02298nas a2200277 4500008004100000022001300041245016000054210006900214260001600283300001600299490000800315520136500323653004401688653002401732653002301756653001801779653002201797653002301819100001201842700001701854700001501871700001901886700001301905700001501918856008701933 2019 eng d a0048969700aAssessment of occupant-behavior-based indoor air quality and its impacts on human exposure risk: A case study based on the wildfires in Northern California0 aAssessment of occupantbehaviorbased indoor air quality and its i cJan-10-2019 a1251 - 12610 v6863 a

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

10acomputational fluid dynamics siumlation10ahuman exposure risk10aindoor air quality10aNAPA wildfire10aoccupant behavior10arespiratory injury1 aLuo, Na1 aWeng, Wenguo1 aXu, Xiaoyu1 aHong, Tianzhen1 aFu, Ming1 aSun, Kaiyu uhttps://simulationresearch.lbl.gov/publications/assessment-occupant-behavior-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 a

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

10adata fusion10aFeature selection10aMachine learning10aoccupancy prediction10aPhysics-based model1 aWang, Wei1 aHong, Tianzhen1 aXu, Ning1 aXu, Xiaodong1 aChen, Jiayu1 aShan, Xiaofang uhttps://simulationresearch.lbl.gov/publications/cross-source-sensing-data-fusion02132nas a2200241 4500008004100000022001300041245011800054210006900172260001600241300001400257490000800271520136600279653001501645653001701660653002101677653001701698653001601715653002401731100001201755700001901767700001801786856008601804 2019 eng d a0378778800aAn inverse approach to solving zone air infiltration rate and people count using indoor environmental sensor data0 ainverse approach to solving zone air infiltration rate and peopl cJan-09-2019 a228 - 2420 v1983 a

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

10aenergyplus10ainfiltration10aInverse problems10apeople count10asensor data10azone air parameters1 aLi, Han1 aHong, Tianzhen1 aSofos, Marina uhttps://simulationresearch.lbl.gov/publications/inverse-approach-solving-zone-air02188nas a2200301 4500008004100000245011100041210006900152260001600221520124300237653001701480653002401497653002901521653002501550100001601575700002001591700001501611700001401626700001901640700001601659700001501675700002001690700001801710700001801728700002001746700002001766700001801786856008201804 2019 eng d00aPrototyping the BOPTEST Framework for Simulation-Based Testing of Advanced Control Strategies in Buildings0 aPrototyping the BOPTEST Framework for SimulationBased Testing of aRome, Italy3 a

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

10abenchmarking10abuilding simulation10aModel predictive control10asoftware development1 aBlum, David1 aJorissen, Filip1 aHuang, Sen1 aChen, Yan1 aArroyo, Javier1 aBenne, Kyle1 aLi, Yanfei1 aGavan, Valentin1 aRivalin, Lisa1 aHelsen, Lieve1 aVrabie, Draguna1 aWetter, Michael1 aSofos, Marina uhttps://simulationresearch.lbl.gov/publications/prototyping-boptest-framework01824nas a2200205 4500008004100000245004000041210003900081490000700120520119400127653002401321653002401345653003601369653002201405653002001427653003001447100001901477700002001496700001501516856008701531 2018 eng d00aBuilding Simulation: Ten Challenges0 aBuilding Simulation Ten Challenges0 v113 a

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

10abuilding energy use10abuilding life cycle10abuilding performance simulation10aenergy efficiency10aenergy modeling10azero-net-energy buildings1 aHong, Tianzhen1 aLangevin, Jared1 aSun, Kaiyu uhttps://simulationresearch.lbl.gov/publications/building-simulation-ten-challenges01954nas a2200241 4500008004100000245009500041210006900136490000800205520119700213653002201410653001201432653002301444653002201467653002101489653002501510100001401535700001201549700001701561700001901578700001401597700001401611856008701625 2018 eng d00aComparative Study of Air-Conditioning Energy Use of Four Office Buildings in China and USA0 aComparative Study of AirConditioning Energy Use of Four Office B0 v1693 a

