modeling and simulation techniques in MOSILAB: A system development case study0 aAdvanced modeling and simulation techniques in MOSILAB A system  app.63-721 aNytsch-Geusen, Christoph1 aErnst, Thilo1 aSchwarz, Peter1 aVetter, Mathias1 aHolm, Andreas1 aLeopold, Juergen1 aMattes, Alexander1 aNordwig, Andre1 aSchneider, Peter1 aWittwer, Christoph1 aNouidui, Thierry, Stephane1 aSchmidt, Gerhardt uhttps://simulationresearch.lbl.gov/publications/advanced-modeling-and-simulation00486nas a2200109 4500008004100000245010600041210006900147260003200216100001900248700002100267856008800288 2006 eng d00aAn Analysis of Building Envelope Upgrades for Residential Energy Efficiency in Hot and Humid Climates0 aAnalysis of Building Envelope Upgrades for Residential Energy Ef aCambridge, MA, USAc08/20061 aMalhotra, Mini1 aHaberl, Jeff, S. uhttps://simulationresearch.lbl.gov/publications/analysis-building-envelope-upgrades00459nas a2200109 4500008004100000245008100041210006900122260003200191100001700223700002300240856008600263 2006 eng d00aAnalysis Process for Designing Double Skin Facades and Associated Case Study0 aAnalysis Process for Designing Double Skin Facades and Associate aCambridge, MA, USAc08/20061 aDoebber, Ian1 aMcClintock, Maurya uhttps://simulationresearch.lbl.gov/publications/analysis-process-designing-double00535nas a2200133 4500008004100000245011600041210006900157260003200226100001500258700002000273700001300293700001500306856008000321 2006 eng d00aThe Application of Building Energy Simulation and Calibration in Two High-Rise Commercial Buildings in Shanghai0 aApplication of Building Energy Simulation and Calibration in Two aCambridge, MA, USAc08/20061 aPan, Yiqun1 aHuang, Zhizhong1 aWu, Gang1 aChen, Chen uhttps://simulationresearch.lbl.gov/publications/application-building-energy00480nas a2200121 4500008004100000245008900041210006900130260001200199100002400211700002500235700001500260856008300275 2006 eng d00aAssessment of the Technical Potential for Achieving Zero-Energy Commercial Buildings0 aAssessment of the Technical Potential for Achieving ZeroEnergy C c08/20061 aGriffith, Brent, T.1 aTorcellini, Paul, A.1 aRyan, John uhttps://simulationresearch.lbl.gov/publications/assessment-technical-potential00514nas a2200133 4500008004100000245006500041210006500106260003200171100002100203700002400224700001900248700002500267856008800292 2006 eng d00aAutomated Multivariate Optimization Tool for Energy Analysis0 aAutomated Multivariate Optimization Tool for Energy Analysis aCambridge, MA, USAc08/20061 aEllis, Peter, G.1 aGriffith, Brent, T.1 aLong, Nicholas1 aTorcellini, Paul, A. uhttps://simulationresearch.lbl.gov/publications/automated-multivariate-optimization00529nas a2200133 4500008004100000245010800041210006900149300001200218490000800230100002200238700002600260700002400286856008500310 2006 eng d00aBrownian Motion Based Convective- Conductive Model for the Effective Thermal Conductivity of Nanofluids0 aBrownian Motion Based Convective Conductive Model for the Effect a588-5950 v1281 aPrasher, Ravi, S.1 aBhattacharya, Prajesh1 aPhelan, Patrick, E. uhttps://simulationresearch.lbl.gov/publications/brownian-motion-based-convective00625nas a2200169 4500008004100000245009000041210006900131260002500200100002600225700001200251700002400263700002400287700001900311700001600330700002100346856008800367 2006 eng d00aCarbon Nanotube (CNT)-Centric Thermal Management of Future High Power Microprocessors0 aCarbon Nanotube CNTCentric Thermal Management of Future High Pow aAtlanta, GAc03/20061 aBhattacharya, Prajesh1 aWei, X.1 aFedorov, Andrei, G.1 aJoshi, Yogendra, K.1 aBajwa, Navdeep1 aCao, Anyuan1 aAjayan, Pulickel uhttps://simulationresearch.lbl.gov/publications/carbon-nanotube-cnt-centric-thermal00618nas a2200145 4500008004100000245013400041210006900175260002900244100001900273700002900292700002400321700001900345700002300364856008500387 2006 eng d00aA Case Study Demonstrating the Utility of Inter-Program Comparative Testing for Diagnosing Errors in Building Simulation Programs0 aCase Study Demonstrating the Utility of InterProgram Comparative aToronto, Canadac05/20061 aWeber, Andreas1 aBeausoleil-Morrison, Ian1 aGriffith, Brent, T.1 aVesanen, Teemu1 aLerson, Sébastien uhttps://simulationresearch.lbl.gov/publications/case-study-demonstrating-utility00457nas a2200121 4500008004100000245006500041210006500106260002600171100001800197700001300215700001900228856008800247 2006 eng d00aCase Study of Continuous Commissioning in an Office Building0 aCase Study of Continuous Commissioning in an Office Building aShenzhen, Chinac20061 aPang, Xiufeng1 aZheng, B1 aLiu, Mingsheng uhttps://simulationresearch.lbl.gov/publications/case-study-continuous-commissioning00459nas a2200121 4500008004100000024001500041245008600056210006900142490000800211100001300219700001800232856008700250 2006 eng d aLBNL-5864900aCase Study of Demand Shifting with Thermal Mass in Two Large Commercial Buildings0 aCase Study of Demand Shifting with Thermal Mass in Two Large Com0 v1121 aXu, Peng1 aHaves, Philip uhttps://simulationresearch.lbl.gov/publications/case-study-demand-shifting-thermal02020nas a2200265 4500008004100000245010800041210006900149260001200218300001400230490000700244520118600251653003801437653002501475653002401500100002601524700001301550700001601563700001301579700001201592700002401604700002201628700002001650700001301670856007101683 2006 eng d00aCharacterization of the Temperature Oscillation Technique to Measure the Thermal Conductivity of Fluids0 aCharacterization of the Temperature Oscillation Technique to Mea c08/2006 a2950-29560 v493 a

The temperature oscillation technique to measure the thermal diffusivity of a fluid consists of filling a cylindrical volume with the fluid, applying an oscillating temperature boundary condition at the two ends of the cylinder, measuring the amplitude and phase of the temperature oscillation at any point inside the cylinder, and finally calculating the fluid thermal diffusivity from the amplitude and phase values of the temperature oscillations at the ends and at the point inside the cylinder. Although this experimental technique was introduced by Santucci and co-workers nearly two decades ago, its application is still limited, perhaps because of the perceived difficulties in obtaining accurate results. Here, we attempt to clarify this approach by first estimating the maximum size of the liquid’s cylindrical volume, performing a systematic series of experiments to find the allowable amplitude and frequency of the imposed temperature oscillations, and then validating our experimental setup and the characterization method by measuring the thermal conductivity of pure water at different temperatures and comparing our results with previously published work.

10aTemperature oscillation technique10aThermal conductivity10athermal diffusivity1 aBhattacharya, Prajesh1 aNara, S.1 aVijayan, P.1 aTang, T.1 aLai, W.1 aPhelan, Patrick, E.1 aPrasher, Ravi, S.1 aSong, David, W.1 aWang, J. uhttp://www.sciencedirect.com/science/article/pii/S001793100600144X02020nas a2200265 4500008004100000245010800041210006900149260001200218300001400230490000700244520118600251653003801437653002501475653002401500100002601524700001301550700001601563700001301579700001201592700002401604700002201628700002001650700001301670856007101683 2006 eng d00aCharacterization of the Temperature Oscillation Technique to Measure the Thermal Conductivity of Fluids0 aCharacterization of the Temperature Oscillation Technique to Mea c08/2006 a2950-29560 v493 a

The temperature oscillation technique to measure the thermal diffusivity of a fluid consists of filling a cylindrical volume with the fluid, applying an oscillating temperature boundary condition at the two ends of the cylinder, measuring the amplitude and phase of the temperature oscillation at any point inside the cylinder, and finally calculating the fluid thermal diffusivity from the amplitude and phase values of the temperature oscillations at the ends and at the point inside the cylinder. Although this experimental technique was introduced by Santucci and co-workers nearly two decades ago, its application is still limited, perhaps because of the perceived difficulties in obtaining accurate results. Here, we attempt to clarify this approach by first estimating the maximum size of the liquid’s cylindrical volume, performing a systematic series of experiments to find the allowable amplitude and frequency of the imposed temperature oscillations, and then validating our experimental setup and the characterization method by measuring the thermal conductivity of pure water at different temperatures and comparing our results with previously published work.

10aTemperature oscillation technique10aThermal conductivity10athermal diffusivity1 aBhattacharya, Prajesh1 aNara, S.1 aVijayan, P.1 aTang, T.1 aLai, W.1 aPhelan, Patrick, E.1 aPrasher, Ravi, S.1 aSong, David, W.1 aWang, J. uhttp://www.sciencedirect.com/science/article/pii/S001793100600144X00467nas a2200109 4500008004100000245010900041210006900150260001200219100001700231700002100248856008800269 2006 eng d00aCoupling between the CFD simulation and building simulation for better prediction of natural ventilation0 aCoupling between the CFD simulation and building simulation for  c04/20061 aWang, Liping1 aWong, Nyuk, Hien uhttps://simulationresearch.lbl.gov/publications/coupling-between-cfd-simulation-and00467nas a2200109 4500008004100000245011100041210006900152260001200221100001700233700002100250856008600271 2006 eng d00aA coupling method to increase the accuracy of natural ventilation prediction in thermal simulation program0 acoupling method to increase the accuracy of natural ventilation  c04/20061 aWang, Liping1 aWong, Nyuk, Hien uhttps://simulationresearch.lbl.gov/publications/coupling-method-increase-accuracy02129nas a2200157 4500008004100000245011200041210006900153260001600222520154600238100001901784700001601803700002201819700002101841700002101862856008801883 2006 eng d00aDehumidification Enhancement of Direct Expansion Systems through Component Augmentation of the Cooling Coil0 aDehumidification Enhancement of Direct Expansion Systems through aOrlando, FL3 a

Diverse air conditioning products with enhanced dehumidification features are being introduced to meet the increased moisture laden ventilation air requirements of ASHRAE Standard 62 in humid climates. In this evaluation, state point performance spreadsheet models for single path, mixed air packaged systems compare a conventional "off the shelf" direct expansion (DX) cooling system and its performance to systems that augment the DX coil with enhanced dehumidification components, such as heat exchangers and desiccant dehumidifiers. Using common performance metrics for comparisons at ARI rating conditions, these alternative systems define a best practice for enhanced dehumidification performance. The state point performance spreadsheet models combine available algorithms from the EnergyPlus™ simulation program for DX coils and heat exchangers with newly developed algorithms for desiccant dehumidifiers. All the models and their algorithms are applied in EnergyPlus™ for simulations of annual system cooling performance, including sensible and latent loads met, energy consumed, and humidity levels maintained, in select building types and climatic locations. Per this EnergyPlus™ analysis, these enhanced dehumidification systems present challenging decision-making tradeoffs between humidity control improvements over conventional DX systems, condensing (compressor) unit energy consumption reductions versus DX cool and reheat approaches, and fan energy use increases due to the additional component pressure drops.

1 aKosar, Douglas1 aShirey, Don1 aBasarkar, Mangesh1 aSwami, Muthasamy1 aRaustad, Richard uhttps://simulationresearch.lbl.gov/publications/dehumidification-enhancement-direct00665nas a2200169 4500008004100000245010100041210006900142260003600211100001800247700002600265700002700291700001800318700002400336700002400360700002700384856008400411 2006 eng d00aDevelopment of a Model Specification for Performance Monitoring Systems for Commercial Buildings0 aDevelopment of a Model Specification for Performance Monitoring  aPacific Grove, CA, USAc08/20061 aHaves, Philip1 aHitchcock, Robert, J.1 aGillespie, Kenneth, L.1 aBrook, Martha1 aShockman, Christine1 aDeringer, Joseph, J1 aKinney, Kristopher, L. uhttps://simulationresearch.lbl.gov/publications/development-model-specification01770nas a2200181 4500008004100000245010100041210006900142260003900211520111000250100001801360700002601378700002701404700001801431700002401449700002401473700002701497856006401524 2006 eng d00aDevelopment of a Model Specification for Performance Monitoring Systems for Commercial Buildings0 aDevelopment of a Model Specification for Performance Monitoring  aAsilomar, California, USAc08/20063 a

The paper describes the development of a model specification for performance monitoring systems for commercial buildings. The specification focuses on four key aspects of performance monitoring: performance metrics measurement system requirements data acquisition and archiving data visualization and reporting The aim is to assist building owners in specifying the extensions to their control systems that are required to provide building operators with the information needed to operate their buildings more efficiently and to provide automated diagnostic tools with the information required to detect and diagnose faults and problems that degrade energy performance. The paper reviews the potential benefits of performance monitoring, describes the specification guide and discusses briefly the ways in which it could be implemented. A prototype advanced visualization tool is also described, along with its application to performance monitoring. The paper concludes with a description of the ways in which the specification and the visualization tool are being disseminated and deployed.

1 aHaves, Philip1 aHitchcock, Robert, J.1 aGillespie, Kenneth, L.1 aBrook, Martha1 aShockman, Christine1 aDeringer, Joseph, J1 aKinney, Kristopher, L. uhttp://www.aceee.org/proceedings-paper/ss06/panel03/paper1000582nas a2200133 4500008004100000245012900041210006900170260003600239100002000275700002200295700002200317700002200339856008700361 2006 eng d00aDynamic Controls for Energy Efficiency and Demand Response: Framework Concepts and a New Construction Case Study in New York0 aDynamic Controls for Energy Efficiency and Demand Response Frame aPacific Grove, CA, USAc08/20061 aKiliccote, Sila1 aPiette, Mary, Ann1 aWatson, David, S.1 aHughes, Glenn, D. uhttps://simulationresearch.lbl.gov/publications/dynamic-controls-energy-efficiency00533nas a2200133 4500008004100000245010900041210006900150300001400219490000600233100002200239700002600261700002400287856008800311 2006 eng d00aEffect of Aggregation Kinetics on the Thermal Conductivity of Nanoscale Colloidal Solutions (Nanofluids)0 aEffect of Aggregation Kinetics on the Thermal Conductivity of Na a1529-15340 v61 aPrasher, Ravi, S.1 aBhattacharya, Prajesh1 aPhelan, Patrick, E. uhttps://simulationresearch.lbl.gov/publications/effect-aggregation-kinetics-thermal00490nas a2200121 4500008004100000245007500041210006900116260002500185100002200210700002600232700002400258856008600282 2006 eng d00aEffect of Coloidal Chemistry on the Thermal Conductivity of Nanofluids0 aEffect of Coloidal Chemistry on the Thermal Conductivity of Nano aChicago, ILc11/20061 aPrasher, Ravi, S.1 aBhattacharya, Prajesh1 aPhelan, Patrick, E. uhttps://simulationresearch.lbl.gov/publications/effect-coloidal-chemistry-thermal00533nas a2200121 4500008004100000245010300041210006900144260003200213100002700245700002400272700002600296856008900322 2006 eng d00aThe Energy Performance of the Cold-Formed Steel-Frame and Wood-Frame Houses Developed for Thailand0 aEnergy Performance of the ColdFormed SteelFrame and WoodFrame Ho aCambridge, MA, USAc08/20061 aMahattanataw, Prechaya1 aPuvanant, Charunpat1 aMongkolsawat, Darunee uhttps://simulationresearch.lbl.gov/publications/energy-performance-cold-formed-steel01265nas a2200169 4500008004100000245004200041210004200083260001200125300001200137490000600149520075900155100002200914700002600936700002400962700002200986856008701008 2006 eng d00aEnhanced Mass Transport in Nanofluids0 aEnhanced Mass Transport in Nanofluids c03/2006 a419-4230 v63 a

Thermal conductivity enhancement in nanofluids, which are liquids containing suspended nanoparticles, has been attributed to localized convection arising from the nanoparticles' Brownian motion. Because convection and mass transfer are similar processes, the objective here is to visualize dye diffusion in nanofluids. It is observed that dye diffuses faster in nanofluids compared to that in water, with a peak enhancement at a nanoparticle volume fraction, φ, of 0.5%. A possible change in the slope of thermal conductivity enhancement at that same φ signifies that convection becomes less important at higher φ. The enhanced mass transfer in nanofluids can be utilized to improve diffusion in microfluidic devices.

1 aKrishnamurthy, S.1 aBhattacharya, Prajesh1 aPhelan, Patrick, E.1 aPrasher, Ravi, S. uhttps://simulationresearch.lbl.gov/publications/enhanced-mass-transport-nanofluids00436nas a2200097 4500008004100000245009300041210006900134260003200203100001300235856009000248 2006 eng d00aEvaluation of Demand Shifting Strategies With Thermal Mass in Large Commercial Buildings0 aEvaluation of Demand Shifting Strategies With Thermal Mass in La aCambridge, MA, USAc08/20061 aXu, Peng uhttps://simulationresearch.lbl.gov/publications/evaluation-demand-shifting-strategies00517nas a2200109 4500008004100000245013500041210006900176260003200245100001900277700002100296856009000317 2006 eng d00aEvaluation of Methods for Determining Demand-Limiting Setpoint Trajectories in Commercial Buildings Using Short-Term Data Analysis0 aEvaluation of Methods for Determining DemandLimiting Setpoint Tr aCambridge, MA, USAc08/20061 aLee, Kyoung-ho1 aBraun, James, E. uhttps://simulationresearch.lbl.gov/publications/evaluation-methods-determining-demand00546nas a2200121 4500008004100000245012400041210006900165260003200234100002300266700002600289700002300315856008600338 2006 eng d00aExperience Testing EnergyPlus With the IEA HVAC Bestest E300-E545 Series and IEA HVAC Bestest Fuel-Fired Furnace Series0 aExperience Testing EnergyPlus With the IEA HVAC Bestest E300E545 aCambridge, MA, USAc08/20061 aWitte, Michael, J.1 aHenninger, Robert, H.1 aCrawley, Drury, B. uhttps://simulationresearch.lbl.gov/publications/experience-testing-energyplus-iea01826nas a2200157 4500008004100000245010000041210006900141260002800210520122700238100002701465700001801492700002601510700002401536700002701560856008101587 2006 eng d00aA Guide for Specifying Performance Monitoring Systems in Commercial and Institutional Buildings0 aGuide for Specifying Performance Monitoring Systems in Commercia aSan Francisco, CAc20063 a

This paper describes a guide for specifying performance monitoring systems that was developed as part of jointly funded CEC PIER-DOE project intended to assist commercial and institutional building owners in specifying what is required to obtain the information necessary to initiate and sustain an ongoing commissioning activity. The project's goal was to facilitate the delivery of specific performance related information to the benefit of both commissioning providers and building operators. A number of large-building owners were engaged in order to help create 'market pull' for performance monitoring while producing a specification that met their needs. The specification guide and example specification language addresses four key aspects of performance monitoring:

The paper describes key aspects of the guide including how measurement accuracy requirements relate to the performance metrics that are used in both troubleshooting and routine reporting. Guide development activities and related tech-transfer efforts are also presented.

1 aGillespie, Kenneth, L.1 aHaves, Philip1 aHitchcock, Robert, J.1 aDeringer, Joseph, J1 aKinney, Kristopher, L. uhttps://simulationresearch.lbl.gov/publications/guide-specifying-performance00480nas a2200133 4500008004100000245005400041210005400095260003600149100001700185700002000202700002000222700001900242856008500261 2006 eng d00aHalfway to Zero Energy in a Large Office Building0 aHalfway to Zero Energy in a Large Office Building aPacific Grove, CA, USAc08/20061 aHanson, Mark1 aCarlson, Steven1 aSammartano, Dan1 aTaylor, Thomas uhttps://simulationresearch.lbl.gov/publications/halfway-zero-energy-large-office00350nas a2200109 4500008004100000245002900041210002900070260002400099100002200123700002100145856007400166 2006 eng d00aIFC to CONTAM Translator0 aIFC to CONTAM Translator aBoston, MAc08/20061 aBasarkar, Mangesh1 aSwami, Muthasamy uhttps://simulationresearch.lbl.gov/publications/ifc-contam-translator00531nas a2200109 4500008004100000245017300041210006900214260001200283100001700295700002100312856008800333 2006 eng d00aThe impacts of facade designs: orientations, window to wall ratios and shading devices on indoor environment for naturally ventilated residential buildings in Singapore0 aimpacts of facade designs orientations window to wall ratios and c09/20061 aWang, Liping1 aWong, Nyuk, Hien uhttps://simulationresearch.lbl.gov/publications/impacts-facade-designs-orientations00445nas a2200109 4500008004100000245006700041210006700108260003200175100001900207700002400226856008500250 2006 eng d00aImplementation of an Earth Tube System Into EnergyPlus Program0 aImplementation of an Earth Tube System Into EnergyPlus Program aCambridge, MA, USAc08/20061 aLee, Kwang, Ho1 aStrand, Richard, K. uhttps://simulationresearch.lbl.gov/publications/implementation-earth-tube-system00853nas a2200133 4500008004100000245007200041210006900113260001500182520040600197100001300603700001800616700002000634856006500654 2006 eng d00aA Library of HVAC Component Models for use in Automated Diagnostics0 aLibrary of HVAC Component Models for use in Automated Diagnostic aBoston, MA3 a

The paper describes and documents a library of equipment reference models developed for automated fault detection and diagnosis of secondary HVAC system (air handling units and air distribution systems). The models are used to predict the performance that would be expected in the absence of faults. The paper includes a description of the use of automatic documentation methods in the library.

1 aXu, Peng1 aHaves, Philip1 aCurtil, Dimitri uhttp://www.ibpsa.us/pub/simbuild2006/papers/SB06_034_041.pdf00526nas a2200121 4500008004100000245008900041210006900130260003200199100003100231700002700262700002700289856008800316 2006 eng d00aLow Energy Cooling Technologies for Sub-Tropical/Warm Humid Climate Building Systems0 aLow Energy Cooling Technologies for SubTropicalWarm Humid Climat aCambridge, MA, USAc08/20061 aChowdhury, Ashfaque, Ahmed1 aRasul, Mohammad, Golam1 aKamal, Mohammad, Masud uhttps://simulationresearch.lbl.gov/publications/low-energy-cooling-technologies-sub02284nas a2200145 4500008004100000245009700041210006900138260002400207520175000231100001301981700001901994700001702013700001902030856008902049 2006 eng d00aMeasured energy performance of a US-China demonstration energy-efficient commercial building0 aMeasured energy performance of a USChina demonstration energyeff aDallas, TXc01/20073 a

In July 1998, the U.S. Department of Energy (USDOE) and China's Ministry of Science of Technology (MOST) signed a Statement of Work (SOW) to collaborate on the design and construction of an energyefficient demonstration office building and design center to be located in Beijing. The proposed 13,000 m2 (140,000 ft2) nine-story office building would use U.S. energy-efficient materials, space-conditioning systems, controls, and design principles that were judged to be widely replicable throughout China. The SOW stated that China would contribute the land and provide for the costs of the base building, while the U.S. would be responsible for the additional (or marginal) costs associated with the package of energy efficiency andrenewable energy improvements to the building. The project was finished and the building occupied in 2004.

