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.
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.
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 aThe 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-based01804nas 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 aFusing 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 aHeating, 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 aUrban 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 aWith 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 aPredicting 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 aAn 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 aPhysics-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 aPhysics-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 aA 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 aWith 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 aThe 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 aBuilding 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 aUrbanization 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.html02376nas 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 aPredictive 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 aAdvanced 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 aIn 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 aAnomalous 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 aThis 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-air01824nas a2200205 4500008004100000245004000041210003900081490000700120520119400127653002401321653002401345653003601369653002201405653002001427653003001447100001901477700002001496700001501516856008701531 2018 eng d00aBuilding Simulation: Ten Challenges0 aBuilding Simulation Ten Challenges0 v113 aBuildings 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 aEnergy-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 aEnergy 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 aEnergy 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 aProperly 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 aOccupants 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.html02000nas 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 aCyber-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 aThis 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 aRainfall 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 aUrban-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 aOver 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 aOccupancy 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 aAs 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 aOccupancy 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 aAccurate 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 aThis 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 aEvaluates 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 aBuilding 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 aThis 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 aBuilding 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 aClimate 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/plain02102nas a2200121 4500008004100000245005000041210004600091520170800137100001701845700001901862700001401881856008501895 2017 eng d00aAn Agent-Based Stochastic Occupancy Simulator0 aAgentBased Stochastic Occupancy Simulator3 aOccupancy 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 aIn 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 aBuildings 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 aWeather 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 aIce-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 aThis 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 aSimulation 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 aSmall- 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 aThis 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 aTo 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 aThe "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 aOne 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 aMore 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 aOperational 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-faults02155nas 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 aDistrict 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 aOccupant 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 aOccupancy 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 aAs 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 aSmall 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:
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 aSmart 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 aInternal 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 aThis 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 aWith 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 aOccupant 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 aOccupant 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 aTraditionally, 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 aVariable 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 aAn 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 aHVAC 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 aOccupants 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 aOccupant 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-energy02261nas 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 aSmall 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 aAs 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-low02814nas a2200349 4500008003900000245007400039210006900113260001100182490000800193520171300201653003701914653005101951653001402002653003202016653003202048653002602080653002202106653001502128653001502143653001302158653002002171653002402191100001902215700002202234700001702256700002002273700002802293700002002321700001502341700002302356856008502379 2015 d00aCommercial Building Energy Saver: An energy retrofit analysis toolkit0 aCommercial Building Energy Saver An energy retrofit analysis too c9/20150 v1593 aSmall 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 aLighting 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 aThe 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 aUnderstanding 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 aThe 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-efficiency02134nas 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 aVariable 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 aRetrofit 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-toolkit02052nas 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 aWhen 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 aUsing 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-its02039nas 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 aBuilding 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 aOccupant 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 aEnergy-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 aReducing 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 aBuilding 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 aOccupants 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 aThis 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 aThe 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 aBuildings 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 aBuildings 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 aThis 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:
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 aThis 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 aEnergy 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-buildings02296nas 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 aOvertime 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 aGreen 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:
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 aBuilding 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 aU.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 aLighting 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 aBuilding 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 aBuildings 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-peak02408nas 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 aOccupancy 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-modeling00472nas 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 aNatural 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 aA 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 aMost 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 aThe 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 aSpace 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 aFor 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 aThe 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-commissioning02363nas 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 aExisting 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=101404nas 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 aThis 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-000666nas 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-energyplus00610nas 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-results01677nas 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 aMost 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-simulation02272nas 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 aMany 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-whole00596nas 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 aDemand 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-commissioning01832nas 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 aIntegrated 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 aA 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-model00475nas 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-schemes00464nas 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-using01213nas 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-constraints00472nas 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 aThis 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 aNumerical 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-stress00473nas 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-window01425nas 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 aThis 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 aWith 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 aIntegrated 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=71324092801911nas 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.pdf02060nas 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 aThe 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-energy00537nas 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 aThis 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 aThe 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 aThis 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-between00545nas 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=50301943nas 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 aThis 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 aThe 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 aIn 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=50300454nas 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 aModelica 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.pdf01584nas 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 aThe 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.pdf00592nas 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-and01795nas 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 aA 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.pdf00501nas 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-prototyping00475nas 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-managing00792nas 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-upgrades00535nas 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-energy00459nas 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-thermal00665nas 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 aThe 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-efficiency00546nas 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 aThis 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-office00853nas 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 aThe 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.pdf02284nas 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 aIn 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-china01672nas 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 aThe 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.pdf00481nas 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-glazing00549nas 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 aFor 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-eindimensionalen00530nas 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-building00574nas 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-based01819nas a2200145 4500008004100000245005600041210005600097260003000153520132100183100001801504700002301522700001801545700002201563856008801585 2005 eng d00aImproving the Data Available to Simulation Programs0 aImproving the Data Available to Simulation Programs aMontreal, Canadac08/20053 aBuilding 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-functional00873nas 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-based02109nas 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 aThe 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-data01965nas 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 aA 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-training00977nas 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-002088nas 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 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.
(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/25/3/22300572nas 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-update00520nas 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-ashrae01717nas 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-002097nas 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 aThe 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-cooling01945nas 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 aA 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-000571nas 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-doesnt01277nas 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/25/3/21100431nas 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 aBuilding 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.pdf01634nas 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 aIn 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-100504nas 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-condition00408nas 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-models00537nas 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 aEnergy 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 aAn 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 aAn 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 aAn 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 aThe 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 aA 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-and00551nas 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-parameter01870nas 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 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 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 aSelecting 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 aA 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 aThe 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 aThe 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 aA 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 aThe 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 aEnergy 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 aThe 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 aThere 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 aWe 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 aThe 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 aA 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 aWe 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 aA 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 aMethods 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 aThis 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 aAn 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 aA 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 aDescribes 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-energy00429nas 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 aThe 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 aA 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 aThree 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-controls01357nas 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 aHeating, 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-modelling00424nas 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-control00414nas 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 aThe 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-solar00671nas 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-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.pdf00595nas 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-analysis00478nas 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 aDetailed 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 aA 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 aRecent 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 aMeasurements 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 aObservations 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