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

10aBuilding envelope10aclimate10aenergy consumption10aoccupant behavior10aoffice buildings10atechnological choice1 aZhou, Xin1 aYan, Da1 aAn, Jingjing1 aHong, Tianzhen1 aShi, Xing1 aJin, Xing uhttps://simulationresearch.lbl.gov/publications/comparative-study-air-conditioning02000nas a2200253 4500008004100000022001300041245010400054210006900158260001200227300001100239490000700250520118500257653002701442653001801469653001601487653002501503653002001528100003001548700001501578700001901593700001901612700002901631856008601660 2018 eng d a1550485900aA Framework for Privacy-Preserving Data Publishing with Enhanced Utility for Cyber-Physical Systems0 aFramework for PrivacyPreserving Data Publishing with Enhanced Ut c12/2018 a1 - 220 v143 a

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

10acyber physical systems10adeep learning10ak-anonymity10aPrivacy preservation10aSmart buildings1 aSangogboye, Fisayo, Caleb1 aJia, Ruoxi1 aHong, Tianzhen1 aSpanos, Costas1 aKjærgaard, Mikkel, Baun uhttps://simulationresearch.lbl.gov/publications/framework-privacy-preserving-data02346nas a2200229 4500008004100000245009900041210006900140490000800209520158400217653003601801653001301837653002001850653001801870653001501888653003001903100002001933700001501953700001901968700002001987700002102007856008802028 2018 eng d00aA Novel Variable Refrigerant Flow (VRF) Heat Recovery System Model: Development and Validation0 aNovel Variable Refrigerant Flow VRF Heat Recovery System Model D0 v1683 a

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

10abuilding performance simulation10acontrols10aenergy modeling10aheat recovery10avalidation10aVariable refrigerant flow1 aZhang, Rongpeng1 aSun, Kaiyu1 aHong, Tianzhen1 aYura, Yoshinori1 aHinokuma, Ryohei uhttps://simulationresearch.lbl.gov/publications/novel-variable-refrigerant-flow-vrf02081nas a2200217 4500008004100000245010200041210006900143490000800212520134200220653002201562653002401584653003301608653001901641653002201660653002201682100002101704700001501725700001901740700002201759856008201781 2018 eng d00aQuantifying the benefits of a building retrofit using an integrated system approach: A case study0 aQuantifying the benefits of a building retrofit using an integra0 v1593 a

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

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

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

10acoupling10aenergy modeling10aenergyplus10aUrban climate modeling10aWRF1 aJain, Rajeev1 aLuo, Xuan1 aSever, Gökhan1 aHong, Tianzhen1 aCatlett, Charlie uhttps://www.tandfonline.com/doi/full/10.1080/19401493.2018.1534275https://www.tandfonline.com/doi/pdf/10.1080/19401493.2018.153427502543nas a2200277 4500008004100000022001300041245018600054210006900240260001200309300001400321490000800335520142800343653002701771653002701798653001801825653003601843100001901879700002001898700002201918700002101940700002401961700001301985700001501998700001902013856023302032 2018 eng d a0306261900aTranslating climate change and heating system electrification impacts on building energy use to future greenhouse gas emissions and electric grid capacity requirements in California0 aTranslating climate change and heating system electrification im c09/2018 a522 - 5340 v2253 a

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

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

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

1 aBlum, David1 aLin, Guanjing1 aSpears, Michael1 aPage, Janie1 aGranderson, Jessica uhttps://simulationresearch.lbl.gov/publications/when-data-analytics-meet-site02289nas a2200217 4500008004100000245009600041210006900137490000800206520155700214100002601771700001801797700002701815700002201842700001801864700002301882700001701905700002901922700002001951700001801971856008201989 2017 eng d00aDynamic equation-based thermo-hydraulic pipe model for district heating and cooling systems0 aDynamic equationbased thermohydraulic pipe model for district he0 v1513 a