Using DOE-2 to analyze the energy performance of the as-built building, the building obtained 44 out of 69 possible points according to the Leadership in Energy and Environmental Design (LEED) rating, including the full maximum of 10 points in the energy performance section. The building achieved a LEED Gold rating, the first such LEED-rated office building in China, and is 60% more efficient than ASHRAE 90.1-1999. The utility data from the first year's operation match well the analysis results, providing that adjustments are made for unexpected changes in occupancy and operations. Compared with similarly equipped office buildings in Beijing, this demonstration building uses 60% less energy per floor area. However, compared to conventional office buildings with less equipment and window air-conditioners, the building uses slightly more energy per floor area.

1 aXu, Peng1 aHuang, Yu, Joe1 aJin, Ruidong1 aYang, Guoxiong uhttps://simulationresearch.lbl.gov/publications/measured-energy-performance-us-china00530nas a2200109 4500008004100000245014700041210006900188260003200257100002400289700002300313856008400336 2006 eng d00aMethodology for Analyzing the Technical Potential for Energy Performance in the U.S. Commercial Buildings Sector With Detailed Energy Modeling0 aMethodology for Analyzing the Technical Potential for Energy Per aCambridge, MA, USAc08/20061 aGriffith, Brent, T.1 aCrawley, Drury, B. uhttps://simulationresearch.lbl.gov/publications/methodology-analyzing-technical00452nas a2200097 4500008004100000245010000041210006900141260003200210100002400242856008800266 2006 eng d00aA Model for Naturally Ventilated Cavities on the Exteriors of Opaque Building Thermal Envelopes0 aModel for Naturally Ventilated Cavities on the Exteriors of Opaq aCambridge, MA, USAc08/20061 aGriffith, Brent, T. uhttps://simulationresearch.lbl.gov/publications/model-naturally-ventilated-cavities01672nas a2200121 4500008004100000245013600041210006900177260003200246520116000278100002001438700002701458856006501485 2006 eng d00aModelica versus TRNSYS — A Comparison Between an Equation-Based and a Procedural Modeling Language for Building Energy Simulation0 aModelica versus TRNSYS A Comparison Between an EquationBased and aCambridge, MA, USAc08/20063 a

The EnergyPlus building energy simulation software has been tested using the IEA HVAC BESTEST E300-E545 series of tests and the IEA HVAC BESTEST Fuel-Fired test series. The first is a series of comparative tests for a single-zone DX cooling system which tests a program's ability to model hourly loads over an expanded range of performance conditions for various air mixing, infiltration, thermostat set-up, overload conditions, and various economizer control schemes. The second is a series of analytical/semianalytical comparative tests for a single-zone fuel-fired furnace which tests a program's ability to model steady state performance, varying outdoor and indoor conditions, and circulating and draft fan operation. Each of these HVAC BESTEST series were used to test EnergyPlus prior to new public releases. The application of these tests proved to be very useful in several ways: a) revealed algorithmic errors which were fixed, b) revealed algorithmic shortcomings which were improved or eliminated through the use of more rigorous calculations for certain components, and c) caught newly introduced bugs before public release of updates.

1 aWetter, Michael1 aHaugstetter, Christoph uhttp://www.ibpsa.us/pub/simbuild2006/papers/SB06_001_008.pdf00641nas a2200169 4500008004100000020001800041245009600059210007000155260003000225100002900255700001900284700002000303700002300323700003100346700002100377856007300398 2006 eng d a3-934681-45-X00aMOSILAB: Ein Modelica-Simulationswerkzeug zur energetischen Gebäude- und Anlagensimulation0 aMOSILAB Ein ModelicaSimulationswerkzeug zur energetischen Gebäud aBad Staffelstein, Germany1 aNytsch-Geusen, Christoph1 aNordwig, Andre1 aVetter, Mathias1 aWittwer, Christoph1 aNouidui, Thierry, Stephane1 aSchneider, Peter uhttps://simulationresearch.lbl.gov/publications/mosilab-ein-modelica01493nas a2200145 4500008004100000245004000041210004000081260002900121300001200150520103200162653002601194653002201220100002001242856008501262 2006 eng d00aMultizone Airflow Model in Modelica0 aMultizone Airflow Model in Modelica aVienna, Austriac09/2006 a431-4403 a

We present the implementation of a library of multi-zone airflow models in Modelica and a comparative model validation with CONTAM. Our models have a similar level of detail as the models in CONTAM and COMIS. The multizone airflow models allow modeling the flow between rooms through doors, staircases or construction cracks. The flow can be caused by buoyancy effects, such as stack effects in high rise buildings or air temperature imbalance between adjoining rooms, by flow imbalance of a ventilation system, or by wind pressure on the building envelope. The here presented library can be used with a Modelica library for thermal building and HVAC system simulation to compute interzonal air flow rates. The combined use facilitates the integrated design of building systems, which is typically required for analyzing the interaction of room control loops in variable air volume flow systems through open doors, the flow in naturally ventilated buildings and the pressure in elevator shafts caused by stacked effects.

10acontaminant transport10amultizone airflow1 aWetter, Michael uhttps://www.modelica.org/events/modelica2006/Proceedings/sessions/Session413.pdf01390nas a2200121 4500008004100000245007300041210006900114260002800183300001200211520094000223100002001163856008501183 2006 eng d00aMultizone Building Model for Thermal Building Simulation in Modelica0 aMultizone Building Model for Thermal Building Simulation in Mode aVienna, Austriac9/2006 a517-5263 aWe present a room model for thermal building simu- lation that we implemented in Modelica. The room model can be used for controls analysis and energy analysis of one or several rooms that are connected through airflow or heat conduction. The room model can assess energy storage in the air and in the build- ing construction materials, heat transfer between the room and the outside environment and the humidity and CO2 release to the room air. The humidity storage in the building construction materials is not modeled. We also describe a novel separation of heat transfer mechanisms on which our room model is built on. The separation allowed a significant reduction in model de- velopment time, and it allows using state-of-the-art programs for computing prior to the thermal building simulation certain energy flows, such as solar heat gain of an active facade without breaking feedback loops between the HVAC system and the room.1 aWetter, Michael uhttps://www.modelica.org/events/modelica2006/Proceedings/sessions/Session5b4.pdf00513nas a2200109 4500008004100000245015400041210006900195260001200264100001700276700002100293856008900314 2006 eng d00aNatural ventilation simulation by using coupling building simulation and CFD simulation program for accurate prediction of indoor thermal environment0 aNatural ventilation simulation by using coupling building simula c09/20061 aWang, Liping1 aWong, Nyuk, Hien uhttps://simulationresearch.lbl.gov/publications/natural-ventilation-simulation-using00435nas a2200109 4500008004100000245008200041210006900123260001200192100001700204700001400221856009000235 2006 eng d00aA numerical study of Trombe wall for enhancing stack ventilation in buildings0 anumerical study of Trombe wall for enhancing stack ventilation i c09/20061 aWang, Liping1 aLi, Angui uhttps://simulationresearch.lbl.gov/publications/numerical-study-trombe-wall-enhancing00481nas a2200109 4500008004100000245009600041210006900137260003200206100002300238700002100261856008900282 2006 eng d00aPerformance of High-Performance Glazing in IECC Compliant Building Simulation Model (DOE-2)0 aPerformance of HighPerformance Glazing in IECC Compliant Buildin aCambridge, MA, USAc08/20061 aMukhopadhyay, Jaya1 aHaberl, Jeff, S. uhttps://simulationresearch.lbl.gov/publications/performance-high-performance-glazing02402nas a2200145 4500008004100000022001400041245010900055210006900164300001500233490000700248520187300255100001802128700002002146856009002166 2006 eng d a1052-623400aPrecision control for generalized pattern search algorithms with adaptive precision function evaluations0 aPrecision control for generalized pattern search algorithms with a650-669
0 v163 a

In the literature on generalized pattern search algorithms, convergence to a stationary point of a once continuously differentiable cost function is established under the assumption that the cost function can be evaluated exactly. However, there is a large class of engineering problems where the numerical evaluation of the cost function involves the solution of systems of differential algebraic equations. Since the termination criteria of the numerical solvers often depend on the design parameters, computer code for solving these systems usually defines a numerical approximation to the cost function that is discontinuous with respect to the design parameters. Standard generalized pattern search algorithms have been applied heuristically to such problems, but no convergence properties have been stated. In this paper we extend a class of generalized pattern search algorithms to include a subprocedure that adaptively controls the precision of the approximating cost functions. The numerical approximations to the cost function need not define a continuous function. Our algorithms can be used for solving linearly constrained problems with cost functions that are at least locally Lipschitz continuous. Assuming that the cost function is smooth, we prove that our algorithms converge to a stationary point. Under the weaker assumption that the cost function is only locally Lipschitz continuous, we show that our algorithms converge to points at which the Clarke generalized directional derivatives are nonnegative in predefined directions. An important feature of our adaptive precision scheme is the use of coarse approximations in the early iterations, with the approximation precision controlled by a test. We show by numerical experiments that such an approach leads to substantial time savings in minimizing computationally expensive functions.

1 aPolak, Elijah1 aWetter, Michael uhttps://simulationresearch.lbl.gov/publications/precision-control-generalized-pattern00441nas a2200109 4500008004100000245007000041210006900111260003200180100001500212700002000227856008400247 2006 eng d00aRadiant Slab Cooling: A Case Study of Building Energy Performance0 aRadiant Slab Cooling A Case Study of Building Energy Performance aCambridge, MA, USAc08/20061 aTian, Zhen1 aLove, James, A. uhttps://simulationresearch.lbl.gov/publications/radiant-slab-cooling-case-study00516nas a2200121 4500008004100000245010000041210006900141260003200210100002000242700002400262700002300286856008500309 2006 eng d00aSimulation Strategies for Healthcare Design to Achieve Comfort and Optimize Building Energy Use0 aSimulation Strategies for Healthcare Design to Achieve Comfort a aCambridge, MA, USAc08/20061 aNarayan, Shruti1 aLavedrine, Isabelle1 aMcClintock, Maurya uhttps://simulationresearch.lbl.gov/publications/simulation-strategies-healthcare00454nas a2200121 4500008004100000245005700041210005700098260002900155100002100184700001900205700001800224856009000242 2006 eng d00aThermal Performance Simulation of an Atrium Building0 aThermal Performance Simulation of an Atrium Building aToronto, Canadac05/20061 aGöçer, Özgür1 aTavil, Aslihan1 aÖzkan, Ertan uhttps://simulationresearch.lbl.gov/publications/thermal-performance-simulation-atrium00549nas a2200145 4500008004100000245006900041210006800110260003200178100001900210700002100229700002100250700001700271700002600288856008900314 2006 eng d00aUsing EnergyPlus for California Title-24 Compliance Calculations0 aUsing EnergyPlus for California Title24 Compliance Calculations aCambridge, MA, USAc08/20061 aHuang, Yu, Joe1 aBourassa, Norman1 aBuhl, Walter, F.1 aErdem, Ender1 aHitchcock, Robert, J. uhttps://simulationresearch.lbl.gov/publications/using-energyplus-california-title-2401595nas a2200169 4500008004100000050001500041245006900056210006800125260002700193520101300220100001901233700002101252700002101273700001701294700002601311856008801337 2006 eng d aLBNL-6152700aUsing EnergyPlus for California Title-24 compliance calculations0 aUsing EnergyPlus for California Title24 compliance calculations aCambridge, MAc08/20063 a

For the past decade, the non-residential portion of California's Title-24 building energy standard has relied on DOE-2.1E as the reference computer simulation program for development as well as compliance. However, starting in 2004, the California Energy Commission has been evaluating the possible use of EnergyPlus as the reference program in future revisions of Title-24. As part of this evaluation, the authors converted the Alternate Compliance Method (ACM) certification test suite of 150 DOE-2 files to EnergyPlus, and made parallel DOE-2 and EnergyPlus runs for this extensive set of test cases. A customized version of DOE-2.1E named doe2ep was developed to automate the conversion process. This paper describes this conversion process, including the difficulties in establishing an apples-to-apples comparison between the two programs, and summarizes how the DOE-2 and EnergyPlus results compare for the ACM test cases.

1 aHuang, Yu, Joe1 aBourassa, Norman1 aBuhl, Walter, F.1 aErdem, Ender1 aHitchcock, Robert, J. uhttps://simulationresearch.lbl.gov/publications/using-energyplus-california-title-000621nas a2200157 4500008004100000020002200041022001800063245011500081210006900196260002000265300001500285100003100300700002900331700001800360856008500378 2006 eng d a978-3-00-019823-6 a3-00-019823-700aValidierung der eindimensionalen hygrothermischen Wandmodelle der Modelica-Bibliothek "BuildingPhysicsLibrary"0 aValidierung der eindimensionalen hygrothermischen Wandmodelle de aMunich, Germany app.144-1461 aNouidui, Thierry, Stephane1 aNytsch-Geusen, Christoph1 aHolm, Andreas uhttps://simulationresearch.lbl.gov/publications/validierung-der-eindimensionalen00504nas a2200133 4500008004100000245006100041210006000102260003600162100002500198700001800223700001800241700002300259856008800282 2006 eng d00aZero Energy Buildings: A Critical Look at the Definition0 aZero Energy Buildings A Critical Look at the Definition aPacific Grove, CA, USAc08/20061 aTorcellini, Paul, A.1 aPless, Shanti1 aDeru, Michael1 aCrawley, Drury, B. uhttps://simulationresearch.lbl.gov/publications/zero-energy-buildings-critical-look01926nas a2200133 4500008004100000245011300041210006900154300001200223490000700235520142300242100002001665700001801685856008901703 2005 eng d00aBuilding design optimization using a convergent pattern search algorithm with adaptive precision simulations0 aBuilding design optimization using a convergent pattern search a a603-6120 v373 a

We propose a simulation–precision control algorithm that can be used with a family of derivative free optimization algorithms to solve optimization problems in which the cost function is defined through the solutions of a coupled system of differential algebraic equations (DAEs). Our optimization algorithms use coarse precision approximations to the solutions of the DAE system in the early iterations and progressively increase the precision as the optimization approaches a solution. Such schemes often yield a significant reduction in computation time. We assume that the cost function is smooth but that it can only be approximated numerically by approximating cost functions that are discontinuous in the design parameters. We show that this situation is typical for many building energy optimization problems.We present a new building energy and daylighting simulation program, which constructs approximations to the cost function that converge uniformly on bounded sets to a smooth function as precision is increased.We prove that for our simulation program, our optimization algorithms construct sequences of iterates with stationary accumulation points. We present numerical experiments in which we minimize the annual energy consumption of an office building for lighting, cooling and heating. In these examples, our precision control algorithm reduces the computation time up to a factor of four.

1 aWetter, Michael1 aPolak, Elijah uhttps://simulationresearch.lbl.gov/publications/building-design-optimization-using-001529nas a2200145 4500008004100000245009200041210006900133260003100202520097800233100002101211700001801232700002101250700002301271856008901294 2005 eng d00aBuilding Effectiveness Communication Ratios for Improved Building Life Cycle Management0 aBuilding Effectiveness Communication Ratios for Improved Buildin aMontréal, Canadac08/20053 a

Many existing building energy performance assessment frameworks, quantifying and categorising buildings post occupancy, offer limited feedback on design decisions. An environment providing decision makers with pertinent information to assess the consequences of each design decision in a timely, cost effective and practical manner is required to promote viable low-energy solutions from the outset. This paper outlines a performance-based strategy utilising building effectiveness communication ratios stored in Building Information Models (BIM). Decision makers will be capable of rating the building's energy performance throughout its natural life cycle without imposing adverse penalties on facilities located in dissimilar climatic zones subjected to stringent building codes and regulations. With this advancement in building energy assessment in place, a progressive improvement in energy efficiency for the building stock is a feasible and realistic target.

1 aMorrissey, Elmer1 aKeane, Marcus1 aO'Donnell, James1 aMcCarthy, John, F. uhttps://simulationresearch.lbl.gov/publications/building-effectiveness-communication00455nas a2200121 4500008004100000245006400041210006400105260002500169100001800194700001300212700001900225856008900244 2005 eng d00aBuilding Pressure Control in VAV System with Relief Air Fan0 aBuilding Pressure Control in VAV System with Relief Air Fan aPittsburgh, PAc20051 aPang, Xiufeng1 aZheng, B1 aLiu, Mingsheng uhttps://simulationresearch.lbl.gov/publications/building-pressure-control-vav-system02352nas a2200121 4500008004100000245008700041210006900128300001400197490000700211520190900218100002002127856008302147 2005 eng d00aBuildOpt - A new building energy simulation program that is built on smooth models0 aBuildOpt A new building energy simulation program that is built  a1085-10920 v403 a

Building energy simulation programs compute numerical approximations to physical phenomena that can be modeled by a system of differential algebraic equations (DAE). For a large class of building energy analysis problems, one can prove that the DAE system has a unique once continuously differentiable solution. Consequently, if building simulation programs are built on models that satisfy the smoothness assumptions required to prove existence of a unique smooth solution, and if their numerical solvers allow controlling the approximation error, one can use such programs with Generalized Pattern Search optimization algorithms that adaptively control the precision of the solutions of the DAE system. Those optimization algorithms construct sequences of iterates with stationary accumulation points and have been shown to yield a significant reduction in computation time compared to algorithms that use fixed precision cost function evaluations. In this paper, we state the required smoothness assumptions and present the theorems that state existence of a unique smooth solution of the DAE system. We present BuildOpt, a detailed thermal and daylighting building energy simulation program. We discuss examples that explain the smoothing techniques used in BuildOpt. We present numerical experiments that compare the computation time for an annual simulation with the smoothing techniques applied to different parts of the models. The experiments show that high precision approximate solutions can only be computed if smooth models are used. This is significant because today's building simulation programs do not use such smoothing techniques and their solvers frequently fail to obtain a numerical solution if the solver tolerances are tight. We also present how BuildOpt's approximate solutions converge to a smooth function as the precision parameter of the numerical solver is tightened.

1 aWetter, Michael uhttps://simulationresearch.lbl.gov/publications/buildopt-new-building-energy-000481nas a2200121 4500008004100000245006800041210006800109260002500177100002600202700002400228700002200252856008500274 2005 eng d00aComputational Analysis of the Colloidal Stability of Nanofluids0 aComputational Analysis of the Colloidal Stability of Nanofluids aOrlando, FLc11/20051 aBhattacharya, Prajesh1 aPhelan, Patrick, E.1 aPrasher, Ravi, S. uhttps://simulationresearch.lbl.gov/publications/computational-analysis-colloidal00424nas a2200121 4500008004100000245005100041210005100092260002500143100001300168700001900181700001800200856008400218 2005 eng d00aContinuous Commissioning of an Office Building0 aContinuous Commissioning of an Office Building aPittsburgh, PAc20051 aZheng, B1 aLiu, Mingsheng1 aPang, Xiufeng uhttps://simulationresearch.lbl.gov/publications/continuous-commissioning-office00530nas a2200133 4500008004100000245008400041210006900125260003000194100002300224700001800247700002100265700002400286856008600310 2005 eng d00aContrasting the Capabilities of Building Energy Performance Simulation Programs0 aContrasting the Capabilities of Building Energy Performance Simu aMontreal, Canadac08/20051 aCrawley, Drury, B.1 aHand, Jon, W.1 aKummert, Michael1 aGriffith, Brent, T. uhttps://simulationresearch.lbl.gov/publications/contrasting-capabilities-building00511nas a2200121 4500008004100000245008500041210006900126260003000195100003500225700002100260700001800281856009000299 2005 eng d00aDesign of the Natural Ventilation System for the New San Diego Children's Museum0 aDesign of the Natural Ventilation System for the New San Diego C aMontreal, Canadac08/20051 ada Graça, Guilherme, Carrilho1 aLinden, Paul, F.1 aBrook, Martha uhttps://simulationresearch.lbl.gov/publications/design-natural-ventilation-system-new00634nas a2200181 4500008004100000245008100041210006900122260003100191100001600222700002600238700001300264700001200277700002400289700002200313700002000335700001300355856008400368 2005 eng d00aEffect of Particle Material on the Static Thermal Conductivity of Nanofluids0 aEffect of Particle Material on the Static Thermal Conductivity o aSan Francisco, CAc07/20051 aVijayan, P.1 aBhattacharya, Prajesh1 aNara, S.1 aLai, W.1 aPhelan, Patrick, E.1 aPrasher, Ravi, S.1 aSong, David, W.1 aWang, J. uhttps://simulationresearch.lbl.gov/publications/effect-particle-material-static00624nas a2200157 4500008004100000245013600041210007000177260001200247490000700259100002100266700001700287700002600304700002600330700001700356856009300373 2005 eng d00aEffects of double glazed façade on energy consumption, thermal comfort and condensation for a typical office building in Singapore0 aEffects of double glazed façade on energy consumption thermal co c06/20050 v371 aWong, Nyuk, Hien1 aWang, Liping1 aChandra, Aida, Noplie1 aPandey, Anupama, Rana1 aWei, Xiaolin uhttps://simulationresearch.lbl.gov/publications/effects-double-glazed-fa%C3%A7ade-energy01543nas a2200217 4500008004100000020001800041245013200059210006900191260003100260520078000291100001301071700002601084700001601110700001201126700001801138700002401156700002201180700002001202700001701222856008601239 2005 eng d a0-7918-4221-500aExperimental Determination of the Effect of Varying Base Fluid and Temperature on the Static Thermal Conductivity of Nanofluids0 aExperimental Determination of the Effect of Varying Base Fluid a aOrlando, FLbASMEc11/20053 a

The heat transfer abilities of fluids can be improved by adding small particles of sizes of the order of nanometers. Recently a lot of research has been done in evaluating the thermal conductivity of nanofluids using various nanoparticles. In our present work we address this issue by conducting a series of experiments to determine the effective thermal conductivity of alumina-nanofluids by varying the base fluid with water and antifreeze liquids like ethylene glycol and propylene glycol. Temperature oscillation method is used to find the thermal conductivity of the nanofluid. The results show the thermal conductivity enhancement of nanofluids depends on viscosity of the base fluid. Finally the results are validated with a recently proposed theoretical model.

1 aNara, S.1 aBhattacharya, Prajesh1 aVijayan, P.1 aLai, W.1 aRosenthal, W.1 aPhelan, Patrick, E.1 aPrasher, Ravi, S.1 aSong, David, W.1 aWang, Jinlin uhttps://simulationresearch.lbl.gov/publications/experimental-determination-effect00574nas a2200145 4500008004100000020001800041245009000059210006900149260002700218100002900245700003100274700001800305700001900323856008600342 2005 eng d a2-553-01152-000aA hygrothermal building model based on the object-oriented modeling language Modelica0 ahygrothermal building model based on the objectoriented modeling aMontreal, Canadac20051 aNytsch-Geusen, Christoph1 aNouidui, Thierry, Stephane1 aHolm, Andreas1 aHaupt, Wolfram uhttps://simulationresearch.lbl.gov/publications/hygrothermal-building-model-based00496nas a2200109 4500008004100000245014400041210006900185260000900254100001700263700002100280856008500301 2005 eng d00aThe impacts of facade and ventilation strategies on indoor thermal environment for a naturally ventilated residential building in Singapore0 aimpacts of facade and ventilation strategies on indoor thermal e c20051 aWang, Liping1 aWong, Nyuk, Hien uhttps://simulationresearch.lbl.gov/publications/impacts-facade-and-ventilation-001819nas a2200145 4500008004100000245005600041210005600097260003000153520132100183100001801504700002301522700001801545700002201563856008801585 2005 eng d00aImproving the Data Available to Simulation Programs0 aImproving the Data Available to Simulation Programs aMontreal, Canadac08/20053 a

Building performance simulation tools have significantly improved in quality and depth of analysis capability over the past thirty-five years. Yet despite these increased capabilities, simulation programs still depend on user entry for significant data about building components, loads, and other typically scheduled inputs. This often forces users to estimate values or find previously compiled sets of data for these inputs. Often there is little information about how the data were derived, what purposes it is fit for, which standards apply, uncertainty associated with each data field as well as a general description of the data.

A similar problem bedeviled access to weather data and Crawley, Hand, and Lawrie (1999) described a generalized weather data format developed for use with two energy simulation programs which has subsequently lead to a repository which is accessed by thousands of practitioners each year.

This paper describes a generalized format and data documentation for user input—whether it is building envelope components, scheduled loads, or environmental emissions—the widgets upon which all models are dependant. We present several examples of the new input data format including building envelope component, a scheduled occupant load, and environmental emissions.

1 aHand, Jon, W.1 aCrawley, Drury, B.1 aDonn, Michael1 aLawrie, Linda, K. uhttps://simulationresearch.lbl.gov/publications/improving-data-available-simulation00495nas a2200133 4500008004100000024001500041245009500056210006900151490000800220100001300228700001800241700001700259856008500276 2005 eng d aLBNL-5580200aModel-Based Automated Functional Testing-Methodology and Application to Air Handling Units0 aModelBased Automated Functional TestingMethodology and Applicati0 v1111 aXu, Peng1 aHaves, Philip1 aKim, Moosung uhttps://simulationresearch.lbl.gov/publications/model-based-automated-functional00476nas a2200109 4500008004100000245009800041210006900139260003000208100002300238700002000261856008500281 2005 eng d00aModeling Ground Source Heat Pump Systems in a Building Energy Simulation Program (EnergyPlus)0 aModeling Ground Source Heat Pump Systems in a Building Energy Si aMontreal, canadac08/20051 aFisher, Daniel, E.1 aRees, Simon, J. uhttps://simulationresearch.lbl.gov/publications/modeling-ground-source-heat-pump00873nas a2200253 4500008004100000245010600041210006900147260002100216300001500237100002900252700001700281700002100298700002000319700001800339700002100357700001800378700001900396700001900415700002300434700003100457700002200488700002200510856008700532 2005 eng d00aMOSILAB: Development of a modelica based generic simulation tool supporting modal structural dynamics0 aMOSILAB Development of a modelica based generic simulation tool  aHamburg, Germany app.527-5341 aNytsch-Geusen, Christoph1 aErnst, Thilo1 aSchneider, Peter1 aVetter, Mathias1 aHolm, Andreas1 aLeopold, Juergen1 aDoll, Ullrich1 aNordwig, Andre1 aSchwarz, Peter1 aWittwer, Christoph1 aNouidui, Thierry, Stephane1 aSchmidt, Gerhardt1 aMattes, Alexander uhttps://simulationresearch.lbl.gov/publications/mosilab-development-modelica-based00415nas a2200097 4500008004100000245007200041210006900113260003000182100001700212856008800229 2005 eng d00aNatural Ventilation Analysis of an Office Building with Open Atrium0 aNatural Ventilation Analysis of an Office Building with Open Atr aMontreal, canadac08/20051 aMehta, Mohit uhttps://simulationresearch.lbl.gov/publications/natural-ventilation-analysis-office00529nas a2200133 4500008004100000245009100041210006900132260003000201100001900231700001900250700001800269700002000287856008800307 2005 eng d00aParametric Analysis of a Solar Desiccant Cooling System using the SimSPARK Environment0 aParametric Analysis of a Solar Desiccant Cooling System using th aMontreal, Canadac08/20051 aWurtz, Etienne1 aMaalouf, Chadi1 aMora, Laurent1 aAllard, Francis uhttps://simulationresearch.lbl.gov/publications/parametric-analysis-solar-desiccant00530nas a2200133 4500008004100000245008200041210006900123260003000192100002100222700002100243700001800264700002700282856008700309 2005 eng d00aReducing Building Operational Cost Through Environmental Effectiveness Ratios0 aReducing Building Operational Cost Through Environmental Effecti aMontreal, Canadac08/20051 aO'Donnell, James1 aMorrissey, Elmer1 aKeane, Marcus1 aGallachóir, Brian, Ó uhttps://simulationresearch.lbl.gov/publications/reducing-building-operational-cost02109nas a2200157 4500008004100000024001700041050001500058245005600073210005300129260002200182520161100204100001301815700001801828700001701846856008801863 2005 eng d aLBNL/PUB-933 aLBNL-5864800aA Semi-Automated Functional Test Data Analysis Tool0 aSemiAutomated Functional Test Data Analysis Tool aNew York City, NY3 a

The growing interest in commissioning is creating a demand that will increasingly be met by mechanical contractors and less experienced commissioning agents. They will need tools to help them perform commissioning effectively and efficiently. The widespread availability of standardized procedures, accessible in the field, will allow commissioning to be specified with greater certainty as to what will be delivered, enhancing the acceptance and credibility of commissioning. In response, a functional test data analysis tool is being developed to analyze the data collected during functional tests for air-handling units.

The functional test data analysis tool is designed to analyze test data, assess performance of the unit under test and identify the likely causes of the failure. The tool has a convenient user interface to facilitate manual entry of measurements made during a test. A graphical display shows the measured performance versus the expected performance, highlighting significant differences that indicate the unit is not able to pass the test. The tool is described as semi-automated because the measured data need to be entered manually, instead of being passed from the building control system automatically. However, the data analysis and visualization are fully automated. The tool is designed to be used by commissioning providers conducting functional tests as part of either new building commissioning or retro-commissioning, as well as building owners and operators interested in conducting routine tests periodically to check the performance of their HVAC systems.

1 aXu, Peng1 aHaves, Philip1 aKim, Moosung uhttps://simulationresearch.lbl.gov/publications/semi-automated-functional-test-data00405nas a2200109 4500008004100000245004700041210004700088260003000135100002100165700002500186856008400211 2005 eng d00aSimulating Tall Buildings Using EnergyPlus0 aSimulating Tall Buildings Using EnergyPlus aMontreal, Canadac08/20051 aEllis, Peter, G.1 aTorcellini, Paul, A. uhttps://simulationresearch.lbl.gov/publications/simulating-tall-buildings-using01965nas a2200145 4500008004100000050001500041245007800056210006900134260002500203520144600228100001301674700001801687700002401705856009001729 2005 eng d aLBNL-5580100aA Simulation-Based Testing and Training Environment for Building Controls0 aSimulationBased Testing and Training Environment for Building Co aBoulder, COc08/20043 a

A hybrid simulation environment for controls testing and training is described. A real-time simulation of a building and HVAC system is coupled to a real building control system using a hardware interface. A prototype has been constructed and tested in which the dynamic performance of both the HVAC equipment and the building envelope is simulated using SPARK (Simulation Problem Analysis and Research Kernel). A low cost hardware interface between the simulation and the real control system is implemented using plug-in analog-to-digital and digital-to-analog cards in a personal computer. The design and implementation of the hardware interface in SPARK are described. The development of a variant of this environment that uses a derivative of EnergyPlus to test the implementation of a natural ventilation control strategy in real control hardware is also described.

Various applications of the hybrid simulation environment are briefly described, including the development of control algorithms and strategies, control system product testing and the pre-commissioning of building control system installations. The application to the education and training of building operators and HVAC service technicians is discussed in more detail, including the development of a community college curriculum that includes the use of the hybrid simulation environment to teach both control system configuration and HVAC troubleshooting.

1 aXu, Peng1 aHaves, Philip1 aDeringer, Joseph, J uhttps://simulationresearch.lbl.gov/publications/simulation-based-testing-and-training00485nas a2200109 4500008004100000245010800041210006900149260003000218100002200248700001800270856008700288 2005 eng d00aSpecifiction of an IFC-Based Intelligent Graphical User Interface to Support Building Energy Simulation0 aSpecifiction of an IFCBased Intelligent Graphical User Interface aMontreal, Canadac08/20051 aO'Sullivan, Barry1 aKeane, Marcus uhttps://simulationresearch.lbl.gov/publications/specifiction-ifc-based-intelligent00472nas a2200109 4500008004100000245011500041210006900156260000900225100001700234700002100251856009000272 2005 eng d00aThermal analysis of climate environments based on weather data in Singapore for naturally ventilated buildings0 aThermal analysis of climate environments based on weather data i c20051 aWang, Liping1 aWong, Nyuk, Hien uhttps://simulationresearch.lbl.gov/publications/thermal-analysis-climate-environments00465nas a2200121 4500008004100000245007100041210006900112490000700181100002200188700002600210700002400236856008300260 2005 eng d00aThermal Conductivity of Nanoscale Colloidal Solutions (Nanofluids)0 aThermal Conductivity of Nanoscale Colloidal Solutions Nanofluids0 v941 aPrasher, Ravi, S.1 aBhattacharya, Prajesh1 aPhelan, Patrick, E. uhttps://simulationresearch.lbl.gov/publications/thermal-conductivity-nanoscale00977nas a2200133 4500008004100000245002400041210002300065260001700088520061600105100001900721700002200740700001900762856006200781 2005 eng d00aTwo DOE-2 functions0 aTwo DOE2 functions aCanadac20053 aThis paper presents two DOE-2 functions to expand the modeling capability of DOE-2.1E, a popular calculation engine for building energy simulations. The first function models sensible and total heat recovery between outside air and exhaust air, with optional evaporative precooling of exhaust air before the heat recovery. The existing heat recovery of DOE-2 only allows preheating outside air when exhaust air is more than 10°F warmer than outside air. The second function models distributed energy storage for direct expansion air conditioners which cannot be modeled by any existing system type of DOE-2.1E.1 aHong, Tianzhen1 aEley, Charles, N.1 aKolderup, Erik uhttp://www.ibpsa.org/proceedings/BS2005/BS05_0419_426.pdf00374nas a2200121 4500008004100000245002400041210002300065260003000088100001900118700002200137700001900159856007400178 2005 eng d00aTwo DOE-2 Functions0 aTwo DOE2 Functions aMontreal, Canadac08/20051 aHong, Tianzhen1 aEley, Charles, N.1 aKolderup, Erik uhttps://simulationresearch.lbl.gov/publications/two-doe-2-functions-000476nas a2200121 4500008004100000245008500041210006900126260002200195100001300217700001800230700001900248856008700267 2005 eng d00aUsing a Fan Air Flow Station to Control Building Static Pressure in a VAV System0 aUsing a Fan Air Flow Station to Control Building Static Pressure aOrlando, FLc20051 aZheng, B1 aPang, Xiufeng1 aLiu, Mingsheng uhttps://simulationresearch.lbl.gov/publications/using-fan-air-flow-station-control00453nas a2200121 4500008004100000245007400041210006900115300001200184490000700196100002100203700001800224856008900242 2004 eng d00aANN Modeling and Self-tuning Control of the Oil Field Heating Furnace0 aANN Modeling and Selftuning Control of the Oil Field Heating Fur a338-2400 v121 aJiang, Yongcheng1 aPang, Xiufeng uhttps://simulationresearch.lbl.gov/publications/ann-modeling-and-self-tuning-control01573nas a2200217 4500008004100000245009500041210006900136260001200205300001600217490000700233520084100240653001901081653002101100653004601121100002601167700001501193700002001208700002401228700002201252856008101274 2004 eng d00aBrownian Dynamics Simulation to Determine the Effective Thermal Conductivity of Nanofluids0 aBrownian Dynamics Simulation to Determine the Effective Thermal  c06/2004 a6492–64940 v953 a

A nanofluid is a fluid containing suspended solid particles, with sizes on the order of nanometers. Normally, nanofluids have higher thermal conductivities than their base fluids. Therefore, it is of interest to predict the effective thermal conductivity of such a nanofluid under different conditions, especially since only limited experimental data are available. We have developed a technique to compute the effective thermal conductivity of a nanofluid using Brownian dynamics simulation, which has the advantage of being computationally less expensive than molecular dynamics, and have coupled that with the equilibrium Green-Kubo method. By comparing the results of our calculation with the available experimental data, we show that our technique predicts the thermal conductivity of nanofluids to a good level of accuracy.

10acomplex fluids10aDisperse systems10aThermal conduction in nonmetallic liquids1 aBhattacharya, Prajesh1 aSaha, S.K.1 aYadav, Ajay, K.1 aPhelan, Patrick, E.1 aPrasher, Ravi, S. uhttps://simulationresearch.lbl.gov/publications/brownian-dynamics-simulation00513nas a2200133 4500008004100000245011300041210006900154260001200223300001200235490000700247100002000254700001800274856008700292 2004 eng d00aBuilding Design Optimization Using a Convergent Pattern Search Algorithm with Adaptive Precision Simulations0 aBuilding Design Optimization Using a Convergent Pattern Search A c09/2004 a603-6120 v371 aWetter, Michael1 aPolak, Elijah uhttps://simulationresearch.lbl.gov/publications/building-design-optimization-using00461nas a2200121 4500008004100000050001700041245009000058210006900148300001200217490000700229100002300236856008000259 2004 eng d aLBNL/PUB-90500aBuilding energy performance simulation as part of interoperable software environments0 aBuilding energy performance simulation as part of interoperable  a879-8830 v391 aBazjanac, Vladimir uhttps://simulationresearch.lbl.gov/publications/building-energy-performance00455nas a2200121 4500008004100000245009000041210006900131260000900200300001200209490000700221100002300228856008200251 2004 eng d00aBuilding Energy Performance Simulation as Part of Interoperable Software Environments0 aBuilding Energy Performance Simulation as Part of Interoperable  c2004 a879-8830 v391 aBazjanac, Vladimir uhttps://simulationresearch.lbl.gov/publications/building-energy-performance-000508nas a2200133 4500008004100000245006300041210006200104260003600166100002100202700002100223700001800244700002300262856008900285 2004 eng d00aBuildingPI: A Future Tool for Building Life Cycle Analysis0 aBuildingPI A Future Tool for Building Life Cycle Analysis aBoulder, Colorado, USAc08/20041 aO'Donnell, James1 aMorrissey, Elmer1 aKeane, Marcus1 aBazjanac, Vladimir uhttps://simulationresearch.lbl.gov/publications/buildingpi-future-tool-building-life00369nas a2200121 4500008004100000022001500041245003000056210002800086100002000114700001800134700001900152856007600171 2004 eng d aLBNL-5465800aBuildOpt 1.0.1 validation0 aBuildOpt 101 validation1 aWetter, Michael1 aPolak, Elijah1 aCarey, Van, P. uhttps://simulationresearch.lbl.gov/publications/buildopt-101-validation02415nas a2200133 4500008004100000024001500041245008700056210006900143260001200212490000700224520194900231100002002180856008102200 2004 eng d aLBNL-5465700aBuildOpt - A new building energy simulation program that is built on smooth models0 aBuildOpt A new building energy simulation program that is built  c08/20050 v403 a

Building energy simulation programs compute numerical approximations to physical phenomena that can be modeled by a system of differential algebraic equations (DAE). For a large class of building energy analysis problems, one can prove that the DAE system has unique solution that is once continuously differentiable in the building design parameters. Consequently, if building simulation programs are built on models that satisfy the smoothness assumptions required to prove existence of a unique smooth solution, and if their numerical solvers allow controlling the approximation error, one can use such programs with generalized pattern search optimization algorithms that adaptively control the precision of the solutions of the DAE system. Those optimization algorithms construct sequences of iterates with stationary accumulation points and have been shown to yield a significant reduction in computation time compared to algorithms that use fixed precision cost function evaluations. In this paper, we state the required smoothness assumptions and present the theorems that state existence of a unique smooth solution of the DAE system. We present BuildOpt, a detailed thermal and daylighting building energy simulation program. We discuss examples that explain the smoothing techniques used in BuildOpt. We present numerical experiments that compare the computation time for an annual simulation with the smoothing techniques applied to different parts of the models. The experiments show that high precision approximate solutions can only be computed if smooth models are used. This is significant because today's building simulation programs do not use such smoothing techniques and their solvers frequently fail to obtain a numerical solution if the solver tolerances are tight. We also present how BuildOpt's approximate solutions converge to a smooth function as the precision parameter of the numerical solver is tightened.

1 aWetter, Michael uhttps://simulationresearch.lbl.gov/publications/buildopt-new-building-energy00460nas a2200109 4500008004100000245006700041210006500108260003600173100002900209700002300238856008900261 2004 eng d00aComparative Analysis of One-Dimensional Slat-Type Blind Models0 aComparative Analysis of OneDimensional SlatType Blind Models aBoulder, Colorado, USAc08/20041 aChantrasrisalai, Chanvit1 aFisher, Daniel, E. uhttps://simulationresearch.lbl.gov/publications/comparative-analysis-one-dimensional01574nas a2200217 4500008004100000245012300041210006900164260001200233300001200245490000700257520083600264653002201100653001801122653002201140653001901162653001701181653003201198100002001230700002501250856008101275 2004 eng d00aA comparison of deterministic and probabilistic optimization algorithms for nonsmooth simulation-based optimization
0 acomparison of deterministic and probabilistic optimization algor c08/2004 a989-9990 v393 a

In solving optimization problems for building design and control, the cost function is often evaluated using a detailed building simulation program. These programs contain code features that cause the cost function to be discontinuous. Optimization algorithms that require smoothness can fail on such problems. Evaluating the cost function is often so time-consuming that stochastic optimization algorithms are run using only a few simulations, which decreases the probability of getting close to a minimum. To show how applicable direct search, stochastic, and gradient-based optimization algorithms are for solving such optimization problems, we compare the performance of these algorithms in minimizing cost functions with different smoothness. We also explain what causes the large discontinuities in the cost functions.

10acoordinate search10adirect search10agenetic algorithm10ahooke–jeeves10aoptimization10aparticle swarm optimization1 aWetter, Michael1 aWright, Jonathan, A. uhttps://simulationresearch.lbl.gov/publications/comparison-deterministic-and01637nas a2200145 4500008004100000245010400041210006900145260001200214300001200226490000700238520111900245100002001364700001801384856008901402 2004 eng d00aA convergent optimization method using pattern search algorithms with adaptive precision simulation0 aconvergent optimization method using pattern search algorithms w c11/2004 a327-3380 v253 a

Thermal building simulation programs, such as EnergyPlus, compute numerical approximations to solutions of systems of differential algebraic equations. We show that the exact solutions of these systems are usually smooth in the building design parameters, but that the numerical approximations are usually discontinuous due to adaptive solvers and finite precision computations. If such approximate solutions are used in conjunction with optimization algorithms that depend on smoothness of the cost function, one needs to compute high precision solutions, which can be prohibitively expensive if used for all iterations. For such situations, we have developed an adaptive simulation–precision control algorithm that can be used in conjunction with a family of derivative free optimization algorithms. We present the main ingredients of the composite algorithms, we prove that the resulting composite algorithms construct sequences with stationary accumulation points, and we show by numerical experiments that using coarse approximations in the early iterations can significantly reduce computation time.

1 aWetter, Michael1 aPolak, Elijah uhttps://simulationresearch.lbl.gov/publications/convergent-optimization-method-using02088nas a2200157 4500008004100000050001500041245009400056210006900150300001200219490000700231520153000238100003501768700002101803700001801824856008801842 2004 eng d aLBNL-5601000aDesign and Testing of a Control Strategy for a Large Naturally Ventilated Office Building0 aDesign and Testing of a Control Strategy for a Large Naturally V a211-2210 v253 a

The design for the new Federal Building for San Francisco includes an office tower that is to be naturally ventilated. Each floor is designed to be cross-ventilated, through upper windows that are controlled by the building management system. Users have control over lower level windows, which can be as much as 50% of the total openable area. There are significant differences in the performance and the control of the windward and leeward sides of the building, and separate monitoring and control strategies are determined for each side. The performance and control of the building has been designed and tested using a modified version of EnergyPlus. Results from studies with EnergyPlus and computational fluid dynamics are used in designing the control strategy. Wind-driven cross-ventilation produces a main jet through the upper openings of the building, across the ceiling from the windward to the leeward side. Below this jet, the occupied regions are subject to a recirculating airflow. Results show that temperatures within the building are predicted to be satisfactory, provided a suitable control strategy is implemented that uses night cooling in periods of hot weather. The control strategy has 10 window opening modes. EnergyPlus was extended to simulate the effects of these modes, and to assess the effects of different forms of user behaviour. The results show how user behaviour can significantly influence the building performance.

(Note: PDF contains both LBNL-56010 & LBNL-56010 Conf.)