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

1 avan der Heijde, Brahm1 aFuchs, Marcus1 aTugores, Carles, Ribas1 aSchweiger, Gerald1 aSartor, Kevin1 aBasciotti, Daniele1 aMuller, Dirk1 aNytsch-Geusen, Christoph1 aWetter, Michael1 aHelsen, Lieve uhttps://simulationresearch.lbl.gov/publications/dynamic-equation-based-thermo02757nas a2200109 4500008004100000245011400041210006900155520229900224100001502523700001902538856009002557 2017 eng d00aA Framework for Quantifying the Impact of Occupant Behavior on Energy Savings of Energy Conservation Measures0 aFramework for Quantifying the Impact of Occupant Behavior on Ene3 a

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

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

1 aSun, Kaiyu1 aHong, Tianzhen uhttps://simulationresearch.lbl.gov/publications/framework-quantifying-impact-occupant02155nas a2200133 4500008004100000245009000041210006900131520167300200100001701873700001201890700001901902700001501921856008501936 2017 eng d00aA Novel Stochastic Modeling Method to Simulate Cooling Loads in Residential Districts0 aNovel Stochastic Modeling Method to Simulate Cooling Loads in Re3 a

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

1 aAn, Jingjing1 aYan, Da1 aHong, Tianzhen1 aSun, Kaiyu uhttps://simulationresearch.lbl.gov/publications/novel-stochastic-modeling-method03410nas a2200409 4500008004100000245008500041210006900126260001200195520213600207653000902343653002502352653002202377653002002399653001902419653002302438653003302461653003902494653003202533653001302565653002102578100002202599700001902621700002202640700002102662700002002683700001702703700002302720700002202743700002102765700002002786700002302806700001902829700001502848700002802863700002002891856008902911 2017 eng d00aSmall and Medium Building Efficiency Toolkit and Community Demonstration Program0 aSmall and Medium Building Efficiency Toolkit and Community Demon c03/20173 a

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

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

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

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

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

10aCBES10acommercial buildings10aenergy efficiency10aenergy modeling10aenergy savings10aindoor air quality10aindoor environmental quality10aoutdoor air measurement technology10aoutdoor airflow intake rate10aretrofit10aventilation rate1 aPiette, Mary, Ann1 aHong, Tianzhen1 aFisk, William, J.1 aBourassa, Norman1 aChan, Wanyu, R.1 aChen, Yixing1 aCheung, H.Y., Iris1 aHotchi, Toshifumi1 aKloss, Margarita1 aLee, Sang, Hoon1 aPrice, Phillip, N.1 aSchetrit, Oren1 aSun, Kaiyu1 aTaylor-Lange, Sarah, C.1 aZhang, Rongpeng uhttps://simulationresearch.lbl.gov/publications/small-and-medium-building-efficiency02293nas a2200241 4500008004100000245016600041210006900207520145100276653002201727653001801749653002101767653002301788653002501811653002201836653001501858100001401873700001201887700001701899700001901916700001401935700001501949856008701964 2017 eng d00aSpatial Distribution of Internal Heat Gains: A Probabilistic Representation and Evaluation of Its Influence on Cooling Equipment Sizing in Large Office Buildings0 aSpatial Distribution of Internal Heat Gains A Probabilistic Repr3 a

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

10aair handling unit10achiller plant10aequipment sizing10ainternal heat gain10aspatial distribution10aspatial diversity10astochastic1 aZhang, Qi1 aYan, Da1 aAn, Jingjing1 aHong, Tianzhen1 aTian, Wei1 aSun, Kaiyu uhttps://simulationresearch.lbl.gov/publications/spatial-distribution-internal-heat02436nas a2200217 4500008004100000245013500041210006900176520163000245653002401875653002501899653002301924653002201947653003801969653004402007100001602051700001202067700001502079700001902094700001602113856008902129 2016 eng d00aA Comparative Study on Energy Performance of Variable Refrigerant Flow Systems and Variable Air Volume Systems in Office Buildings0 aComparative Study on Energy Performance of Variable Refrigerant 3 a

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


 

 

10abuilding simulation10acomparative analysis10aenergy performance10afield measurement10aVariable Air Volume (VAV) Systems10aVariable Refrigerant Flow (VRF) Systems1 aYu, Xinqiao1 aYan, Da1 aSun, Kaiyu1 aHong, Tianzhen1 aZhu, Dandan uhttps://simulationresearch.lbl.gov/publications/comparative-study-energy-performance02209nas 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-baseline01835nas a2200169 4500008003900000245005800039210005700097520128500154653001601439653002101455653002501476653002201501100001501523700001901538700002701557856008101584 2016 d00aOccupancy data analytics and prediction: a case study0 aOccupancy data analytics and prediction a case study3 a