1 ada Graça, Guilherme, Carrilho1 aLinden, Paul, F.1 aHaves, Philip uhttps://simulationresearch.lbl.gov/publications/design-and-testing-control-strategy01971nas a2200157 4500008004100000024001500041245009400056210006900150300001200219490000700231520145700238100003501695700002101730700001801751856004401769 2004 eng d aLBNL-5601000aDesign and Testing of a Control Strategy for a Large Naturally Ventilated Office Building0 aDesign and Testing of a Control Strategy for a Large Naturally V a223-2390 v253 aThe design for the new Federal Building for San Francisco includes an office tower that is to be naturally ventilated. Each floor is designed to be cross-ventilated, through upper windows that are controlled by the building management system. Users have control over lower level windows, which can be as much as 50% of the total openable area. There are significant differences in the performance and the control of the windward and leeward sides of the building, and separate monitoring and control strategies are determined for each side. The performance and control of the building has been designed and tested using a modified version of EnergyPlus. Results from studies with EnergyPlus and computational fluid dynamics are used in designing the control strategy. Wind-driven cross-ventilation produces a main jet through the upper openings of the building, across the ceiling from the windward to the leeward side. Below this jet, the occupied regions are subject to a recirculating airflow. Results show that temperatures within the building are predicted to be satisfactory, provided a suitable control strategy is implemented that uses night cooling in periods of hot weather. The control strategy has 10 window opening modes. EnergyPlus was extended to simulate the effects of these modes, and to assess the effects of different forms of user behaviour. The results show how user behaviour can significantly influence the building performance.1 ada Graça, Guilherme, Carrilho1 aLinden, Paul, F.1 aHaves, Philip uhttp://bse.sagepub.com/content/25/3/22300504nas a2200121 4500008004100000245009000041210006900131260002600200100002600226700002400252700002200276856008400298 2004 eng d00aDetermining the Effective Viscosity of a Nanofluid Using Brownian Dynamics Simulation0 aDetermining the Effective Viscosity of a Nanofluid Using Brownia aHonolulu, HIc03/20041 aBhattacharya, Prajesh1 aPhelan, Patrick, E.1 aPrasher, Ravi, S. uhttps://simulationresearch.lbl.gov/publications/determining-effective-viscosity00572nas a2200169 4500008004100000245006500041210006500106260000900171300001200180490000700192653001500199653004000214100002000254700001900274700002200293856008700315 2004 eng d00aDevelopment of a Thermal Energy Storage Model for EnergyPlus0 aDevelopment of a Thermal Energy Storage Model for EnergyPlus c2004 a807-8140 v3610aenergyplus10athermal energy storage (tes) system1 aIhm, Pyeongchan1 aKrarti, Moncef1 aHenze, Gregor, P. uhttps://simulationresearch.lbl.gov/publications/development-thermal-energy-storage00468nas a2200121 4500008004100000245006200041210006100103260003600164100001900200700002000219700002700239856008000266 2004 eng d00aDevelopment of Trade-Off Equations for EnergyStar Windows0 aDevelopment of TradeOff Equations for EnergyStar Windows aBoulder, Colorado, USAc08/20041 aHuang, Yu, Joe1 aMitchell, Robin1 aSelkowitz, Stephen, E. uhttps://simulationresearch.lbl.gov/publications/development-trade-equations00835nas a2200277 4500008004100000245002600041210002500067260003600092100002300128700002200151700002500173700003000198700002300228700002400251700002400275700002100299700001900320700002600339700001800365700002300383700002100406700002400427700002100451700001500472856007000487 2004 eng d00aEnergyPlus: An Update0 aEnergyPlus An Update aBoulder, Colorado, USAc08/20041 aCrawley, Drury, B.1 aLawrie, Linda, K.1 aPedersen, Curtis, O.1 aWinkelmann, Frederick, C.1 aWitte, Michael, J.1 aStrand, Richard, K.1 aLiesen, Richard, J.1 aBuhl, Walter, F.1 aHuang, Yu, Joe1 aHenninger, Robert, H.1 aGlazer, Jason1 aFisher, Daniel, E.1 aShirley, Don, B.1 aGriffith, Brent, T.1 aEllis, Peter, G.1 aGu, Lixing uhttps://simulationresearch.lbl.gov/publications/energyplus-update00745nas a2200181 4500008004100000245019400041210006900235260002500304100002600329700001600355700001300371700001300384700002400397700002200421700001300443700002000456856008700476 2004 eng d00aEvaluation of the Temperature Oscillation Technique to Calculate Thermal Conductivity of Water and Systematic Measurement of the Thermal Conductivity of Aluminum Oxide – Water Nanofluiids0 aEvaluation of the Temperature Oscillation Technique to Calculate aAnaheim, CAc11/20041 aBhattacharya, Prajesh1 aVijayan, P.1 aTang, T.1 aNara, S.1 aPhelan, Patrick, E.1 aPrasher, Ravi, S.1 aWang, J.1 aSong, David, W. uhttps://simulationresearch.lbl.gov/publications/evaluation-temperature-oscillation00520nas a2200121 4500008004100000245009100041210006900132260003600201100002300237700002600260700002300286856008900309 2004 eng d00aExperience Testing EnergyPlus With the ASHRAE 1052-RP Building Fabric Analytical Tests0 aExperience Testing EnergyPlus With the ASHRAE 1052RP Building Fa aBoulder, Colorado, USAc08/20041 aWitte, Michael, J.1 aHenninger, Robert, H.1 aCrawley, Drury, B. uhttps://simulationresearch.lbl.gov/publications/experience-testing-energyplus-ashrae00337nas a2200097 4500008004100000245003300041210003300074260003600107100002100143856007500164 2004 eng d00aFlow in an Underfloor Plenum0 aFlow in an Underfloor Plenum aBoulder, Colorado, USAc08/20041 aLinden, Paul, F. uhttps://simulationresearch.lbl.gov/publications/flow-underfloor-plenum00484nas a2200121 4500008004100000245010400041210006900145260001200214490000700226100002400233700001800257856008700275 2004 eng d00aFramework for Coupling Room Air Models to Heat Balance Model Load and Energy Calculations (RP-1222)0 aFramework for Coupling Room Air Models to Heat Balance Model Loa c04/20040 v101 aGriffith, Brent, T.1 aChen, Qingyan uhttps://simulationresearch.lbl.gov/publications/framework-coupling-room-air-models01766nas a2200109 4500008004100000022001500041245004800056210004400104520140400148100002001552856008401572 2004 eng d aLBNL-5419900aGenOpt 2.0.0 - Generic optimization program0 aGenOpt 200 Generic optimization program3 a

GenOpt is an optimization program for the minimization of a cost function that is evaluated by an external simulation program. It has been developed for optimization problems where the cost function is computationally expensive and its derivatives are not available or may not even exist. GenOpt can be coupled to any simulation program that reads its input from text files and writes its output to text files. The independent variables can be continuous variables (possibly with lower and upper bounds), discrete variables, or both, continuous and discrete variables. Constraints on dependent variables can be implemented using penalty or barrier functions.

GenOpt has a library with local and global multi-dimensional and one-dimensional optimization algorithms, and algorithms for doing parametric runs. An algorithm interface allows adding new minimization algorithms without knowing the details of the program structure.

GenOpt is written in Java so that it is platform independent. The platform independence and the general interface make GenOpt applicable to a wide range of optimization problems.

GenOpt has not been designed for linear programming problems, quadratic programming problems, and problems where the gradient of the cost function is available. For such problems, as well as for other problems, special tailored software exists that is more efficient.

1 aWetter, Michael uhttps://simulationresearch.lbl.gov/publications/genopt-200-generic-optimization01717nas a2200133 4500008004100000245005400041210005300095260002700148520125500175100002301430700002501453700001801478856008701496 2004 eng d00aGraph-theoretic Methods in Simulation Using SPARK0 aGraphtheoretic Methods in Simulation Using SPARK aArlington, VAc04/20043 aThis paper deals with simulation modeling of nonlinear, deterministic, continuous systems. It describes how the Simulation Problem Analysis and Research Kernel (SPARK) uses the mathematical graph both to describe models of such systems, and to solve the embodied differential-algebraic equation systems (DAEs). Problems are described declaratively rather than algorithmically, with atomic objects representing individual equations and macro objects representing larger programming entities (submodels) in a smooth hierarchy. Internally, in a preprocessing step, graphs are used to represent the problem at the level of equations and variables rather than procedural, multi-equation blocks. Benefits obtained include models that are without predefined input and output sets, enhancing modeling flexibility and code reusability, and relieving the modeler from manual algorithm development. Moreover, graph algorithms are used for problem decomposition and reduction, greatly reducing solution time for wide classes of problems. After describing the methodology the paper presents results of benchmark tests that quantify performance advantages relative to conventional methods. In a somewhat contrived nonlinear example we show O performance as opposed1 aSowell, Edward, F.1 aMoshier, Michael, A.1 aHaves, Philip uhttps://simulationresearch.lbl.gov/publications/graph-theoretic-methods-simulation00495nas a2200133 4500008004100000245005400041210005300095260003800148100002300186700002500209700001800234700002000252856008900272 2004 eng d00aGraph-Theoretic Methods in Simulation Using SPARK0 aGraphTheoretic Methods in Simulation Using SPARK aArlington, Virginia, USAc04/20041 aSowell, Edward, F.1 aMoshier, Michael, A.1 aHaves, Philip1 aCurtil, Dimitri uhttps://simulationresearch.lbl.gov/publications/graph-theoretic-methods-simulation-000502nas a2200133 4500008004100000245009500041210006900136490000600205100001400211700001900225700001700244700001700261856009000278 2004 eng d00aHeat transfer and natural ventilation from single-sided heated solar chimney for buildings0 aHeat transfer and natural ventilation from singlesided heated so0 v31 aLi, Angui1 aJones, Phillip1 aZhao, Pingge1 aWang, Liping uhttps://simulationresearch.lbl.gov/publications/heat-transfer-and-natural-ventilation00480nas a2200109 4500008004100000245009600041210006900137260003600206100002300242700001800265856008700283 2004 eng d00aIFC HVAC Interface to EnergyPlus: A Case of Expanded Interoperability for Energy Simulation0 aIFC HVAC Interface to EnergyPlus A Case of Expanded Interoperabi aBoulder, Colorado, USAc08/20041 aBazjanac, Vladimir1 aMaile, Tobias uhttps://simulationresearch.lbl.gov/publications/ifc-hvac-interface-energyplus-case00501nas a2200121 4500008004100000050001700041245009700058210006900155260002500224100002300249700001800272856008900290 2004 eng d aLBNL/PUB-90700aIFC HVAC interface to EnergyPlus - A case of expanded interoperability for energy simulation0 aIFC HVAC interface to EnergyPlus A case of expanded interoperabi aBoulder, COc08/20041 aBazjanac, Vladimir1 aMaile, Tobias uhttps://simulationresearch.lbl.gov/publications/ifc-hvac-interface-energyplus-case-000479nas a2200109 4500008004100000245009400041210006900135260003600204100001900240700002400259856008600283 2004 eng d00aImprovement of the ASHRAE Secondary HVAC Toolkit Simple Cooling Coil Model for Simulation0 aImprovement of the ASHRAE Secondary HVAC Toolkit Simple Cooling  aBoulder, Colorado, USAc08/20041 aChillar, Rahul1 aLiesen, Richard, J. uhttps://simulationresearch.lbl.gov/publications/improvement-ashrae-secondary-hvac00361nas a2200097 4500008004100000245004000041210003900081260003600120100001900156856008800175 2004 eng d00aNear Real-Time Weather Data Archive0 aNear RealTime Weather Data Archive aBoulder, Colorado, USAc08/20041 aLong, Nicholas uhttps://simulationresearch.lbl.gov/publications/near-real-time-weather-data-archive00439nas a2200109 4500008004100000245009300041210006900134260001200203100001700215700001400232856008300246 2004 eng d00aA numerical study of vertical solar chimney for Enhancing stack ventilation in buildings0 anumerical study of vertical solar chimney for Enhancing stack ve c09/20041 aWang, Liping1 aLi, Angui uhttps://simulationresearch.lbl.gov/publications/numerical-study-vertical-solar00461nas a2200133 4500008004100000245005300041210005200094260001200146100001600158700002400174700002000198700002600218856008300244 2004 eng d00aNumerical Tools For Particle- Fluid Interactions0 aNumerical Tools For Particle Fluid Interactions c02/20041 aCalhoun, R.1 aPhelan, Patrick, E.1 aYadav, Ajay, K.1 aBhattacharya, Prajesh uhttps://simulationresearch.lbl.gov/publications/numerical-tools-particle-fluid02097nas a2200157 4500008003900000245009300039210006900132260003100201520151300232653003401745100001301779700001801792700002201810700002101832856008601853 2004 d00aPeak Demand Reduction from Pre-Cooling with Zone Temperature Reset in an Office Building0 aPeak Demand Reduction from PreCooling with Zone Temperature Rese aPacific Grove, CAc08/20043 a

The objective of this study was to demonstrate the potential for reducing peak-period electrical demand in moderate-weight commercial buildings by modifying the control of the HVAC system. An 80,000 ft2 office building with a medium-weight building structure and high window-to-wall ratio was used for a case study in which zone temperature set-points were adjusted prior to and during occupancy. HVAC performance data and zone temperatures were recorded using the building control system. Additional operative temperature sensors for selected zones and power meters for the chillers and the AHU fans were installed for the study. An energy performance baseline was constructed from data collected during normal operation. Two strategies for demand shifting using the building thermal mass were then programmed in the control system and implemented progressively over a period of one month. It was found that a simple demand limiting strategy performed well in this building. This strategy involved maintaining zone temperatures at the lower end of the comfort region during the occupied period up until 2 pm. Starting at 2 pm, the zone temperatures were allowed to float to the high end of the comfort region. With this strategy, the chiller power was reduced by 80-100% (1 - 2.3 W/ft2) during normal peak hours from 2 - 5 pm, without causing any thermal comfort complaints. The effects on the demand from 2 - 5 pm of the inclusion of pre-cooling prior to occupancy are unclear.

10ademand shifting (pre-cooling)1 aXu, Peng1 aHaves, Philip1 aPiette, Mary, Ann1 aBraun, James, E. uhttps://simulationresearch.lbl.gov/publications/peak-demand-reduction-pre-cooling00466nas a2200109 4500008004100000245008300041210006900124260003500193100002400228700002100252856008300273 2004 eng d00aPhotovoltaic and Solar Thermal Modeling with the EnergyPlus Calculation Engine0 aPhotovoltaic and Solar Thermal Modeling with the EnergyPlus Calc aDenver, Colorado, USAc09/20041 aGriffith, Brent, T.1 aEllis, Peter, G. uhttps://simulationresearch.lbl.gov/publications/photovoltaic-and-solar-thermal00465nas a2200121 4500008004100000245005400041210005400095260003600149100002400185700002400209700002300233856008700256 2004 eng d00aResources for Teaching Building Energy Simulation0 aResources for Teaching Building Energy Simulation aBoulder, Colorado, USAc08/20041 aStrand, Richard, K.1 aLiesen, Richard, J.1 aWitte, Michael, J. uhttps://simulationresearch.lbl.gov/publications/resources-teaching-building-energy00506nas a2200121 4500008004100000245008400041210006900125260003600194100002100230700002400251700002600275856008300301 2004 eng d00aSimulation of Tubular Daylighting Devices and Daylighting Shelves in EnergyPlus0 aSimulation of Tubular Daylighting Devices and Daylighting Shelve aBoulder, Colorado, USAc08/20041 aEllis, Peter, G.1 aStrand, Richard, K.1 aBaumgartner, Kurt, T. uhttps://simulationresearch.lbl.gov/publications/simulation-tubular-daylighting00423nas a2200109 4500008004100000245005000041210004900091260005800140490001000198100002000208856008500228 2004 eng d00aSimulation-Based Building Energy Optimization0 aSimulationBased Building Energy Optimization aBerkeley, CA, USAbUniversity of California, Berkeley0 vPh.D.1 aWetter, Michael uhttps://simulationresearch.lbl.gov/publications/simulation-based-building-energy02585nas a2200109 4500008004100000245005000041210004900091520221100140653001702351100002002368856008702388 2004 eng d00aSimulation-based building energy optimization0 aSimulationbased building energy optimization3 a

This dissertation presents computational techniques for simulation-based design optimization of buildings and heating, ventilation, air-conditioning and lighting systems in which the cost function is smooth. In such problems, the evaluation of the cost function involves the numerical solution of systems of differential algebraic equations (DAE). Since the termination criteria of the iterative solvers often depend on the design parameters, a computer code for solving such systems usually defines a numerical approximation to the cost function that is discontinuous in the design parameters. The discontinuities can be large in cost functions that are evaluated by commercial building energy simulation programs, and optimization algorithms that require smoothness frequently fail if used with such programs. Furthermore, controlling the numerical approximation error is often not possible with commercial building energy simulation programs.

In this dissertation, we present BuildOpt, a new detailed thermal building and daylighting simulation program. BuildOpt's simulation models dene a DAE system that is smooth in the state variables, in time and in the design parameters. This allows proving that the DAE system has a unique solution that is smooth in the design parameters, and it is required to compute high precision approximating cost functions that converge to a cost function that is smooth in the design parameters as the DAE solver tolerance is tightened.

For simulation programs that allow such a precision control, we constructed subprocedures for Generalized Pattern Search (GPS) optimization algorithms that adaptively control the precision of the cost function evaluations: coarse precision for the early iterations,with precision progressively increasing as a stationary point is approached. This scheme significantly reduces the computation time, and it allows to prove that the sequence of iterates contains stationary accumulation points. For optimization problems in which commercial building energy simulation programs are used to evaluate the cost function, we compared by numerical experiment several deterministic and probabilistic optimization algorithms.

10adissertation1 aWetter, Michael uhttps://simulationresearch.lbl.gov/publications/simulation-based-building-energy-001945nas a2200145 4500008004100000024001500041245007800056210006900134260001600203520144200219100001301661700001801674700002401692856008301716 2004 eng d aLBNL-5580100aA simulation-based testing and training environment for building controls0 asimulationbased testing and training environment for building co aBoulder, CO3 a

A hybrid simulation environment for controls testing and training is described. A real-time simulation of a building and HVAC system is coupled to a real building control system using a hardware interface. A prototype has been constructed and tested in which the dynamic performance of both the HVAC equipment and the building envelope is simulated using SPARK (Simulation Problem Analysis and Research Kernel). A low cost hardware interface between the simulation and the real control system is implemented using plug-in analog-to-digital and digital-to-analog cards in a personal computer. The design and implementation of the hardware interface in SPARK are described. The development of a variant of this environment that uses a derivative of EnergyPlus to test the implementation of a natural ventilation control strategy in real control hardware is also described. Various applications of the hybrid simulation environment are briefly described, including the development of control algorithms and strategies, control system product testing and the pre-commissioning of building control system installations. The application to the education and training of building operators and HVAC service technicians is discussed in more detail, including the development of a community college curriculum that includes the use of the hybrid simulation environment to teach both control system configuration and HVAC troubleshooting.

1 aXu, Peng1 aHaves, Philip1 aDeringer, Joseph, J uhttps://simulationresearch.lbl.gov/publications/simulation-based-testing-and-000587nas a2200133 4500008004100000245013700041210006900178260003600247100002100283700002100304700001800325700002300343856008700366 2004 eng d00aSpecification and Implementation of IFC Based Performance Metrics to Support Building Life Cycle Assessment of Hybrid Energy Systems0 aSpecification and Implementation of IFC Based Performance Metric aBoulder, Colorado, USAc08/20041 aMorrissey, Elmer1 aO'Donnell, James1 aKeane, Marcus1 aBazjanac, Vladimir uhttps://simulationresearch.lbl.gov/publications/specification-and-implementation-000605nas a2200145 4500008004100000050001700041245013700058210006900195260002500264100002100289700002100310700001800331700002300349856008700372 2004 eng d aLBNL/PUB-90600aSpecification and Implementation of IFC Based Performance Metrics to Support Building Life Cycle Assessment of Hybrid Energy Systems0 aSpecification and Implementation of IFC Based Performance Metric aBoulder, COc08/20041 aMorrissey, Elmer1 aO'Donnell, James1 aKeane, Marcus1 aBazjanac, Vladimir uhttps://simulationresearch.lbl.gov/publications/specification-and-implementation-100589nas a2200133 4500008004100000245013700041210006900178260003600247100002100283700002100304700001800325700002300343856008900366 2004 eng d00aSpecification and Implementation of IFC-Based Performance Metrics to Support Building Life Cycle Assessment of Hybrid Energy Systems0 aSpecification and Implementation of IFCBased Performance Metrics aBoulder, Colorado, USAc08/20041 aMorrissey, Elmer1 aO'Donnell, James1 aKeane, Marcus1 aBazjanac, Vladimir uhttps://simulationresearch.lbl.gov/publications/specification-and-implementation-ifc00567nas a2200133 4500008004100000245011600041210006900157260003600226100002100262700002100283700001800304700002300322856008800345 2004 eng d00aSpecification of IFC Based Performance Metrics to Support Building Life Cycle Analysis of Hybrid Energy Systems0 aSpecification of IFC Based Performance Metrics to Support Buildi aBoulder, Colorado, USAc08/20041 aMorrissey, Elmer1 aO'Donnell, James1 aKeane, Marcus1 aBazjanac, Vladimir uhttps://simulationresearch.lbl.gov/publications/specification-ifc-based-performance00571nas a2200121 4500008004100000245014700041210006900188260004400257100002400301700001900325700001900344856008600363 2004 eng d00aTransferred Just on Paper? Why Doesn't the Reality of Transferring/Adapting Energy Efficiency Codes and Standards Come Close to the Potential?0 aTransferred Just on Paper Why Doesnt the Reality of Transferring aPacific Grove, California, USAc08/20041 aDeringer, Joseph, J1 aIyer, Maithili1 aHuang, Yu, Joe uhttps://simulationresearch.lbl.gov/publications/transferred-just-paper-why-doesnt00435nas a2200133 4500008004100000245005500041210005500096300001000151490000700161100001600168700001700184700001600201856008400217 2004 eng d00aUpdating traditional CRM system by terminal server0 aUpdating traditional CRM system by terminal server a94-950 v271 aZuo, Wangda1 aYang, Tianyi1 aZou, Wenyan uhttps://simulationresearch.lbl.gov/publications/updating-traditional-crm-system01277nas a2200157 4500008004100000024001500041245008400056210006900140300001200209490000700221520077300228100001801001700002101019700003501040856004401075 2004 eng d aLBNL-5601100aUse of Simulation in the Design of a Large Naturally Ventilated Office Building0 aUse of Simulation in the Design of a Large Naturally Ventilated  a211-2210 v253 aThe design for the new Federal Building for San Francisco includes an office tower that is to be naturally ventilated. The EnergyPlus thermal simulation program was used to evaluate different ventilation strategies for space cooling and rationalize the design of the façade. The strategies include ventilation driven by different combinations of wind, internal stack and external stack. The simulation results indicate that wind-driven ventilation can maintain adequate comfort even during hot periods. Computational fluid dynamics was used to study the airflow and temperature distribution in the occupied spaces arising from different combinations of window openings and outside conditions and thereby inform both the design of the windows and the control strategy.1 aHaves, Philip1 aLinden, Paul, F.1 ada Graça, Guilherme, Carrilho uhttp://bse.sagepub.com/content/25/3/21100443nas a2200109 4500008004100000245006200041210006200103260003600165100002400201700001900225856008900244 2004 eng d00aVariable Heat Recovery in Double Bundle Electric Chillers0 aVariable Heat Recovery in Double Bundle Electric Chillers aBoulder, Colorado, USAc08/20041 aLiesen, Richard, J.1 aChillar, Rahul uhttps://simulationresearch.lbl.gov/publications/variable-heat-recovery-double-bundle01157nas a2200121 4500008004100000050001500041245007900056210006900135260003000204520069600234100002300930856008200953 2004 eng d aLBNL-5607200aVirtual Building Environments - Applying Information Modeling to Buildings0 aVirtual Building Environments Applying Information Modeling to B aIstanbul, Turkeyc09/20043 a

A Virtual Building Environment (VBE) is a place where building industry project staffs can get help in creating Building Information Models (BIM) and in the use of virtual buildings. It consists of a group of industry software that is operated by industry experts who are also experts in the use of that software. The purpose of a VBE is to facilitate expert use of appropriate software applications in conjunction with each other to efficiently support multidisciplinary work. This paper defines BIM and virtual buildings, and describes VBE objectives, set-up and characteristics of operation. It informs about the VBE Initiative and the benefits from a couple of early VBE projects.

1 aBazjanac, Vladimir uhttps://simulationresearch.lbl.gov/publications/virtual-building-environments00431nas a2200121 4500008004100000050001500041245006000056210005700116100001300173700001700186700001800203856008800221 2003 eng d aLBNL-5351200aAn automated functional test and fault detection method0 aautomated functional test and fault detection method1 aXu, Peng1 aKim, Moosung1 aHaves, Philip uhttps://simulationresearch.lbl.gov/publications/automated-functional-test-and-fault02172nas a2200169 4500008004100000245009100041210006900132260002700201300001400228490000800242520160400250100002001854700002501874700002401899700001601923856006301939 2003 eng d00aComparison of a generalized pattern search and a genetic algorithm optimization method0 aComparison of a generalized pattern search and a genetic algorit aEindhoven, Netherlands a1401-14080 vIII3 a

Building and HVAC system design can significantly improve if numerical optimization is used. However, if a cost function that is smooth in the design parameter is evaluated by a building energy simulation program, it usually becomes replaced with a numerical approximation that is discontinuous in the design parameter. Moreover, many building simulation programs do not allow obtaining an error bound for the numerical approximations to the cost function. Thus, if a cost function is evaluated by such a program, optimization algorithms that depend on smoothness of the cost function can fail far from a minimum.

For such problems it is unclear how the Hooke-Jeeves Generalized Pattern Search optimization algorithm and the simple Genetic Algorithm perform. The Hooke-Jeeves algorithm depends on smoothness of the cost function, whereas the simple Genetic Algorithm may not even converge if the cost function is smooth. Therefore, we are interested in how these algorithms perform if used in conjunction with a cost function evaluated by a building energy simulation program.

In this paper we show what can be expected from the two algorithms and compare their performance in minimizing the annual primary energy consumption of an office building in three locations. The problem has 13 design parameters and the cost function has large discontinuities. The optimization algorithms reduce the energy consumption by 7% to 32%, depending on the building location. Given the short labor time to set up the optimization problems, such reductions can yield considerable economic gains.

1 aWetter, Michael1 aWright, Jonathan, A.1 aAugenbroe, Godfried1 aHensen, Jan uhttp://www.ibpsa.org/proceedings/BS2003/BS03_1401_1408.pdf00512nas a2200145 4500008004100000245007700041210006900118300001200187490000700199100001800206700002100224700001800245700001500263856008800278 2003 eng d00aComputer Measurement and Automation System for Gas-fired Heating Furnace0 aComputer Measurement and Automation System for Gasfired Heating  a374-3780 v351 aPang, Xiufeng1 aJiang, Yongcheng1 aMiao, Yan-shu1 aXiong, Jun uhttps://simulationresearch.lbl.gov/publications/computer-measurement-and-automation01634nas a2200241 4500008004100000245010400041210006900145260002700214300001400241490000800255520083600263653002201099653001801121653002201139653001901161653001701180653003201197100002001229700001801249700002401267700001601291856008501307 2003 eng d00aA convergent optimization method using pattern search algorithms with adaptive precision simulation0 aconvergent optimization method using pattern search algorithms w aEindhoven, Netherlands a1393-14000 vIII3 a

In solving optimization problems for building design and control, the cost function is often evaluated using a detailed building simulation program. These programs contain code features that cause the cost function to be discontinuous. Optimization algorithms that require smoothness can fail on such problems. Evaluating the cost function is often so time-consuming that stochastic optimization algorithms are run using only a few simulations, which decreases the probability of getting close to a minimum. To show how applicable direct search, stochastic, and gradient-based optimization algorithms are for solving such optimization problems, we compare the performance of these algorithms in minimizing cost functions with different smoothness. We also explain what causes the large discontinuities in the cost functions.

10acoordinate search10adirect search10agenetic algorithm10ahooke–jeeves10aoptimization10aparticle swarm optimization1 aWetter, Michael1 aPolak, Elijah1 aAugenbroe, Godfried1 aHensen, Jan uhttps://simulationresearch.lbl.gov/publications/convergent-optimization-method-000585nas a2200145 4500008004100000024001500041245009400056210006900150260003600219100003500255700002100290700002000311700001800331856009000349 2003 eng d aLBNL-5601000aDesign and Testing of a Control Strategy for a Large Naturally Ventilated Office Building0 aDesign and Testing of a Control Strategy for a Large Naturally V aEindhoven, Netherlandsc08/20031 ada Graça, Guilherme, Carrilho1 aLinden, Paul, F.1 aMcConahey, Erin1 aHaves, Philip uhttps://simulationresearch.lbl.gov/publications/design-and-testing-control-strategy-100573nas a2200145 4500008004100000245010100041210006900142260002700211100002600238700001500264700002000279700002400299700002200323856008200345 2003 eng d00aDetermining the Effective Thermal Conductivity of a Nanofluid Using Brownian Dynamics Simulation0 aDetermining the Effective Thermal Conductivity of a Nanofluid Us aLas Vegas, NVc07/20031 aBhattacharya, Prajesh1 aSaha, S.K.1 aYadav, Ajay, K.1 aPhelan, Patrick, E.1 aPrasher, Ravi, S. uhttps://simulationresearch.lbl.gov/publications/determining-effective-thermal00504nas a2200133 4500008004100000245008500041210006900126300001200195490000700207100002500214700001800239700002500257856008800282 2003 eng d00aField Testing Model-Based Condition Monitoring on a HVAC Cooling Coil Sub-System0 aField Testing ModelBased Condition Monitoring on a HVAC Cooling  a103-1160 v241 aBuswell, Richard, A.1 aHaves, Philip1 aWright, Jonathan, A. uhttps://simulationresearch.lbl.gov/publications/field-testing-model-based-condition00488nas a2200121 4500008004100000050001700041245008400058210006900142260003600211490000600247100002300253856009000276 2003 eng d aLBNL/PUB-90800aImproving building energy performance simulation with software interoperability0 aImproving building energy performance simulation with software i aEindhoven, Netherlandsc08/20030 v11 aBazjanac, Vladimir uhttps://simulationresearch.lbl.gov/publications/improving-building-energy-performance00408nas a2200109 4500008004100000050001500041245006200056210006200118100001300180700001800193856008700211 2003 eng d aLBNL-5350500aLibrary of component reference models for fault detection0 aLibrary of component reference models for fault detection1 aXu, Peng1 aHaves, Philip uhttps://simulationresearch.lbl.gov/publications/library-component-reference-models00527nas a2200133 4500008004100000245012500041210006900166300001200235490000700247100002100254700001800275700001500293856008500308 2003 eng d00aResearch of ANN Internal Model Self-tuning Control Applied in Combustion Process Control of Heating Furnace in Oil Field0 aResearch of ANN Internal Model Selftuning Control Applied in Com a108-1120 v341 aJiang, Yongcheng1 aPang, Xiufeng1 aFu, Shaobo uhttps://simulationresearch.lbl.gov/publications/research-ann-internal-model-self00537nas a2200133 4500008004100000024001500041245009500056210006900151260003600220100001800256700003500274700002100309856007300330 2003 eng d aLBNL-5601100aUse of Simulation in the Design of a Large Naturally Ventilated Commercial Office Building0 aUse of Simulation in the Design of a Large Naturally Ventilated  aEindhoven, Netherlandsc08/20031 aHaves, Philip1 ada Graça, Guilherme, Carrilho1 aLinden, Paul, F. uhttp://www.inive.org/members_area/medias/pdf/Inive/IBPSA/UFSC912.pdf00410nas a2200121 4500008004100000245003800041210003400079260002500113100001900138700002200157700001900179856009000198 2003 eng d00aVisualDOE – A Green Design Tool0 aVisualDOE A Green Design Tool aBeijing, Chinac20031 aHong, Tianzhen1 aEley, Charles, N.1 aKolderup, Erik uhttps://simulationresearch.lbl.gov/publications/visualdoe-%E2%80%93-green-design-tool01417nas a2200145 4500008004100000245008800041210006900129490000700198520090100205100001901106700001801125700001801143700002201161856008801183 2002 eng d00aOn Approaches to Couple Energy Simulation and Computational Fluid Dynamics Programs0 aApproaches to Couple Energy Simulation and Computational Fluid D0 v373 a

Energy simulation (ES) and computational fluid dynamics (CFD) can play important roles in building design by providing complementary information about the buildings' environmental performance. However, separate applications of ES and CFD are usually unable to give an accurate prediction of building performance due to the assumptions involved in the separate calculations. Integration of ES and CFD eliminates many of these assumptions since the information provided by the models is complementary. Several different approaches to integrating ES and CFD are described. In order to bridge the discontinuities of time-scale, spatial resolution and computing speed between ES and CFD programs, a staged coupling strategy for different problems is proposed. The paper illustrates a typical dynamic coupling process by means of an example implemented using the EnergyPlus and MIT-CFD programs.

1 aZhai, Zhiqiang1 aChen, Qingyan1 aHaves, Philip1 aKlems, Joseph, H. uhttps://simulationresearch.lbl.gov/publications/approaches-couple-energy-simulation01794nas a2200133 4500008004100000245009600041210006900137260003900206520127100245100002101516700001801537700001901555856008601574 2002 eng d00aA Computer Simulation Appraisal of Non-Residential Low Energy Cooling Systems in California0 aComputer Simulation Appraisal of NonResidential Low Energy Cooli aAsilomar, California, USAc08/20023 a

An appraisal of the potential performance of different Low Energy Cooling (LEC) systems in nonresidential buildings in California is being conducted using computer simulation. The paper presents results from the first phase of the study, which addressed the systems that can be modeled, with the DOE-2.1E simulation program.

The following LEC technologies were simulated as variants of a conventional variable-air-volume system with vapor compression cooling and mixing ventilation in the occupied spaces:

Results are presented for four populous climates, represented by Oakland, Sacramento, Pasadena and San Diego. The greatest energy savings are obtained from a combination of displacement ventilation and air-side indirect/direct evaporative pre-cooling. Cool beam systems have the lowest peak demand but do not reduce energy consumption significantly because the reduction in fan energy is offset by a reduction in air-side free cooling. Overall, the results indicate significant opportunities for LEC technologies to reduce energy consumption and demand in non-residential new construction and retrofit.

1 aBourassa, Norman1 aHaves, Philip1 aHuang, Yu, Joe uhttps://simulationresearch.lbl.gov/publications/computer-simulation-appraisal-non01390nas a2200133 4500008004100000024001700041245011000058210006900168260003900237520086100276100001301137700001801150856008801168 2002 eng d aLBNL - 5067800aField Testing of Component-Level Model-Based Fault Detection Methods for Mixing Boxes and VAV Fan Systems0 aField Testing of ComponentLevel ModelBased Fault Detection Metho aAsilomar, California, USAc08/20023 a

An automated fault detection and diagnosis tool for HVAC systems is being developed, based on an integrated, lifecycle, approach to commissioning and performance monitoring. The tool uses component-level HVAC equipment models implemented in the SPARK equation-based simulation environment. The models are configured using design information and component manufacturers' data and then fine-tuned to match the actual performance of the equipment by using data measured during functional tests of the sort using in commissioning. This paper presents the results of field tests of mixing box and VAV fan system models in an experimental facility and a commercial office building. The models were found to be capable of representing the performance of correctly operating mixing box and VAV fan systems and detecting several types of incorrect operation.

1 aXu, Peng1 aHaves, Philip uhttps://simulationresearch.lbl.gov/publications/field-testing-component-level-model01395nas a2200133 4500008004100000050001500041245011000056210006900166260003900235520086600274100001301140700001801153856009001171 2002 eng d aLBNL-5067800aField Testing of Component-Level Model-Based Fault Detection Methods for Mixing Boxes and VAV Fan Systems0 aField Testing of ComponentLevel ModelBased Fault Detection Metho aPacific Grove, Californiac05/20023 a

An automated fault detection and diagnosis tool for HVAC systems is being developed, based on an integrated, life-cycle, approach to commissioning and performance monitoring. The tool uses component-level HVAC equipment models implemented in the SPARK equation-based simulation environment. The models are configured using design information and component manufacturers' data and then fine-tuned to match the actual performance of the equipment by using data measured during functional tests of the sort using in commissioning. This paper presents the results of field tests of mixing box and VAV fan system models in an experimental facility and a commercial office building. The models were found to be capable of representing the performance of correctly operating mixing box and VAV fan systems and detecting several types of incorrect operation.

1 aXu, Peng1 aHaves, Philip uhttps://simulationresearch.lbl.gov/publications/field-testing-component-level-model-001937nas a2200169 4500008004100000024001500041245006700056210006700123260002900190520137000219100002301589700002001612700001801632700001701650700001301667856008701680 2002 eng d aLBNL-5136500aHVAC Component Data Modeling Using Industry Foundation Classes0 aHVAC Component Data Modeling Using Industry Foundation Classes aLiège, Belgiumc12/20023 a

The Industry Foundation Classes (IFC) object data model of buildings is being developed by the International Alliance for Interoperability (IAI). The aim is to support data sharing and exchange in the building and construction industry across the life-cycle of a building.

This paper describes a number of aspects of a major extension of the HVAC part of the IFC data model. First is the introduction of a more generic approach for handling HVAC components. This includes type information, which corresponds to catalog data, occurrence information, which defines item-specific attributes such as location and connectivity, and performance history information, which documents the actual performance of the component instance over time. Other IFC model enhancements include an extension of the connectivity model used to specify how components forming a system can be traversed and the introduction of time-based data streams.

This paper includes examples of models of particular types of HVAC components, such as boilers and actuators, with all attributes included in the definitions. The paper concludes by describing the on-going process of model testing, implementation and integration into the complete IFC model and how the model can be used by software developers to support interoperability between HVAC-oriented design and analysis tools.

1 aBazjanac, Vladimir1 aForester, James1 aHaves, Philip1 aSucic, Darko1 aXu, Peng uhttps://simulationresearch.lbl.gov/publications/hvac-component-data-modeling-using02220nas a2200145 4500008004100000024001700041245013300058210006900191260003900260520164100299100002001940700001801960700001601978856008001994 2002 eng d aLBNL - 5113400aThe Integration of Engineering and Architecture: a Perspective on Natural Ventilation for the new San Francisco Federal Building0 aIntegration of Engineering and Architecture a Perspective on Nat aAsilomar, California, USAc08/20023 a

A description of the in-progress design of a new Federal Office Building for San Francisco is used to illustrate a number of issues arising in the design of large, naturally ventilated office buildings. These issues include the need for an integrated approach to design involving the architects, mechanical and structural engineers, lighting designers and specialist simulation modelers. In particular, the use of natural ventilation, and the avoidance of air-conditioning, depends on the high degree of exposed thermal mass made possible by the structural scheme and by the minimization of solar heat gains while maintaining the good daylighting that results from optimization of the façade. Another issue was the need for a radical change in interior space planning in order to enhance the natural ventilation; all the individual enclosed offices are located along the central spine of each floorplate rather than at the perimeter. The role of integration in deterring the undermining of the design through value engineering is discussed. The comfort criteria for the building were established based on the recent extension to the ASHRAE comfort standard based on the adaptive model for naturally ventilated buildings. The building energy simulation program EnergyPlus was used to compare the performance of different natural ventilation strategies. The results indicate that, in the San Francisco climate, wind-driven ventilation provides sufficient nocturnal cooling to maintain comfortable conditions and that external chimneys do not provide significant additional ventilation at times when it when it would be beneficial.

1 aMcConahey, Erin1 aHaves, Philip1 aChirst, Tim uhttps://simulationresearch.lbl.gov/publications/integration-engineering-and00472nas a2200109 4500008004100000245009400041210006900135260002800204100002600232700002400258856008000282 2002 eng d00aModeling the Behavior of F1-ATPase Biomolecular Motors Using Brownian Dynamics Simulation0 aModeling the Behavior of F1ATPase Biomolecular Motors Using Brow aScottsdale, AZc09/20021 aBhattacharya, Prajesh1 aPhelan, Patrick, E. uhttps://simulationresearch.lbl.gov/publications/modeling-behavior-f1-atpase00551nas a2200133 4500008004100000245010500041210006900146260002900215100002500244700001800269700002200287700002500309856008300334 2002 eng d00aNon-Linear Recursive Parameter Estimation Applied to Fault Detection and Diagnosis in Real Buildings0 aNonLinear Recursive Parameter Estimation Applied to Fault Detect aLiège, Belgiumc12/20021 aBuswell, Richard, A.1 aHaves, Philip1 aSalsbury, Tim, I.1 aWright, Jonathan, A. uhttps://simulationresearch.lbl.gov/publications/non-linear-recursive-parameter00482nas a2200109 4500008004100000245010100041210006900142260002600211100002600237700002400263856008500287 2002 eng d00aUnderstanding the Behavior of an F1-ATPase Biomolecular Motor Using Brownian Dynamics Simulation0 aUnderstanding the Behavior of an F1ATPase Biomolecular Motor Usi aBerkeley, CAc06/20021 aBhattacharya, Prajesh1 aPhelan, Patrick, E. uhttps://simulationresearch.lbl.gov/publications/understanding-behavior-f1-atpase01870nas a2200193 4500008004100000245009500041210006900136260001200205300001200217490000700229520122600236653002801462653002301490653000901513100002201522700002601544700001801570856008801588 2001 eng d00aAnalysis of an Information Monitoring and Diagnostic System to Improve Building Operations0 aAnalysis of an Information Monitoring and Diagnostic System to I c10/2001 a783-7920 v333 a

This paper discusses a demonstration of a technology to address the problem that buildings do not perform as well as anticipated during design. We partnered with an innovative building operator to evaluate a prototype information monitoring and diagnostic system (IMDS). The IMDS consists of a set of high-quality sensors, data acquisition software and hardware, and data visualization software including a web-based remote access system, that can be used to identify control problems and equipment faults. The information system allowed the operators to make more effective use of the building control system and freeing up time to take care of other tenant needs. They report observing significant improvements in building comfort, potentially improving tenant health and productivity. The reduction in the labor costs to operate the building is about US$ 20,000 per year, which alone could pay for the information system in about 5 years. A control system retrofit based on findings from the information system is expected to reduce energy use by 20% over the next year, worth over US$ 30,000 per year in energy cost savings. The operators are recommending that similar technology be adopted in other buildings.

10abuilding control system10abuilding operation10aimds1 aPiette, Mary, Ann1 aKhalsa, Satkartar, T.1 aHaves, Philip uhttps://simulationresearch.lbl.gov/publications/analysis-information-monitoring-and02019nas a2200121 4500008004100000245007200041210006900113260002400182520156300206100002201769700001801791856008801809 2001 eng d00aComparison of Chiller Models for use in Model-Based Fault Detection0 aComparison of Chiller Models for use in ModelBased Fault Detecti aAustin, TXc07/20013 a

Selecting the model is an important and essential step in model based fault detection and diagnosis (FDD). Factors that are considered in evaluating a model include accuracy, training data requirements, calibration effort, generality, and computational requirements. The objective of this study was to evaluate different modeling approaches for their applicability to model based FDD of vapor compression chillers. Three different models were studied: the Gordon and Ng Universal Chiller model (2nd generation) and a modified version of the ASHRAE Primary Toolkit model, which are both based on first principles, and the DOE-2 chiller model, as implemented in CoolToolsTM, which is empirical. The models were compared in terms of their ability to reproduce the observed performance of an older, centrifugal chiller operating in a commercial office building and a newer centrifugal chiller in a laboratory. All three models displayed similar levels of accuracy. Of the first principles models, the Gordon-Ng model has the advantage of being linear in the parameters, which allows more robust parameter estimation methods to be used and facilitates estimation of the uncertainty in the parameter values. The ASHRAE Toolkit Model may have advantages when refrigerant temperature measurements are also available. The DOE-2 model can be expected to have advantages when very limited data are available to calibrate the model, as long as one of the previously identified models in the CoolTools library matches the performance of the chiller in question.

1 aSreedharan, Priya1 aHaves, Philip uhttps://simulationresearch.lbl.gov/publications/comparison-chiller-models-use-model01526nas a2200145 4500008004100000245008300041210006900124260002400193520099600217100002201213700002201235700001501257700001801272856009001290 2001 eng d00aDemand Relief and Weather Sensitivity in Large California Commercial Buildings0 aDemand Relief and Weather Sensitivity in Large California Commer aAustin, TXc07/20013 a

A great deal of research has examined the weather sensitivity of energy consumption in commercial buildings; however, the recent power crisis in California has given greater importance to peak demand. Several new loadshedding programs have been implemented or are under consideration. Historically, the target customers have been large industrial users who can reduce the equivalent load of several large office buildings. While the individual load reduction from an individual office building may be less significant, there is ample opportunity for load reduction in this area. The load reduction programs and incentives for industrial customers may not be suitable for commercial building owners. In particular, industrial customers are likely to have little variation in load from day to day. Thus a robust baseline accounting for weather variability is required to provide building owners with realistic targets that will encourage them to participate in load shedding programs.

1 aKinney, Satkartar1 aPiette, Mary, Ann1 aGu, Lixing1 aHaves, Philip uhttps://simulationresearch.lbl.gov/publications/demand-relief-and-weather-sensitivity02170nas a2200217 4500008004100000245007200041210006900113260001200182300001200194490000700206520147200213653002801685653002901713653003001742653002001772653002001792653001701812100002301829700001801852856008201870 2001 eng d00aEfficient Solution Strategies for Building Energy System Simulation0 aEfficient Solution Strategies for Building Energy System Simulat c04/2001 a309-3170 v333 a

The efficiencies of methods employed in solution of building simulation models are considered and compared by means of benchmark testing. Direct comparisons between the Simulation Problem Analysis and Research Kernel (SPARK) and the HVACSIM+ programs are presented, as are results for SPARK versus conventional and sparse matrix methods. An indirect comparison between SPARK and the IDA program is carried out by solving one of the benchmark test suite problems using the sparse methods employed in that program. The test suite consisted of two problems chosen to span the range of expected performance advantage. SPARK execution times versus problem size are compared to those obtained with conventional and sparse matrix implementations of these problems. Then, to see if the results of these limiting cases extend to actual problems in building simulation, a detailed control system for a heating, ventilating and air conditioning (HVAC) system is simulated with and without the use of SPARK cut set reduction. Execution times for the reduced and non-reduced SPARK models are compared with those for an HVACSIM+ model of the same system. Results show that the graph-theoretic techniques employed in SPARK offer significant speed advantages over the other methods for significantly reducible problems and that by using sparse methods in combination with graph-theoretic methods even problem portions with little reduction potential can be solved efficiently.

10abuilding energy systems10acomputational efficiency10agraph theory applications10ahvac simulation10ahvacsim+ models10aspark models1 aSowell, Edward, F.1 aHaves, Philip uhttps://simulationresearch.lbl.gov/publications/efficient-solution-strategies02364nas a2200169 4500008004100000245004400041210004200085260001900127300001200146490000600158520188400164100002002048700002202068700002602090700001602116856006202132 2001 eng d00aGenOpt - A Generic Optimization Program0 aGenOpt A Generic Optimization Program aRio de Janeiro a601-6080 vI3 a

The potential offered by computer simulation is often not realized: Due to the interaction of system variables, simulation users rarely know how to choose input parameter settings that lead to optimal performance of a given system. Thus, a program called GenOpt® that automatically determines optimal parameter settings has been developed.

GenOpt is a generic optimization program. It minimizes an objective function with respect to multiple parameters. The objective function is evaluated by a simulation program that is iteratively called by GenOpt. In thermal building simulation — which is the main target of GenOpt — the simulation program usually has text-based I/O. The paper shows how GenOpt's simulation program interface allows the coupling of any simulation program with text based I/O by simply editing a configuration file, avoiding code modification of the simulation program. By using object-oriented programming, a high-level interface for adding minimization algorithms to GenOpt's library has been developed. We show how the algorithm interface separates the minimization algorithms and GenOpt's kernel, which allows implementing additional algorithms without being familiar with the kernel or having to recompile it. The algorithms can access utility classes that are commonly used for minimization, such as optimality check, line-search, etc.

GenOpt has successfully solved various optimization problems in thermal building simulation. We show an example of minimizing source energy consumption of an office building using EnergyPlus, and of minimizing auxiliary electric energy of a solar domestic hot water system using TRNSYS. For both examples, the time required to set up the optimization was less than one hour, and the energy savings are about 15%, together with better daylighting usage or lower investment costs, respectively.