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

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

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

10abehavior measure10aBehavior Modeling10abuilding performance simulation10aenergy savings10aenergyplus10aoccupant behavior1 aSun, Kaiyu1 aHong, Tianzhen uhttps://simulationresearch.lbl.gov/publications/simulation-approach-estimate-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 a

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

10abuilding simulation10aEnergy conservation measure10aenergy modeling10aenergyplus10aHigh Performance computing10aretrofit1 aLee, Sang, Hoon1 aHong, Tianzhen1 aPiette, Mary, Ann1 aSawaya, Geof1 aChen, Yixing1 aTaylor-Lange, Sarah, C. uhttps://simulationresearch.lbl.gov/publications/accelerating-energy-retrofit00936nas a2200157 4500008004100000245008500041210006900126260003000195520038100225653004400606653001000650100001800660700002200678700002400700856005400724 2015 eng d00aCLIMATE-SPECIFIC MODELING AND ANALYSIS FOR BEST-PRACTICE INDIAN OFFICE BUILDINGS0 aCLIMATESPECIFIC MODELING AND ANALYSIS FOR BESTPRACTICE INDIAN OF aHyderabad, Indiac12/20153 a

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

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

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

10aBuilding Technologies Department10aBuilding Technology and Urban Systems Division10abuildings10abuildings energy efficiency10aCommercial Building Systems10aconservation measures10aenergy efficiency10aenergy use10aenergyplus10aExternal10aRetrofit Energy10asimulation research1 aHong, Tianzhen1 aPiette, Mary, Ann1 aChen, Yixing1 aLee, Sang, Hoon1 aTaylor-Lange, Sarah, C.1 aZhang, Rongpeng1 aSun, Kaiyu1 aPrice, Phillip, N. uhttps://simulationresearch.lbl.gov/publications/commercial-building-energy-saver02785nas a2200145 4500008003900000245011200039210006900151520224000220100002002460700001902480700001702499700001702516700002202533856008402555 2015 d00aDEEP: A Database of Energy Efficiency Performance to Accelerate Energy Retrofitting of Commercial Buildings0 aDEEP A Database of Energy Efficiency Performance to Accelerate E3 a

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

1 aLee, Sang, Hoon1 aHong, Tianzhen1 aSawaya, Geof1 aChen, Yixing1 aPiette, Mary, Ann uhttps://simulationresearch.lbl.gov/publications/deep-database-energy-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 a

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

10abuilding simulation10aenergy modeling10aenergyplus10aHeat pump10amodel validation10aVariable refrigerant flow1 aHong, Tianzhen1 aSun, Kaiyu1 aZhang, Rongpeng1 aHinokuma, Ryohei1 aKasahara, Shinichi1 aYura, Yoshinori uhttps://simulationresearch.lbl.gov/publications/development-and-validation-new02052nas a2200217 4500008003900000245008100039210006900120260005100189520129700240100001601537700002401553700002001577700002501597700001801622700001901640700002101659700002201680700002101702700002701723856008401750 2015 d00aGreen, Clean, & Mean: Pushing the Energy Envelope in Tech Industry Buildings0 aGreen Clean Mean Pushing the Energy Envelope in Tech Industry Bu bLawrence Berkeley National Laboratoryc05/20153 a

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

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

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

1 aMills, Evan1 aGranderson, Jessica1 aChan, Wanyu, R.1 aDiamond, Richard, C.1 aHaves, Philip1 aNordman, Bruce1 aMathew, Paul, A.1 aPiette, Mary, Ann1 aRobinson, Gerald1 aSelkowitz, Stephen, E. uhttps://simulationresearch.lbl.gov/publications/green-clean-mean-pushing-energy02242nas a2200133 4500008003900000245007600039210006900115520175500184100001501939700001901954700002801973700002202001856008502023 2015 d00aA pattern-based automated approach to building energy model calibration0 apatternbased automated approach to building energy model calibra3 a