1 aWetter, Michael1 aLamberts, Roberto1 aNegrão, Cezar, O. R.1 aHensen, Jan uhttp://www.ibpsa.org/proceedings/BS2001/BS01_0601_608.pdf01389nas a2200229 4500008004100000245009200041210006900133260001200202300001200214490000700226520069500233653002100928653002500949653002900974653001101003653001801014653001601032653001501048100002001063700001801083856005801101 2001 eng d00aA Nodal Model for Displacement Ventilation and Chilled Ceiling Systems in Office Spaces0 aNodal Model for Displacement Ventilation and Chilled Ceiling Sys c07/2001 a753-7620 v363 a

A nodal model has been developed to represent room heat transfer in displacement ventilation and chilled ceiling systems. The model uses precalculated air flow rates to predict the air temperature distribution and the division of the cooling load between the ventilation air and the chilled ceiling. The air movements in the plumes and the rest of the room are represented separately using a network of ten air nodes. The values of the capacity rate parameters are calculated by solving the heat and mass balance equations for each node using measured temperatures as inputs. Correlations between parameter values for a range of cooling loads and supply air flow rates are presented.

10aChilled ceilings10acommercial buildings10aDisplacement ventilation10aenergy10aHeat Transfer10aNodal model10asimulation1 aRees, Simon, J.1 aHaves, Philip uhttp://www.ibpsa.org/proceedings/BS1999/BS99_D-05.pdf01528nas a2200157 4500008004100000245012300041210006900164260001200233300001400245490000700259520097200266100002001238700002301258700001801281856007101299 2001 eng d00aNumerical Investigation of Transient Buoyant Flow in a Room with a Displacement Ventilation and Chilled Ceiling System0 aNumerical Investigation of Transient Buoyant Flow in a Room with c08/2001 a3067-30800 v443 a

The air flow in the office ventilation system known as displacement ventilation is dominated by a gravity current from the inlet and buoyant plumes above internal heat sources. Calculations of the flow and heat transfer in a typical office room have been made for this type of ventilation system used in conjunction with chilled ceiling panels. These calculations have been made in parallel with full size test chamber experiments. It has been found that with higher values of internal load (45 and 72 W m−2 of floor area) the flow becomes quasi-periodic in nature. Complex lateral oscillations are seen in the plumes above the heat sources which impinge on the ceiling and induce significant recirculating flows in the room. The frequency spectra of the transient calculations show good agreement with those of the experimental results. Comparison is also made between calculated mean room air speeds and temperature profiles and measured values.

1 aRees, Simon, J.1 aMcGuirk, James, J.1 aHaves, Philip uhttp://www.sciencedirect.com/science/article/pii/S001793100000348301524nas a2200181 4500008004100000050001500041245009700056210006900153260003600222300001000258490000600268520090100274100001901175700001801194700002201212700001801234856009001252 2001 eng d aLBNL-4828600aStrategies for Coupling Energy Simulation Programs and Computational Fluid Dynamics Programs0 aStrategies for Coupling Energy Simulation Programs and Computati aRio de Janeiro, Brazilc08/2001 a59-660 v13 a

Energy simulation (ES) and computational fluid dynamics (CFD) can play important roles in building design by providing complementary information about the buildings' environmental performance. However, separate applications of ES and CFD are usually unable to give an accurate prediction of building performance due to the assumptions involved in the separate calculations. Integration of ES and CFD eliminates many of these assumptions since the information provided by the models is complementary. Several different approaches to integrating ES and CFD are described. In order to bridge the discontinuities of time-scale, spatial resolution and computing speed between ES and CFD programs, a staged coupling strategy for different problems is proposed. The paper illustrates a typical dynamic coupling process by means of an example implemented using the EnergyPlus and MIT-CFD programs.

1 aZhai, Zhiqiang1 aChen, Qingyan1 aKlems, Joseph, H.1 aHaves, Philip uhttps://simulationresearch.lbl.gov/publications/strategies-coupling-energy-simulation01366nas a2200145 4500008004100000245010700041210006900148260002800217520080900245100001801054700002201072700002001094700001901114856008701133 2001 eng d00aUse of Whole Building Simulation in On-Line Performance Assessment: Modeling and Implementation Issues0 aUse of Whole Building Simulation in OnLine Performance Assessmen aRio de Janeiroc08/20013 a

The application of model-based performance assessment at the whole building level is explored. The information requirements for a simulation to predict the actual performance of a particular real building, as opposed to estimating the impact of design options, are addressed with particular attention to common sources of input error and important deficiencies in most simulation models. The role of calibrated simulations is discussed. The communication requirements for passive monitoring and active testing are identified and the possibilities for using control system communications protocols to link on-line simulation and energy management and control systems are discussed. The potential of simulation programs to act as "plug-and-play" components on building control networks is discussed.

1 aHaves, Philip1 aSalsbury, Tim, I.1 aClaridge, David1 aLiu, Mingsheng uhttps://simulationresearch.lbl.gov/publications/use-whole-building-simulation-line01863nas a2200193 4500008004100000024001500041245007000056210006900126260002800195520122600223100001801449700001901467700001901486700002201505700001601527700001801543700001801561856009001579 2000 eng d aLBNL-4845600aBetter IAQ Through Integrating Design Tools For The HVAC Industry0 aBetter IAQ Through Integrating Design Tools For The HVAC Industr aEspoo, Finlandc08/20003 a

There is currently no effective combination of interoperable design tools to cover all critical aspects of the HVAC design process. Existing design tools are separately available, but require expertise and operating time that is beyond the scope of a normal design project. For example, energy analysis and computational fluid dynamics (CFD) tools are not used in practical design, leading to poor indoor air quality and/or unnecessary energy consumption in buildings.

A prototype integrated software tool for demonstration, process mapping and proof-of-concept purposes was developed under a new international, Finland/USA jointly funded development project BildIT. Individual design tools were simplified and adapted to specific applications and also integrated so that they can be used in a timely and effective manner by the designer. The core of the prototype linked together an architectural CAD system, a 3D space model, a CFD program and a building energy simulation program and it utilises real product data from manufacturer's software. Also the complex building design, construction, maintenance and retrofit processes were mapped to get a template for the structure of the integrated design tool.

1 aLaine, Tuomas1 aKosonen, Risto1 aHagström, Kim1 aMustakallio, Panu1 aYin, De-Wei1 aHaves, Philip1 aChen, Qingyan uhttps://simulationresearch.lbl.gov/publications/better-iaq-through-integrating-design01168nas a2200169 4500008004100000245007600041210006900117260001200186300001200198490000700210520062300217653002400840100001900864700001900883700001500902856008100917 2000 eng d00aBuilding simulation: an overview of development and information sources0 aBuilding simulation an overview of development and information s c05/2000 a347-3610 v353 a

We review the state-of-the-art on the development and application of computer-aided building simulation by addressing some crucial questions in the field. Although the answers are not intended to be comprehensive, they are sufficiently varied to provide an overview ranging from the historical and technical development to choosing a suitable simulation program and performing building simulation. Popular icons of major interested agencies and simulation tools and key information sources are highlighted. Future trends in the design and operation of energy-efficient ‘green' buildings are briefly described.

10abuilding simulation1 aHong, Tianzhen1 aChou, Siaw, K.1 aBong, T.Y. uhttps://simulationresearch.lbl.gov/publications/building-simulation-overview01273nas a2200145 4500008004100000245013200041210006900173490000700242520074700249100002000996700002501016700002401041700001801065856004401083 2000 eng d00aComparison of Peak Load Predictions and Treatment of Solar Gains in the Admittance and Heat Balance Load Calculation Procedures0 aComparison of Peak Load Predictions and Treatment of Solar Gains0 v213 aCalculation of design cooling loads is of critical concern to designers of HVAC systems. The work reported here has been carried out under a joint ASHRAE-CIBSE research project to compare design cooling calculation methods. Peak cooling loads predicted by the ASHRAE heat balance method are compared with those predicted by a number of implementations of the admittance method using different window models. The results presented show the general trends in overprediction or underprediction of peak load. Particular attention is given to different window modelling practices. The performance of the methods is explained in terms of some of the underlying assumptions in the window models, and by reference to specific inter-model comparisons.1 aRees, Simon, J.1 aSpitler, Jeffrey, D.1 aHolmes, Michael, J.1 aHaves, Philip uhttp://bse.sagepub.com/content/21/2/12501872nas a2200133 4500008004100000024001500041245009200056210006900148260003900217520135100256100001801607700002601625856008701651 2000 eng d aLBNL-4594900aModel-based Performance Monitoring: Review of Diagnostic Methods and Chiller Case Study0 aModelbased Performance Monitoring Review of Diagnostic Methods a aAsilomar, California, USAc08/20003 a

The paper commences by reviewing the variety of technical approaches to the problem of detecting and diagnosing faulty operation in order to improve the actual performance of buildings. The review covers manual and automated methods, active testing and passive monitoring, the different classes of models used in fault detection, and methods of diagnosis. The process of model-based fault detection is then illustrated by describing the use of relatively simple empirical models of chiller energy performance to monitor equipment degradation and control problems. The CoolTools™ chiller model identification package is used to fit the DOE-2 chiller model to on-site measurements from a building instrumented with high quality sensors. The need for simple algorithms to reject transient data, detect power surges and identify control problems is discussed, as is the use of energy balance checks to detect sensor problems. The accuracy with which the chiller model can be expected to predict performance is assessed from the goodness of fit obtained and the implications for fault detection sensitivity and sensor accuracy requirements are discussed. A case study is described in which the model was applied retroactively to high-quality data collected in a San Francisco office building as part of a related project (Piette et al. 1999).

1 aHaves, Philip1 aKhalsa, Satkartar, T. uhttps://simulationresearch.lbl.gov/publications/model-based-performance-monitoring01529nas a2200157 4500008004100000245009000041210006900131300001000200490000600210520097900216100002001195700002501215700002301240700001801263856009001281 2000 eng d00aQualitative Comparison of North American and U.K. Cooling Load Calculation Procedures0 aQualitative Comparison of North American and UK Cooling Load Cal a75-990 v63 a

A qualitative comparison is presented between three current North American and U.K. design cooling load calculation methods. The methods compared are the ASHRAE Heat Balance Method, the Radiant Time Series Method and the Admittance Method, used in the U.K. The methods are compared and contrasted in terms of their overall structure. In order to generate the values of the 24 hourly cooling loads, comparison was also made in terms of the processing of the input data and the solution of the equations required. Specific comparisons are made between the approximations used by the three calculation methods to model some of the principal heat transfer mechanisms. Conclusions are drawn regarding the ability of the simplified methods to correctly predict peak-cooling loads compared to the Heat Balance Method predictions. Comment is also made on the potential for developing similar approaches to cooling load calculation in the U.K. and North America in the future.

1 aRees, Simon, J.1 aSpitler, Jeffrey, D.1 aDavies, Morris, G.1 aHaves, Philip uhttps://simulationresearch.lbl.gov/publications/qualitative-comparison-north-american01940nas a2200133 4500008004100000245010000041210006900141260001200210520147600222100002201698700002601720700001801746856004201764 2000 eng d00aUse of an Information Monitoring and Diagnostic System for Commissioning and Ongoing Operations0 aUse of an Information Monitoring and Diagnostic System for Commi c05/20003 aThis paper discusses a demonstration of a technology to address the problem that buildings do not perform as well as anticipated during design. We partnered with an innovative building operator to evaluate a prototype Information Monitoring and Diagnostic System (IMDS). The IMDS consists of a set of high-quality sensors, data acquisition software and hardware, and data visualization software, including a web-based remote access system that can be used to identify control problems and equipment faults. The IMDS allowed the operators to make more effective use of the control system, freeing up time to take care of other tenant needs. The operators report observing significant improvements in building comfort, potentially improving tenant health and productivity. Reduction in hours to operate the building are worth about $20,000 per year, which alone could pay for the IMDS in about five years. A control system retrofit based on findings from the IMDS is expected to reduce energy use by 20 percent over the next year, worth over $30,000 per year in energy cost savings. The operators recommend that similar technology be adopted in other buildings. While the current IMDS is oriented toward manual, human-based diagnostic techniques, we also evaluated automated diagnostic techniques. Strategies for utilizing results from this demonstration to influence commercial building performance monitoring for commissioning and operations will be discussed. Background1 aPiette, Mary, Ann1 aKhalsa, Satkartar, T.1 aHaves, Philip uhttp://imds.lbl.gov/pubs/paper383.pdf01723nas a2200217 4500008004100000245005700041210005500098260001200153300001200165490000700177520108800184653002401272653001501296653001001311653002601321653001701347100001901364700001901383700001501402856008801417 1999 eng d00aA design day for building load and energy estimation0 adesign day for building load and energy estimation c07/1999 a469-4770 v343 a

We describe how a design day for building energy performance simulation can be selected from a typical meteorological year of a location. The advantages of the design day weather file are its simplicity and flexibility in use with simulation programs. The design day is selected using a weather parameter comprising the daily average dry bulb temperature and total solar insolation. The selection criterion addresses the balance between the need to minimise the part-load performance of the air-conditioning systems and plants and the number of hours of load not met. To validate the versatility of the design day weather file, we compare simulation results of the peak load and load profile of a building obtained from the DOE-2.1E code and a specially developed load estimation program, PEAKLOAD. PEAKLOAD is developed using the transfer function method and ASHRAE databases. Comparative results are in good agreement, indicating that a design day thus selected can be used when quick answers are required and simulations using a TMY file cannot be easily done or justified.

10abuilding simulation10adesign day10adoe-210apeak load calculation10aweather data1 aHong, Tianzhen1 aChou, Siaw, K.1 aBong, T.Y. uhttps://simulationresearch.lbl.gov/publications/design-day-building-load-and-energy01143nas a2200121 4500008004100000245009200041210006900133260002600202520069700228100002000925700001800945856005800963 1999 eng d00aA Nodal Model for Displacement Ventilation and Chilled Ceiling Systems in Office Spaces0 aNodal Model for Displacement Ventilation and Chilled Ceiling Sys aKyoto, Japanc09/19993 a

A nodal model has been developed to represent room heat transfer in displacement ventilation and chilled ceiling systems. The model uses precalculated air flow rates to predict the air temperature distribution and the division of the cooling load between the ventilation air and the chilled ceiling. The air movements in the plumes and the rest of the room are rep- resented separately using a network of ten air nodes. The values of the capacity rate parameters are calculated by solving the heat and mass balance equations for each node using measured temperatures as inputs. Correlations between parameter values for a range of cooling loads and supply air flow rates are presented.

1 aRees, Simon, J.1 aHaves, Philip uhttp://www.ibpsa.org/proceedings/BS1999/BS99_D-05.pdf02073nas a2200121 4500008004100000245007100041210006900112260002600181520164500207100002301852700001801875856005801893 1999 eng d00aNumerical Performance of a Graph-Theoretic HVAC Simulation Program0 aNumerical Performance of a GraphTheoretic HVAC Simulation Progra aKyoto, Japanc09/19993 aThe Simulation Problem Analysis and Research Kernel (SPARK) uses graph-theoretic techniques to match equations to variables and build computational graphs, yielding solution sequences indicated by needed data flow. Additionally, the problem graph is decomposed into strongly connected components, thus reducing the size of simultaneous equation sets, and small cut sets are determined, thereby reducing the number of iteration variables needed to solve each equation set. The improvement in computational efficiency produced by this graph theoretic preprocessing depends on the nature of the problem. The paper explores the improvement one might expect in practice in three ways. First, two problems chosen to span the range of performance are studied and some of the factors determining the performance are identified and discussed. The problem selected to exhibit a large improvement consists of a set of sparsely coupled non-linear equations. The problem selected to represent the other end of the performance spectrum is a set of equations obtained by discretizing Laplace's equation in two dimensions, e.g. a heat conduction problem. Execution time versus problem size is compared to that obtained with sparse matrix implementations of the same problems. Then, to see if the results of these somewhat contrived limiting cases extend to actual problems in building simulation, a detailed control system model of a six- zone VAV HVAC system is simulated with and without the use of cut set reduction. Execution times are compared between the reduced and non-reduced SPARK models, and with those from an HVACSIM+ model of the same system.1 aSowell, Edward, F.1 aHaves, Philip uhttp://www.ibpsa.org/proceedings/BS1999/BS99_A-05.pdf00515nas a2200121 4500008004100000245012500041210006900166260001900235300001600254100001800270700002300288856008200311 1998 eng d00aThe application of Problem Reduction Techniques Based on Graph Theory to the Simulation of Non-Linear Continuous Systems0 aapplication of Problem Reduction Techniques Based on Graph Theor aManchester, UK app. 203-2071 aHaves, Philip1 aSowell, Edward, F. uhttps://simulationresearch.lbl.gov/publications/application-problem-reduction01646nas a2200145 4500008004100000245009200041210006900133300001000202490000800212520113200220100002501352700002001377700001801397856008501415 1998 eng d00aComparison of North American and U.K. Cooling Load Calculation Procedures - Methodology0 aComparison of North American and UK Cooling Load Calculation Pro a47-610 v1043 aThis paper describes the methodology used in a quanti- tative comparison between the current North American and United Kingdom cooling load calculation methods. Three calculation methods have been tested as part of a joint ASHRAE/CIBSE research project: the ASHRAE heat balance method and radiant time series method and the admittance method, used in the U.K. A companion paper (Rees et al.1998) describes the results of the study. The quantitative comparison is primarily organized as a parametric study—each building zone/weather day combination compared may be thought of as a combination of various parameters, e.g., exterior wall type, roof type, glazing area, etc. Specifically, this paper describes the overall organization of the study, the parameters and parameter levels that can be varied, and the tools developed to create input files, automate the load calculations, and extract the results. A brief descrip- tion of the cooling load calculation procedure implementa- tions is also given. The methodology presented and the tools described could also be used to make comparisons between other calculation methods.1 aSpitler, Jeffrey, D.1 aRees, Simon, J.1 aHaves, Philip uhttps://simulationresearch.lbl.gov/publications/comparison-north-american-and-uk01209nas a2200145 4500008004100000245008800041210006900129300001000198490000800208520069700216100002000913700002500933700001800958856008700976 1998 eng d00aComparison of North American and U.K. Cooling Load Calculation Procedures - Results0 aComparison of North American and UK Cooling Load Calculation Pro a36-460 v1043 aCalculation of design cooling loads is of critical concern to designers of HVAC systems. The work reported here has been carried out under a joint ASHRAE/CIBSE research project to compare design cooling calculation methods. Three calculation methods have been tested, the ASHRAE heat balance method and radiant time series method, and the admit- tance method, used in the U.K. The results presented in this paper show the general trends in over/underprediction of peak load in the simplified methods compared to the heat balance method. The performance of the simplified methods is explained in terms of some of the underlying assumptions in the methods and by reference to specific examples.1 aRees, Simon, J.1 aSpitler, Jeffrey, D.1 aHaves, Philip uhttps://simulationresearch.lbl.gov/publications/comparison-north-american-and-uk-000478nas a2200109 4500008004100000245010300041210006900144260002700213100001800240700002300258856008700281 1998 eng d00aComponent-Based and Equation-Based Solvers for HVAC Simulation: a Comparison of HVACSIM+ and SPARK0 aComponentBased and EquationBased Solvers for HVAC Simulation a C aLiège, Belgiumc12/981 aHaves, Philip1 aSowell, Edward, F. uhttps://simulationresearch.lbl.gov/publications/component-based-and-equation-based01552nas a2200205 4500008004100000245007600041210006900117260000900186300001200195490000700207520087100214653002901085653003001114653002601144653002401170653003701194100001901231700001401250856008201264 1998 eng d00aOutdoor synthetic temperature for the calculation of space heating load0 aOutdoor synthetic temperature for the calculation of space heati c1998 a269-2770 v283 a

Methods to select the outdoor design temperature (ODT) for heating load calculation specified in current design codes in different countries are firstly discussed. Then a new method namely Stochastic Analysis is presented to determine the outdoor synthetic temperature (OST), which fully considers the randomness of weather and internal casual gains, and the thermal performance of buildings. The concept of OST enables the design of space heating system to be the trade-off between economics and risk. Finally, case studies of the influence of different building components on OST of a residential room in Beijing have been studied, which shows that OST depends upon building structures as well as weather conditions. It is recommended that OST rather than ODT should be employed in heating load calculation hence, sizing equipment for space heating systems.

10aheating load calculation10aoutdoor design conditions10aresidential buildings10astochastic analysis10athermal performance of buildings1 aHong, Tianzhen1 aJiang, Yi uhttps://simulationresearch.lbl.gov/publications/outdoor-synthetic-temperature02115nas a2200133 4500008004100000245008800041210006900129490000800198520163400206100001801840700002401858700001901882856008001901 1998 eng d00aA Standard Simulation Testbed for the Evaluation of Control Algorithms & Strategies0 aStandard Simulation Testbed for the Evaluation of Control Algori0 v1043 a

This paper, which reports the results of ASHRAE Research Project 825, describes the development of a set of tools and supporting data to facilitate the evaluation of HVAC control algorithms and strategies using computer simulation. The tools consist of a documented set of component models for use in two component-based HVAC simulation programs. New models have been developed to enable explicit simulation of flow rates and pressure drops in ventilation systems, particularly variable-air-volume (VAV) systems, and detailed simulation of algorithms and strategies used in HVAC control systems. A mixed-use building equipped with a VAV HVAC system has been extensively documented, and a detailed model of the fabric, mechanical equipment, and controls has been produced in order to illustrate the capabilities and use of the tools. Values for the parameters in the component models describing the fabric and mechanical equipment are based on construction drawings, manufacturer's specifications, surveys, and measurements. Detailed models of the strategies for fan control, supply air temperature control, and room temperature control were developed from the controls manufacturer's technical information and the configuration of the actual control system. A simulation model of the whole building was then assembled from the models of the fabric, mechanical equipment, and controls. Results obtained by exercising the test bed in order to demonstrate its use in evaluating the performance of interacting control loops are presented. The paper concludes by discussing possible applications and extensions of the test bed.

1 aHaves, Philip1 aNorford, Leslie, K.1 aDeSimone, Mark uhttps://simulationresearch.lbl.gov/publications/standard-simulation-testbed00904nas a2200109 4500008004100000245005500041210005400096260003600150520053200186100001800718856005800736 1997 eng d00aFault Modelling in Component-based HVAC Simulation0 aFault Modelling in Componentbased HVAC Simulation aPrague, Czech Republicc09/19973 aModels of faulty components or processes may either be used on-line as part of a fault detec- tion and diagnosis (FDD) system or may be used in simulations to train or test FDD procedures. Some faults may be modelled by choosing suit- able values of the parameters of fault free models, whereas other faults require specific extensions to fault free models. An example of the modelling of various faults in a cooling coil subsystem is pre- sented and different methods of using simulation in testing and training are discussed.1 aHaves, Philip uhttp://www.ibpsa.org/proceedings/BS1997/BS97_P101.pdf01533nas a2200205 4500008004100000245005900041210005800100260000900158300001200167490000700179520095600186653000801142653002401150653000901174653002301183653000801206100001901214700001401233856008001247 1997 eng d00aIISABRE: An integrated building simulation environment0 aIISABRE An integrated building simulation environment c1997 a219-2240 v323 a

An integrated building simulation environment, IISABRE, is introduced. IISABRE consists of CABD, BTP and IISPAM. CABD is an AutoCAD-based building descriptor enabling users to draw a building and define information. Some design tools are built into CABD, and a STEP-based building database can be generated, which provides an open mechanism to share the building database with other programs. BTP is a program for the detailed dynamic simulation of building thermal performance. With a PC 486DX50 (8M RAM) running in MS-Windows 3.11, BTP needs about 40 minutes to calculate the annual hourly energy demand for a building with 20 zones. IISPAM is a knowledge-based system for translating the STEP-based building database into ASCII-based data files for BTP. IISABRE can be widely employed in the field of building environmental engineering in order to improve the energy efficiency of buildings and the thermal comfort of the indoor environment.