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

1 aSun, Kaiyu1 aHong, Tianzhen1 aTaylor-Lange, Sarah, C.1 aPiette, Mary, Ann uhttps://simulationresearch.lbl.gov/publications/pattern-based-automated-approach02234nas a2200313 4500008003900000245007900039210006900118260001200187300001200199490000700211520134300218653001401561653001501575653001801590653001501608653002401623653002901647653001501676653001301691100001701704700001901721700001301740700001401753700001301767700001501780700001501795700002201810856008801832 2014 d00aComparison of Building Energy Use Data Between the United States and China0 aComparison of Building Energy Use Data Between the United States c08/2014 a165-1750 v783 a

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

10abuildings10acomparison10adata analysis10adata model10aEnergy benchmarking10aenergy monitoring system10aenergy use10aretrofit1 aXia, Jianjun1 aHong, Tianzhen1 aShen, Qi1 aFeng, Wei1 aYang, Le1 aIm, Piljae1 aLu, Alison1 aBhandari, Mahabir uhttps://simulationresearch.lbl.gov/publications/comparison-building-energy-use-data00559nas a2200181 4500008003900000245005300039210005300092100001900145700001400164700002500178700001200203700001400215700001400229700001500243700001500258700001700273856008700290 2014 d00aIntegrated Design for High Performance Buildings0 aIntegrated Design for High Performance Buildings1 aHong, Tianzhen1 aLi, Cheng1 aDiamond, Richard, C.1 aYan, Da1 aZhang, Qi1 aZhou, Xin1 aGuo, Siyue1 aSun, Kaiyu1 aWang, Jingyi uhttps://simulationresearch.lbl.gov/publications/integrated-design-high-performance02607nas a2200169 4500008003900000245006200039210006000101520204900161100001902210700001802229700001902247700001702266700002302283700002002306700002102326856009002347 2014 d00aA New Model to Simulate Energy Performance of VRF Systems0 aNew Model to Simulate Energy Performance of VRF Systems3 a

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

1 aHong, Tianzhen1 aPang, Xiufeng1 aSchetrit, Oren1 aWang, Liping1 aKasahara, Shinichi1 aYura, Yoshinori1 aHinokuma, Ryohei uhttps://simulationresearch.lbl.gov/publications/new-model-simulate-energy-performance01865nas a2200145 4500008004100000245014400041210006900185260001200254490000700266520130200273100002101575700001801596700002101614856008401635 2014 eng d00aThe Role of International Partnerships in Delivering Low- Energy Building Design: A Case Study of the Singapore Scientific Planning Process0 aRole of International Partnerships in Delivering Low Energy Buil c05/20140 v143 a

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

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

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

10abuilding energy use10abuilding simulation10amodel calibration10aoccupant behavior10aovertime occupancy10astochastic modeling1 aSun, Kaiyu1 aHong, Tianzhen1 aGuo, Siyue uhttps://simulationresearch.lbl.gov/publications/stochastic-modeling-overtime05291nas a2200193 4500008003900000245004400039210004400083260001200127520474700139100001904886700001404905700001504919700001704934700001304951700001304964700001504977700002204992856008305014 2013 d00aBuilding Energy Monitoring and Analysis0 aBuilding Energy Monitoring and Analysis c06/20133 a

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

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

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

Key research findings were summarized as follows:

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

1 aHong, Tianzhen1 aFeng, Wei1 aLu, Alison1 aXia, Jianjun1 aYang, Le1 aShen, Qi1 aIm, Piljae1 aBhandari, Mahabir uhttps://simulationresearch.lbl.gov/publications/building-energy-monitoring-and01318nas a2200193 4500008003900000245006300039210006300102260002500165520071500190100002400905700001500929700001900944700002200963700002900985700002601014700002001040700001801060856004601078 2012 d00aApplication of a stochastic window use model in EnergyPlus0 aApplication of a stochastic window use model in EnergyPlus aMadison, WIc08/20123 a