10abtp10abuilding simulation10adest10aenergy performance10agui1 aHong, Tianzhen1 aJiang, Yi uhttps://simulationresearch.lbl.gov/publications/iisabre-integrated-building00471nas a2200121 4500008004100000245006400041210006100105260003100166100002500197700001800222700002200240856008700262 1997 eng d00aA Model-Based Approach to the Commissioning of HVAC Systems0 aModelBased Approach to the Commissioning of HVAC Systems aBrussles, Belgiumc08/19971 aBuswell, Richard, A.1 aHaves, Philip1 aSalsbury, Tim, I. uhttps://simulationresearch.lbl.gov/publications/model-based-approach-commissioning01057nas a2200145 4500008004100000245007300041210006900114260000900183300001200192490000700204520058400211100001900795700001400814856008300828 1997 eng d00aA new multizone model for simulation of building thermal performance0 anew multizone model for simulation of building thermal performan c1997 a123-1280 v323 a

A new multizone model which is an improvement on the state space model is presented, which is potentially more efficient in the simulation of large scale buildings than other methods such as finite difference, transfer functions, or finite volume. The modeling philosophy is firstly discussed. Then the principle and algorithm of the new model are described. Finally, a PC based program BTP developed based on state-of-the-art modeling strategy reveals its applicability with fast calculation speed and satisfactory accuracy in the modeling of building energy performance.

1 aHong, Tianzhen1 aJiang, Yi uhttps://simulationresearch.lbl.gov/publications/new-multizone-model-simulation00468nas a2200121 4500008004100000245007400041210006900115490000800184100001800192700002200210700002500232856008900257 1996 eng d00aCondition Monitoring in HVAC Subsystems using First Principles Models0 aCondition Monitoring in HVAC Subsystems using First Principles M0 v1021 aHaves, Philip1 aSalsbury, Tim, I.1 aWright, Jonathan, A. uhttps://simulationresearch.lbl.gov/publications/condition-monitoring-hvac-subsystems01440nas a2200265 4500008004100000024002400041245008600065210006900151250000600220260001600226490000800242520064800250653002100898653001400919653001800933653001300951653001500964653001200979653001400991100001801005700002001023700002201043700002301065856008601088 1996 eng d aPaper no. AT-96-1-100aDevelopment and Testing of a Prototype Tool for HVAC Control System Commissioning0 aDevelopment and Testing of a Prototype Tool for HVAC Control Sys a1 aAtlanta, GA0 v1023 a

Describes a set of automated tests for use in commissioning the controls associated with coils and mixing boxes in air-handling units. The test procedures were developed using a computer simulation of an office building air conditioning system and were verified by manual testing in real buildings. A prototype automated commissioning system was then evaluated in blind tests on a large air conditioning test rig. Concludes that automated commissioning has the potential to reduce the cost and increase the thoroughness of HVAC controls commissioning. A prototype commissioning tool is under development based on the described approach.

10aair conditioning10aautomatic10acommissioning10acontrols10aprototypes10atesting10ayear 19961 aHaves, Philip1 aJorgensen, D.R.1 aSalsbury, Tim, I.1 aDexter, Arthur, L. uhttps://simulationresearch.lbl.gov/publications/development-and-testing-prototype00980nas a2200109 4500008004100000245007100041210006900112260002500181520058600206100001800792856006000810 1995 eng d00aDetailed Modelling and Simulation of a VAV Air-Conditioning System0 aDetailed Modelling and Simulation of a VAV AirConditioning Syste aMadison, WIc08/19953 aThe paper describes a component-based dynamic simulation of a variable air volume (VAV) airconditioning system. The model is based closely on the design of one floor of a real commercial office building in London. The model includes an air handling unit and a duct system incorporating pressure-independent VAV boxes. The paper describes the simulation environment used to test control systems and to develop fault detection and diagnosis procedures and presents results of simulations that illustrate how the simulation can be used to study the interactions between control loops.1 aHaves, Philip uhttp://www.ibpsa.org/proceedings/BS1995/BS95_056_63.pdf00506nas a2200121 4500008004100000245009300041210006900134260002700203100002200230700001800252700002500270856008900295 1995 eng d00aA Fault Detection and Diagnosis Method Based on First Principles Models and Expert Rules0 aFault Detection and Diagnosis Method Based on First Principles M aBejing, Chinac09/19951 aSalsbury, Tim, I.1 aHaves, Philip1 aWright, Jonathan, A. uhttps://simulationresearch.lbl.gov/publications/fault-detection-and-diagnosis-method00355nas a2200109 4500008004100000245003800041210003800079260000900117100001400126700001900140856008600159 1995 eng d00aIntegrated building design system0 aIntegrated building design system c19951 aJiang, Yi1 aHong, Tianzhen uhttps://simulationresearch.lbl.gov/publications/integrated-building-design-system00484nas a2200109 4500008004100000245011100041210006900152260002500221100002000246700001800266856009000284 1995 eng d00aA Model of a Displacement Ventilation/Chilled Ceiling Cooling System Suitable for Annual Energy Simulation0 aModel of a Displacement VentilationChilled Ceiling Cooling Syste aMadison, WIc08/19951 aRees, Simon, J.1 aHaves, Philip uhttps://simulationresearch.lbl.gov/publications/model-displacement-ventilationchilled00453nas a2200121 4500008004100000245005900041210005900100260002700159100001800186700002000204700001900224856008800243 1995 eng d00aModelling and Simulation of Low Energy Cooling Systems0 aModelling and Simulation of Low Energy Cooling Systems aBejing, Chinac09/19951 aHaves, Philip1 aRees, Simon, J.1 aHarrington, L. uhttps://simulationresearch.lbl.gov/publications/modelling-and-simulation-low-energy00448nas a2200133 4500008004100000245004600041210004600087300001200133490000700145100002400152700002200176700002600198856009000224 1995 eng d00aNanofluids for Heat Transfer Applications0 aNanofluids for Heat Transfer Applications a255-2750 v141 aPhelan, Patrick, E.1 aPrasher, Ravi, S.1 aBhattacharya, Prajesh uhttps://simulationresearch.lbl.gov/publications/nanofluids-heat-transfer-applications00429nas a2200109 4500008004100000245007100041210006900112260002500181100001900206700001400225856008000239 1995 eng d00aPrediction of building thermal performance under random conditions0 aPrediction of building thermal performance under random conditio aBeijing, Chinac19951 aHong, Tianzhen1 aJiang, Yi uhttps://simulationresearch.lbl.gov/publications/prediction-building-thermal01011nas a2200145 4500008004100000245005500041210005500096260000900151300001200160490000700172520056700179100001900746700001400765856008600779 1995 eng d00aStochastic weather model for building HVAC systems0 aStochastic weather model for building HVAC systems c1995 a521-5320 v303 a

The weather is a multi-dimensional stochastic process; the traditional typical or standard meteorological year is not enough to describe the random behaviour of weather. The model presented in this paper is based on the vector auto-regressive (VAR) time series method. From the validation results, it can be seen that the stochastic weather model is essential to describe real climate behaviour, and the accuracy obtained is sufficient for the application of the stochastic weather model in the simulation and stochastic analysis of building HVAC systems.

1 aHong, Tianzhen1 aJiang, Yi uhttps://simulationresearch.lbl.gov/publications/stochastic-weather-model-building00365nas a2200097 4500008004100000245004500041210004400086260002900130100001800159856009000177 1994 eng d00aComponent-Based Modelling of VAV Systems0 aComponentBased Modelling of VAV Systems aLiège, Belgiumc12/19941 aHaves, Philip uhttps://simulationresearch.lbl.gov/publications/component-based-modelling-vav-systems00474nas a2200121 4500008004100000245008700041210006900128490000800197100001900205700001800224700002000242856009000262 1994 eng d00aDesign, Construction and Commissioning of Building Emulators for EMCS Applications0 aDesign Construction and Commissioning of Building Emulators for 0 v1001 aWang, Shengwei1 aHaves, Philip1 aNusgens, Pierre uhttps://simulationresearch.lbl.gov/publications/design-construction-and-commissioning01341nas a2200121 4500008004100000245007700041210006900118490000700187520094000194100002301134700001801157856004401175 1994 eng d00aEvaluating the Performance of Building Control Systems using an Emulator0 aEvaluating the Performance of Building Control Systems using an 0 v153 aThe control performance of an air-conditioning system is assessed using a qualitative method of evaluation. Fuzzy logic is used to relate performance criteria expressed in the form of IF-THEN rules to quantitative measures of energy consumption, discomfort, and maintenance costs. Test data were generated using an emulator consisting of a real-time simulation of the building shell and HVAC plant, together with a hardware interface that connects the simulation to commercial control equipment. Two case studies are presented. In the first, the effect of changing the strategy used to determine the zone temperature set-points is evaluated using 'expert rules', generated by a hypothetical facilities manager. In the second case study, the effect of varying the tuning parameters of the control system is evaluated using two sets of rules assumed to represent the differing perspectives of a facilities manager and a control engineer.1 aDexter, Arthur, L.1 aHaves, Philip uhttp://bse.sagepub.com/content/15/3.toc00468nas a2200121 4500008004100000245007000041210006700111260001800178100002300196700002400219700001800243856008500261 1994 eng d00aFault Detection in Air-Conditioning Systems Using A.I. Techniques0 aFault Detection in AirConditioning Systems Using AI Techniques aYork, England1 aDexter, Arthur, L.1 aFargus, Richard, S.1 aHaves, Philip uhttps://simulationresearch.lbl.gov/publications/fault-detection-air-conditioning00561nas a2200145 4500008004100000245010900041210006900150490000800219100002300227700001900250700001800269700002100287700002000308856008700328 1994 eng d00aInvestigation of the Reliability of Building Emulators for Testing Energy Management and Control Systems0 aInvestigation of the Reliability of Building Emulators for Testi0 v1001 aPeitsman, Henk, C.1 aWang, Shengwei1 aHaves, Philip1 aKärki, Satu, H.1 aPark, Cheol, P. uhttps://simulationresearch.lbl.gov/publications/investigation-reliability-building00600nas a2200157 4500008004100000245008700041210006900128260002900197100002300226700002300249700002400272700001800296700002200314700002500336856008100361 1994 eng d00aModel-Based Approaches to Fault Detection and Diagnosis in Air-Conditioning System0 aModelBased Approaches to Fault Detection and Diagnosis in AirCon aLiège, Belgiumc12/19941 aBenouarets, Mourad1 aDexter, Arthur, L.1 aFargus, Richard, S.1 aHaves, Philip1 aSalsbury, Tim, I.1 aWright, Jonathan, A. uhttps://simulationresearch.lbl.gov/publications/model-based-approaches-fault00446nas a2200121 4500008004100000245005200041210005200093260002900145100002300174700001800197700002000215856008900235 1993 eng d00aAutomatic Commissioning of HVAC Control Systems0 aAutomatic Commissioning of HVAC Control Systems aLondon, Englandc11/19931 aDexter, Arthur, L.1 aHaves, Philip1 aJorgensen, D.R. uhttps://simulationresearch.lbl.gov/publications/automatic-commissioning-hvac-control00488nas a2200121 4500008004100000245008500041210006900126260002800195100002300223700001800246700002000264856008200284 1993 eng d00aDevelopment of Techniques to Assist in the Commissioning of HVAC Control Systems0 aDevelopment of Techniques to Assist in the Commissioning of HVAC aManchester, UKc05/19931 aDexter, Arthur, L.1 aHaves, Philip1 aJorgensen, D.R. uhttps://simulationresearch.lbl.gov/publications/development-techniques-assist01511nas a2200145 4500008004100000245005400041210005400095260000900149300001200158490000700170520106600177100001401243700001901257856008901276 1993 eng d00aStochastic analysis of building thermal processes0 aStochastic analysis of building thermal processes c1993 a209-2180 v283 a

A methodology is presented for investigating the uncertainty properties of the building thermal processes caused by the random behaviour of the meteorological processes and the casual gains. A detailed building thermal model is used with a stochastic weather model and a random casual gain model. The probability distribution of the zone temperature of the building is calculated directly from these models. The overheating risk has been analysed as an example. The probability distribution of the periods when the zone temperature is higher than the demand temperature is calculated. The result shows all the possible situations rather than only a sample as would be obtained by running a normal simulation using given weather data. The influence of different building components on the overheating risk has been studied. The result shows that the most likely component for overheating risk in a residential building in Beijing is the window size. The thermal mass of the internal walls and the placing of windows have little effect on overheating risk.

1 aJiang, Yi1 aHong, Tianzhen uhttps://simulationresearch.lbl.gov/publications/stochastic-analysis-building-thermal00408nas a2200109 4500008004100000245005700041210005700098260002100155100001400176700001900190856008900209 1993 eng d00aStochastic analysis of overheating risk in buildings0 aStochastic analysis of overheating risk in buildings aLondon, UKc19931 aJiang, Yi1 aHong, Tianzhen uhttps://simulationresearch.lbl.gov/publications/stochastic-analysis-overheating-risk00422nas a2200121 4500008004100000245004900041210004900090260002600139100001800165700001400183700001600197856008700213 1992 eng d00aClimate Change and Passive Cooling in Europe0 aClimate Change and Passive Cooling in Europe aAuckland, New Zealand1 aHaves, Philip1 aKenny, G.1 aRoaf, Susan uhttps://simulationresearch.lbl.gov/publications/climate-change-and-passive-cooling00489nas a2200133 4500008004100000020001500041245005600056210005600112260005000168100001800218700001600236700002200252856008100274 1992 eng d a047021952100aEnvironmental Control in Energy Efficient Buildings0 aEnvironmental Control in Energy Efficient Buildings aOxfordbBlackwell Scientific Publications Ltd1 aHaves, Philip1 aRoaf, Susan1 aHancock, Mary, E. uhttps://simulationresearch.lbl.gov/publications/environmental-control-energy00380nas a2200121 4500008004100000245003000041210003000071260003100101100001600132700001800148700001700166856007500183 1992 eng d00aImpacts of Climate Change0 aImpacts of Climate Change aSolihull, Englandc05/19921 aHulme, Mike1 aHaves, Philip1 aBoardman, B. uhttps://simulationresearch.lbl.gov/publications/impacts-climate-change00501nas a2200133 4500008004100000245008000041210006900121260001400190100002000204700002300224700001300247700001800260856008900278 1991 eng d00aSelf-tuning Control with Fuzzy Rule-Based Supervision for HVAC Applications0 aSelftuning Control with Fuzzy RuleBased Supervision for HVAC App aSingapore1 aLing, Keck-Voon1 aDexter, Arthur, L.1 aGeng, G.1 aHaves, Philip uhttps://simulationresearch.lbl.gov/publications/self-tuning-control-fuzzy-rule-based00781nas a2200241 4500008004100000245010800041210006900149490000700218653002100225653001400246653001800260653002200278653001300300653002200313653001200335653001600347100001800363700002300381700002000404700002000424700001300444856008200457 1991 eng d00aUse of a Building Emulator to Develop Techniques for Improved Commissioning and Control of HVAC Systems0 aUse of a Building Emulator to Develop Techniques for Improved Co0 v9710aair conditioning10aautomatic10acommissioning10acomputer programs10acontrols10aenergy management10aheating10aventilation1 aHaves, Philip1 aDexter, Arthur, L.1 aJorgensen, D.R.1 aLing, Keck-Voon1 aGeng, G. uhttps://simulationresearch.lbl.gov/publications/use-building-emulator-develop00469nas a2200109 4500008004100000245009300041210006900134260003200203100001800235700002300253856008300276 1991 eng d00aUse of a Building Emulator to Evaluate Control Strategies Implemented in Commercial BEMS0 aUse of a Building Emulator to Evaluate Control Strategies Implem aCantebury, Englandc04/19911 aHaves, Philip1 aDexter, Arthur, L. uhttps://simulationresearch.lbl.gov/publications/use-building-emulator-evaluate01682nas a2200193 4500008004100000245009600041210006900137260002600206300001200232520101800244100002501262700001501287700001801302700002301320700002201343700002001365700001901385856008401404 1991 eng d00aUse of Building Emulators to Evaluate the Performance of Building Energy Management Systems0 aUse of Building Emulators to Evaluate the Performance of Buildin aNice, Francec08/1991 a209-2133 a

Three complementary approaches may be used in the evaluation of the performance of building control systems-simulation, emulation and field testing. In emulation a real-time simulation of the building and HVAC plant is connected to a real building energy management system (BEMS) via a hardware interface. Emulation has the advantage of allowing controlled, repeatable experiments whilst testing real devices that may contain proprietary algorithms. Building emulators have been developed by the authors in the context of lEA Annex 17, which is concerned with the use of simulation to evaluate the performance of BEMS. The paper discusses different approaches to the design of building emulators and describes the different architectures, hardware and software used by the authors. The problem of evaluating the overall performance of BEMS is discussed and results are presented that illustrate the use of emulators to investigate the influence of the tuning of local loop controls on building performance.

1 aVaezi-Nejad, Hossein1 aHutter, E.1 aHaves, Philip1 aDexter, Arthur, L.1 aKelly, George, E.1 aNusgens, Pierre1 aWang, Shengwei uhttps://simulationresearch.lbl.gov/publications/use-building-emulators-evaluate00456nas a2200109 4500008004100000245007600041210006900117260002900186100002300215700001800238856009000256 1990 eng d00aThe Influence of Tuning on the Performance of a Building Control System0 aInfluence of Tuning on the Performance of a Building Control Sys aLiège, Belgiumc12/19901 aDexter, Arthur, L.1 aHaves, Philip uhttps://simulationresearch.lbl.gov/publications/influence-tuning-performance-building00380nas a2200097 4500008004100000245005800041210005500099100002300154700001800177856008700195 1989 eng d00aA Robust Self-Tuning Controller for HVAC Applications0 aRobust SelfTuning Controller for HVAC Applications1 aDexter, Arthur, L.1 aHaves, Philip uhttps://simulationresearch.lbl.gov/publications/robust-self-tuning-controller-hvac00373nas a2200109 4500008004100000245003800041210003800079260002200117100002300139700001800162856008300180 1989 eng d00aSimulation of Local Loop Controls0 aSimulation of Local Loop Controls aVancouver, Canada1 aDexter, Arthur, L.1 aHaves, Philip uhttps://simulationresearch.lbl.gov/publications/simulation-local-loop-controls00555nas a2200169 4500008003900000245004100039210004100080260003500121100002500156700002200181700002400203700002200227700002000249700002500269700003000294856006100324 1989 d00aThermal Energy Storage System Sizing0 aThermal Energy Storage System Sizing aVancouver, BC, Canadac01/19891 aDumortier, Dominique1 aKammerud, Ron, C.1 aBirdsall, Bruce, E.1 aAndersson, Brandt1 aEto, Joseph, H.1 aCarroll, William, L.1 aWinkelmann, Frederick, C. uhttp://www.ibpsa.org/proceedings/BS1989/BS89_357_362.pdf01357nas a2200145 4500008004100000245006500041210006400106260001200170300001200182490000600194520088100200100001801081700002501099856008701124 1988 eng d00aDaylight in Dynamic Thermal Modelling Programs: a Case Study0 aDaylight in Dynamic Thermal Modelling Programs a Case Study c11/1988 a183-1880 v93 a

Heating, cooling and lighting energy consumptions in buildings are inter-related, and a model which treats thermal performance and lighting simultaneously is required in order to evaluate the full benefits of daylighting in buildings. A lighting facility has been included in a dynamic building simulation program (SERI-RES) used in the Department of Energy's passive solar programme. Interior daylight illuminance is calculated using an extension of the daylight factor method. The lighting usage of various lighting systems is predicted from the daylight illuminance, and the thermal consequences of that lighting use included in the thermal simulation of the building. The applicability of the method described in this paper is not limited to SERI-RES. The method could be incorporated in any building energy analysis program intended for the UK or similar climates.

1 aHaves, Philip1 aLittlefair, Paul, J. uhttps://simulationresearch.lbl.gov/publications/daylight-dynamic-thermal-modelling00368nas a2200109 4500008003900000245004400039210004000083260001200123100002000135700001800155856008500173 1988 d00aThe HVAC Costs of Fresh Air Ventilation0 aHVAC Costs of Fresh Air Ventilation c09/19881 aEto, Joseph, H.1 aMeyer, Cecile uhttps://simulationresearch.lbl.gov/publications/hvac-costs-fresh-air-ventilation00458nas a2200109 4500008003900000245008000039210006900119260003900188100002000227700001800247856008300265 1988 d00aThe HVAC Costs of Increased Fresh Air Ventilation Rates in Office Buildings0 aHVAC Costs of Increased Fresh Air Ventilation Rates in Office Bu aOttawa, ON, Canada.bLBNLc01/19881 aEto, Joseph, H.1 aMeyer, Cecile uhttps://simulationresearch.lbl.gov/publications/hvac-costs-increased-fresh-air00432nas a2200121 4500008003900000024001500039245004800054210004600102260003000148100002000178700002200198856009000220 1988 d aDA-88-21-100aModeling Cogeneration Systems with DOE-2.1C0 aModeling Cogeneration Systems with DOE21C aDallas, TXbLBNLc01/19881 aEto, Joseph, H.1 aGates, Steven, D. uhttps://simulationresearch.lbl.gov/publications/modeling-cogeneration-systems-doe-21c01083nas a2200133 4500008003900000245007600039210006900115260001800184490000700202520061200209100002000821700002600841856008200867 1988 d00aSaving Electricity in Commercial Buildings with Adjustable-Speed Drives0 aSaving Electricity in Commercial Buildings with AdjustableSpeed  bIEEEc05/19880 v243 a

Fan and chiller energy savings achievable in commercial buildings with adjustable-speed drives are described. The savings are estimated with the aid of parametric simulations from a sophisticated, hourly building energy simulation model. Two prototypes-a single-zone retail store and a multizone medium office building-are simulated for five U.S. locations. The model incorporates part-load performance curves for both inlet vane and adjustable-speed drive controls for fans and centrifugal chillers. The results identify economic conditions that justify the added expense of adjustable-speed drives.

1 aEto, Joseph, H.1 aDe Almeida, Anibal, T uhttps://simulationresearch.lbl.gov/publications/saving-electricity-commercial00424nas a2200109 4500008004100000245006200041210006200103260002900165100001800194700001700212856008500229 1988 eng d00aTowards an Environment for HVAC Control System Evaluation0 aTowards an Environment for HVAC Control System Evaluation aOstend, Belgiumc09/19881 aHaves, Philip1 aTrewella, D. uhttps://simulationresearch.lbl.gov/publications/towards-environment-hvac-control01630nas a2200121 4500008003900000245010400039210006900143260001200212490000700224520117100231100002001402856008601422 1988 d00aOn Using Degree-days to Account for the Effects of Weather on Annual Energy Use in Office Buildings0 aUsing Degreedays to Account for the Effects of Weather on Annual c09/19880 v123 a

To better quantify the effects of conservation measures, degree.day-based techniques are commonly used to isolate weather.induced changes in building energy use. In this paper, we use a building energy simulation model, which allows us to hold fixed all influences on energy use besides weather, to evaluate several degree-day-based techniques. The evaluation is applied to simulated electricity and natural gas consumption for two large office building prototypes located in five U.8. climates. We review the development of degree day- based, weather-normalization techniques to identify issues for applying the techniques to office buildings and then evaluate the accuracy of the techniques with the simulated data. We conclude that, for the two office building prototypes and five U.8. locations examined, most techniques perform reasonably well; accuracy, in predicting annual consumption, is generally better than 10%. Our major finding is that accuracy among individual techniques is overwhelmed by circumstances outside the control of the analyst, namely, the choice of the initial year from which the normalization estimates are made.

1 aEto, Joseph, H. uhttps://simulationresearch.lbl.gov/publications/using-degree-days-account-effects00414nas a2200097 4500008004100000245008700041210006900128260001500197100001800212856008600230 1987 eng d00aThe Application of Simulation to the Evaluation of Building Energy Control Systems0 aApplication of Simulation to the Evaluation of Building Energy C aBangor, UK1 aHaves, Philip uhttps://simulationresearch.lbl.gov/publications/application-simulation-evaluation01698nas a2200169 4500008004100000245006200041210006000103260001200163300001200175490000600187520117800193100001601371700002101387700002201408700001801430856008001448 1987 eng d00aPerformance of Roofpond Cooled Residences in U.S. Climate0 aPerformance of Roofpond Cooled Residences in US Climate c01/1987 a265-2920 v43 a

The thermal advantages of a roofpond as an element of a residential cooling system are described. The authors conducted heat transfer experiments at two roofpond residences (RPRs) at Trinity University; the authors used data from these experiments to validate RPR simulations. Results of measurements of vertical and horizontal temperature differences within roofponds are discussed. Horizontal heat transfer within one water bag was effective. Thermal resistance at the outer surface of a water bag with a deflated glazing can be significant. Simulation shows that an RPR can provide comfort without supplemental sensible cooling during almost all hours of a typical summer in any U.S climate. Ceiling fans are important in most climates. In the most demanding climates, the residence and the pond insulating panels must have high R-value. A map is included that provides RPR design guidance. The simulations indicate that dehumidification will be required to control mold, mildew, and ceiling condensation in an RPR in most climates; energy and power displacement by an RPR is sensitive to the humidity control required and the efficiency of the dehumidifier used.

1 aClark, Gene1 aLoxsom, Fred, M.1 aDoderer, Earl, S.1 aHaves, Philip uhttps://simulationresearch.lbl.gov/publications/performance-roofpond-cooled00593nas a2200145 4500008004100000245011800041210006900159260003500228490000600263100002300269700002600292700001800318700002900336856008200365 1987 eng d00aThe Use of Dynamic Simulation Models to Evaluate Algorithms for Building Energy Control: Experience with HVACSIM+0 aUse of Dynamic Simulation Models to Evaluate Algorithms for Buil aLausanne, Switzerlandc09/19870 v81 aDexter, Arthur, L.1 aEftekhari, Mahroo, M.1 aHaves, Philip1 aJota, Fábio, Gonçalves uhttps://simulationresearch.lbl.gov/publications/use-dynamic-simulation-models00432nas a2200109 4500008004100000245006600041210006500107260002500172100002400197700001800221856008300239 1986 eng d00aDevelopment of SERI-RES within the UK Passive Solar Programme0 aDevelopment of SERIRES within the UK Passive Solar Programme aBoulder, COc06/19861 aLittler, John, G.F.1 aHaves, Philip uhttps://simulationresearch.lbl.gov/publications/development-seri-res-within-uk00482nas a2200109 4500008004100000245011700041210006900158260002700227100001800254700001800272856008200290 1986 eng d00aGeneration of Data for Passive Solar Building Simulation from a Three Dimensional Architectural Modelling System0 aGeneration of Data for Passive Solar Building Simulation from a  aPecs, Hungaryc09/19861 aGreen, Cedric1 aHaves, Philip uhttps://simulationresearch.lbl.gov/publications/generation-data-passive-solar00440nas a2200097 4500008003900000245008800039210006900127260004100196100002000237856008500257 1985 d00aA Comparison of Weather Normalization Techniques for Commercial Building Energy Use0 aComparison of Weather Normalization Techniques for Commercial Bu aClearwater Beach, FL bLBNLc12/19851 aEto, Joseph, H. uhttps://simulationresearch.lbl.gov/publications/comparison-weather-normalization00440nas a2200097 4500008003900000245009000039210006900129260003600198100002000234856008800254 1985 d00aCooling Strategies Based on Indicators of Thermal Storage in Commercial Building Mass0 aCooling Strategies Based on Indicators of Thermal Storage in Com aCollege Station, Texasc09/19851 aEto, Joseph, H. uhttps://simulationresearch.lbl.gov/publications/cooling-strategies-based-indicators00671nas a2200193 4500008003900000245006700039210006200106260004300168490000800211100002400219700002100243700002400264700001700288700001600305700002200321700002100343700003000364856008300394 1985 d00aThe DOE-2 Computer Program for Thermal Simulation of Buildings0 aDOE2 Computer Program for Thermal Simulation of Buildings bAmerican Institute of Physicsc01/19850 v1351 aBirdsall, Bruce, E.1 aBuhl, Walter, F.1 aCurtis, Richard, B.1 aErdem, Ender1 aEto, Joseph1 aHirsch, James, J.1 aOlson, Karen, H.1 aWinkelmann, Frederick, C. uhttps://simulationresearch.lbl.gov/publications/doe-2-computer-program-thermal01406nas a2200193 4500008003900000024001800039245010700057210006900164260002400233520072900257653002500986653001901011653002401030653001601054653001701070100002001087700001601107856008901123 1985 d aEEB-BED-85-0500aImplications of Office Building Thermal Mass and Multi-day Temperature Profiles for Cooling Strategies0 aImplications of Office Building Thermal Mass and Multiday Temper aDenver, COc08/19853 a

This paper describes a study of the cooling energy requirements that result from thermal storage in building mass, and suggests methods for predicting and controlling its energy cost implications. The study relies on computer simulations of energy use for a large office building prototype in El Paso, TX using the DOE-2 building energy analysis program. Increased Monday cooling energy requirements resulting from the weekend shut-down of HVAC systems are documented. Predictors of energy use and peak demands, which account for thermal storage in building mass, are described. Load-shifting, sub-cooling and pre-cooling equipment operating strategies are evaluated with explicit reference to utility rate schedules.

10acommercial buildings10acooling energy10aenergy conservation10apeak demand10athermal mass1 aEto, Joseph, H.1 aPowell, Gay uhttps://simulationresearch.lbl.gov/publications/implications-office-building-thermal00486nas a2200121 4500008004100000245006100041210005700102260006900159100001800228700001800246700001600264856008400280 1985 eng d00aThe Integration of Graphic and Thermal Simulation Models0 aIntegration of Graphic and Thermal Simulation Models aPinner, Middlesex, UKbWembley, Online Publications Ltdc10/19851 aGreen, Cedric1 aHaves, Philip1 aHuddy, Paul uhttps://simulationresearch.lbl.gov/publications/integration-graphic-and-thermal00539nas a2200145 4500008003900000245005700039210005500096260007100151100002100222700001700243700002000260700002200280700003000302856006100332 1985 d00aNew Features of the DOE-2.1c Energy Analysis Program0 aNew Features of the DOE21c Energy Analysis Program bInternational Building Performance Simulation Associationc01/19851 aBuhl, Walter, F.1 aErdem, Ender1 aEto, Joseph, H.1 aHirsch, James, J.1 aWinkelmann, Frederick, C. uhttp://www.ibpsa.org/proceedings/BS1985/BS85_195_200.pdf00378nas a2200097 4500008003900000245005200039210005200091260002800143100002000171856008900191 1984 d00aCommercial Building Cogeneration Opportuntities0 aCommercial Building Cogeneration Opportuntities aSanta Cruz, CAc08/19841 aEto, Joseph, H. uhttp://aceee.org/files/proceedings/1984/data/papers/SS84_Panel1_Paper_059.pdf#page=100595nas a2200181 4500008003900000245004700039210004200086260002300128100002400151700002400175700002100199700001700220700002000237700002200257700002100279700003000300856008300330 1984 d00aThe DOE-2 Building Energy Analysis Program0 aDOE2 Building Energy Analysis Program aSingaporec05/19841 aCurtis, Richard, B.1 aBirdsall, Bruce, E.1 aBuhl, Walter, F.1 aErdem, Ender1 aEto, Joseph, H.1 aHirsch, James, J.1 aOlson, Karen, H.1 aWinkelmann, Frederick, C. uhttps://simulationresearch.lbl.gov/publications/doe-2-building-energy-analysis00395nas a2200097 4500008003900000245006400039210006300103260002500166100002000191856008600211 1983 d00aOptimal Cogeneration Systems for High-Rise Office Buildings0 aOptimal Cogeneration Systems for HighRise Office Buildings aOrlando, FLc05/19831 aEto, Joseph, H. uhttps://simulationresearch.lbl.gov/publications/optimal-cogeneration-systems-high00478nas a2200133 4500008004100000245006100041210006100102260001700163100001600180700002100196700001800217700002200235856008700257 1983 eng d00aResults of Validated Simulations of Roof Pond Residences0 aResults of Validated Simulations of Roof Pond Residences aSanta Fe, NM1 aClark, Gene1 aLoxsom, Fred, M.1 aHaves, Philip1 aDoderer, Earl, S. uhttps://simulationresearch.lbl.gov/publications/results-validated-simulations-roof00416nas a2200097 4500008004100000245007900041210006900120260002700189100001800216856008400234 1983 eng d00aSelection and Sizing of Low Energy Cooling Systems for More Humid Climates0 aSelection and Sizing of Low Energy Cooling Systems for More Humi aCrete, Greecec06/19831 aHaves, Philip uhttps://simulationresearch.lbl.gov/publications/selection-and-sizing-low-energy00408nas a2200097 4500008004100000245008400041210006900125260001200194100001800206856008600224 1983 eng d00aSERI-RES: a Thermal Simulation Model for Passive Solar and Low Energy Buildings0 aSERIRES a Thermal Simulation Model for Passive Solar and Low Ene c10/19831 aHaves, Philip uhttps://simulationresearch.lbl.gov/publications/seri-res-thermal-simulation-model01768nas a2200169 4500008004100000245009200041210006900133260002500202300001200227490000600239520120000245100001801445700001601463700001801479700001501497856008601512 1982 eng d00aAccuracy of a Simple Method of Estimating the Minimum Temperature of a Sealed Roof Pond0 aAccuracy of a Simple Method of Estimating the Minimum Temperatur aHouston, TXc07/1982 a709-7140 v53 a

Detailed heat flux and temperature measurements have been made in two residential scale roof pond buildings in San Antonio, Texas from July to November 1981. The minimum temprature of the 4 in deep roof pond sealed in PVC bags was approximately equal to the minimum ambient dry bulb temperature. The sensitivity of this equality to changes in meteorological conditions, maximum pond temperature and thermal load is evaluated using the measurements. Verified simulations are then used to evaluate the sensitivity of this equality to changes in the thermal load, and to changes in the depth, surface emittance and surface thermal resistance of the sealed pond in various climates. For the range of roof pond design options of interest in passive cooling of buildings, the minimum pond temperature was found to be within 2 F of the minimum ambient temperature in all climates considered. The equality of these minimum temperatures is advocated as a useful rule of thumb for feasibility assessment and as part of a simplified design methodology. The simulated minimum pond temperature was found to be surprisingly insensitive to a 50% decrease in the fraction of pond area exposed to the sky.

1 aSchutt, Brady1 aClark, Gene1 aHaves, Philip1 aMerino, M. uhttps://simulationresearch.lbl.gov/publications/accuracy-simple-method-estimating00493nas a2200121 4500008004100000245008400041210006900125260002700194100001800221700002100239700002200260856008900282 1982 eng d00aDehumidification and Passive Cooling for Retrofit and Conventional Construction0 aDehumidification and Passive Cooling for Retrofit and Convention aKnoxville, TNc07/19821 aHaves, Philip1 aLoxsom, Fred, M.1 aDoderer, Earl, S. uhttps://simulationresearch.lbl.gov/publications/dehumidification-and-passive-cooling00512nas a2200109 4500008004100000245014100041210006900182260002300251100002200274700001800296856008800314 1981 eng d00aDesign and Operating Strategies and Sizing Relationships for Solar Regenerated Desiccant Dehumidifiers Used with Passive Cooling Systems0 aDesign and Operating Strategies and Sizing Relationships for Sol aMiami, FLc11/19811 aNelson, Peter, E.1 aHaves, Philip uhttps://simulationresearch.lbl.gov/publications/design-and-operating-strategies-and00476nas a2200121 4500008004100000245007700041210006900118260003000187100002200217700001700239700001800256856008000274 1981 eng d00aEconomic Analysis of Desiccant Dehumidifiers in Passive Solar Residences0 aEconomic Analysis of Desiccant Dehumidifiers in Passive Solar Re aPhiladelphia, PAc05/19811 aNelson, Peter, E.1 aMcDougal, G.1 aHaves, Philip uhttps://simulationresearch.lbl.gov/publications/economic-analysis-desiccant00473nas a2200109 4500008004100000245010500041210006900146260002300215100002200238700001800260856008500278 1981 eng d00aExperimental Validation of a Computer Model of a Solar Regenerated Desiccant Dehumidification System0 aExperimental Validation of a Computer Model of a Solar Regenerat aMiami, FLc11/19811 aNelson, Peter, E.1 aHaves, Philip uhttps://simulationresearch.lbl.gov/publications/experimental-validation-computer00578nas a2200157 4500008004100000022002900041245004800070210004800118260008900166100001500255700001800270700001600288700001800304700001600322856008200338 1981 eng d a0895530333 978089553033200aHeat Loss Rates from Wetted Tilted Surfaces0 aHeat Loss Rates from Wetted Tilted Surfaces aMiami Beach, FLbAmerican Section of the International Solar Energy Societyc11/19811 aHaines, R.1 aHaves, Philip1 aVollink, D.1 aBowen, Arthur1 aClark, Gene uhttps://simulationresearch.lbl.gov/publications/heat-loss-rates-wetted-tilted00500nas a2200133 4500008004100000245007400041210006900115260002300184100002100207700001600228700001500244700001800259856008900277 1981 eng d00aMeasurement of Components of Heat Transfer in Passive Cooling Systems0 aMeasurement of Components of Heat Transfer in Passive Cooling Sy aMiami, FLc11/19811 aLoxsom, Fred, M.1 aClark, Gene1 aMerino, M.1 aHaves, Philip uhttps://simulationresearch.lbl.gov/publications/measurement-components-heat-transfer00439nas a2200097 4500008004100000245010600041210006900147260002300216100001800239856008400257 1981 eng d00aSimulated Performance of a Passively Cooled Residence with a Solar Regenerated Desiccant Dehumidifier0 aSimulated Performance of a Passively Cooled Residence with a Sol aMiami, FLc11/19811 aHaves, Philip uhttps://simulationresearch.lbl.gov/publications/simulated-performance-passively00416nas a2200121 4500008004100000245004800041210004800089260002500137100001800162700001500180700001600195856008300211 1980 eng d00aHeat Transfer in Passively Cooled Buildings0 aHeat Transfer in Passively Cooled Buildings aOrlando, FLc07/19801 aHaves, Philip1 aBently, D.1 aClark, Gene uhttps://simulationresearch.lbl.gov/publications/heat-transfer-passively-cooled01170nas a2200133 4500008004100000245006500041210006100106260002500167490000800192520072500200100001500925700001800940856007800958 1980 eng d00aThe Thermal Benefits and Cost Effectiveness of Earth Berming0 aThermal Benefits and Cost Effectiveness of Earth Berming aAmherst, MAc10/19800 v5.13 a

A number of advantages are claimed for earth sheltered buildings; the earth provides both insulation and thermal storage and also serves to reduce infiltration and noise. This paper seeks to quantify the thermal advantages of both earth sheltering and perimeter insulation by comparing the simulated thermal performance of an earth sheltered house, a house with perimeter insulation and a house with neither. The fuel savings are then compared to the estimated construction costs to determine cost-effectiveness. The major saving from an earth sheltered building is obtained in colder climates where the effective elevation of the frost line due to the earth berms considerably reduces the cost of the foundation.

1 aSpeltz, J.1 aHaves, Philip uhttps://simulationresearch.lbl.gov/publications/thermal-benefits-and-cost00416nas a2200097 4500008004100000245007200041210006900113260002900182100001800211856008900229 1979 eng d00aOne Dimensional Representations of the Heat Flow Beneath a Building0 aOne Dimensional Representations of the Heat Flow Beneath a Build aSan Antonio, TXc03/19791 aHaves, Philip uhttps://simulationresearch.lbl.gov/publications/one-dimensional-representations-heat00825nas a2200253 4500008004100000245008000041210007100121260001200192300001200204490000800216653002500224653002600249653001200275653001900287653003000306653001800336653002200354653002600376100002100402700001800423700002300441700002000464856008700484 1976 eng d00aThe Radio Structure of a Sample of 101 Quasars from the Parkes ±4º Survey0 aRadio Structure of a Sample of 101 Quasars from the Parkes ±4º S c08/1976 a275-3060 v17610aAngular Distribution10aAstronomical Catalogs10aQuasars10aRadio Emission10aRadio Sources (Astronomy)10aRadio Spectra10aSpectrum Analysis10aUltrahigh Frequencies1 aBentley, Michael1 aHaves, Philip1 aSpencer, Ralph, E.1 aStannard, David uhttps://simulationresearch.lbl.gov/publications/radio-structure-sample-101-quasars00495nas a2200133 4500008004100000245007100041210006900112490000800181100002100189700001800210700002300228700002000251856009000271 1975 eng d00aHigh Resolution Observations of Extended Radio Sources at 1666 MHz0 aHigh Resolution Observations of Extended Radio Sources at 1666 M0 v1731 aBentley, Michael1 aHaves, Philip1 aSpencer, Ralph, E.1 aStannard, David uhttps://simulationresearch.lbl.gov/publications/high-resolution-observations-extended01326nas a2200229 4500008004100000245005900041210005500100260001200155300001200167490000800179520057600187653003200763653003400795653002500829653003300854653004000887653002500927653001900952100001800971700002200989856008501011 1975 eng d00aThe Orientation of the Magnetic Field in Radio Sources0 aOrientation of the Magnetic Field in Radio Sources c11/1975 a53P-56P0 v1733 a

Recent data on the polarization of extragalactic radio sources are used to investigate the distribution of Delta, the angle between the major axis of a source and the intrinsic position angle of the E vector of linear polarization. Previous work on this subject has led to widely divergent conclusions. It is found that sources of high radio luminosity usually have Delta near 90 deg, implying that the magnetic fields in such sources are oriented along the major axis. For radio galaxies with low luminosity, on the other hand, Delta tends to lie nearer zero deg.

10aextragalactic radio sources10amagnetic field configurations10apolarization (waves)10apolarization characteristics10apolarized electromagnetic radiation10aradiant flux density10aradio galaxies1 aHaves, Philip1 aConway, Robin, G. uhttps://simulationresearch.lbl.gov/publications/orientation-magnetic-field-radio00371nas a2200097 4500008004100000245006300041210006300104490000800167100001800175856008000193 1975 eng d00aPolarization Parameters of 183 Extragalactic Radio Sources0 aPolarization Parameters of 183 Extragalactic Radio Sources0 v1731 aHaves, Philip uhttps://simulationresearch.lbl.gov/publications/polarization-parameters-18301622nas a2200301 4500008004100000245004700041210004300088260001200131300001200143490000800155520072700163653002600890653003200916653001900948653001900967653002300986653004001009653001201049653002501061653002001086653002501106653001801131653002601149100001801175700002201193700002001215856008501235 1974 eng d00aThe Polarization of Radio Sources at 31 CM0 aPolarization of Radio Sources at 31 CM c10/1974 a117-1310 v1693 a

Measurements of the linear polarization of extragalactic radio sources have been made over a range of wavelengths in order to study both the properties of the sources themselves and the Faraday rotation along the line of sight to the observer. As part of a continuing program of such measurements the flux densities and integrated polarizations of 226 sources (including 134 quasars) were observed at 966 MHz (lambda 31 cm), to complement previous measurements at lambda 49 and lambda 74 cm (Conway et al. 1972). These results have been combined with others at shorter wavelengths in a discussion of the polarization properties of quasars (Conway et al. 1974). All the sources have angular sizes of 1 arcmin or less

10aAstronomical Catalogs10aextragalactic radio sources10afaraday effect10ainterferometry10amicrowave emission10apolarized electromagnetic radiation10aQuasars10aradiant flux density10aradio astronomy10astatistical analysis10atables (data)10avery high frequencies1 aHaves, Philip1 aConway, Robin, G.1 aStannard, David uhttps://simulationresearch.lbl.gov/publications/polarization-radio-sources-31-cm00504nas a2200181 4500008004100000245002700041210002600068260001200094300001200106490000800118100002200126700002100148700001800169700002100187700002300208700002000231856007100251 1974 eng d00aQSOs of High Redshift?0 aQSOs of High Redshift c11/1974 a209-2100 v2521 aBrowne, Ian, W.A.1 aBentley, Michael1 aHaves, Philip1 aMcEwan, Neil, J.1 aSpencer, Ralph, E.1 aStannard, David uhttps://simulationresearch.lbl.gov/publications/qsos-high-redshift01668nas a2200193 4500008004100000245003800041210003400079260001200113300001200125490000800137520111500145100002201260700001801282700002601300700002001326700002501346700002401371856007901395 1974 eng d00aThe Radio Polarization of Quasars0 aRadio Polarization of Quasars c07/1974 a137-1620 v1683 a

Observations over a wide range of wavelengths, 2.2 ≤ λ ≤ 73 cm, have been combined to define the wavelength variation of the degree of linear polarization m(λ) for 120 quasars with known redshift. For the majority, m(λ) decreases monotonically with increasing wavelength but for 35 sources the polarization curve is inverted at short wavelengths. A classification is given, based on both the polarization curve and the radio spectrum, and the results are interpreted in terms of the presence or absence of opaque components in the source. The depolarization which occurs at long wavelengths is accounted for by a combination of spectral effects and Faraday depolarization. For 46 steep-spectrum sources the depolarization curve appears to be dominated by the Faraday effect, and has been used to deduce the electron density within the radiating components. In this group of sources the correlation between depolarization and redshift noted by Kronberg et al. is confirmed and strengthened. A discussion is given of some theoretical models of radio sources in the light of the depolarization data.

1 aConway, Robin, G.1 aHaves, Philip1 aKronberg, Philipp, P.1 aStannard, David1 aVallée, Jacques, P.1 aWardle, John, F. C. uhttps://simulationresearch.lbl.gov/publications/radio-polarization-quasars