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

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

1 aDutton, Spencer, M.1 aZhang, Hui1 aZhai, Yongchao1 aArens, Edward, A.1 aSmires, Youness, Bennani1 aBrunswick, Samuel, L.1 aKonis, Kyle, S.1 aHaves, Philip uhttps://escholarship.org/uc/item/2gm7r78301650nas a2200157 4500008003900000245005400039210005400093260003000147520113000177100001801307700002201325700002101347700001801368700002201386856008401408 2012 d00aMapping Hvac Systems for Simulation In EnergyPlus0 aMapping Hvac Systems for Simulation In EnergyPlus aMadison, WI, USAc07/20123 a

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

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

1 aMaile, Tobias1 aBasarkar, Mangesh1 aO'Donnell, James1 aHaves, Philip1 aSettlemyre, Kevin uhttps://simulationresearch.lbl.gov/publications/mapping-hvac-systems-simulation02446nas a2200277 4500008004100000245004600041210004600087260003100133520169300164653001401857653001101871653002201882653001101904653001001915653001501925653002101940653001401961100001801975700001901993700001302012700001502025700001902040700001802059700001802077856007302095 2012 eng d00aSustainable Campus with PEV and Microgrid0 aSustainable Campus with PEV and Microgrid aPacific Grove, CAc08/20193 a

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

10abuildings10acampus10aelectric vehicles10aenergy10aloads10amicrogrids10arenewable energy10atransport1 aKumar, Nandha1 aSivaneasan, B.1 aSo, P.L.1 aGooi, H.B.1 aJadhav, Nilesh1 aSingh, Reshma1 aMarnay, Chris uhttps://aceee.org/files/proceedings/2012/data/papers/0193-000363.pdf00610nas 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-energyplus02272nas a2200169 4500008004100000245007100041210006900112260001200181520171200193100002101905700001701926700001501943700001801958700002301976700001801999856008502017 2011 eng d00aSimModel: A domain data model for whole building energy simulation0 aSimModel A domain data model for whole building energy simulatio c10/20113 a

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

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

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

1 aO'Donnell, James1 aSee, Richard1 aRose, Cody1 aMaile, Tobias1 aBazjanac, Vladimir1 aHaves, Philip uhttps://simulationresearch.lbl.gov/publications/simmodel-domain-data-model-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-000569nas 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-commissioning01850nas 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-analysis01856nas a2200133 4500008004100000245009800041210006900139260002400208520133300232100001701565700003101582700002101613856008801634 2009 eng d00aApplication of software tools for moisture protection of buildings in different climate zones0 aApplication of software tools for moisture protection of buildin aSisimiut, Groenland3 a

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

1 aKrus, Martin1 aNouidui, Thierry, Stephane1 aSedlbauer, Klaus uhttps://simulationresearch.lbl.gov/publications/application-software-tools-moisture00473nas a2200121 4500008003900000245008000039210006900119260001200188100001900200700002700219700002100246856008400267 2009 d00aAssessment of Energy Impact of Window Technologies for Commercial Buildings0 aAssessment of Energy Impact of Window Technologies for Commercia c10/20091 aHong, Tianzhen1 aSelkowitz, Stephen, E.1 aYazdanian, Mehry uhttps://simulationresearch.lbl.gov/publications/assessment-energy-impact-window00608nas a2200157 4500008004100000022001400041245013400055210006900189300001200258490000700270100003100277700002100308700002900329700001700358856007500375 2009 eng d a0171-544500aNeue objektorientierte hygrothermische Modell-Bibliothek zur Ermittlung des hygrothermischen und hygienischen Komforts in Räumen0 aNeue objektorientierte hygrothermische ModellBibliothek zur Ermi a271-2780 v311 aNouidui, Thierry, Stephane1 aSedlbauer, Klaus1 aNytsch-Geusen, Christoph1 aKießl, Kurt uhttps://simulationresearch.lbl.gov/publications/neue-objektorientierte02060nas a2200217 4500008004100000245010500041210006900146260000900215300001200224490000600236520133500242653001601577653002401593653002301617653002201640653003001662653002901692100001501721700001901736856008701755 2009 eng d00aSimulation-based assessment of the energy savings benefits of integrated control in office buildings0 aSimulationbased assessment of the energy savings benefits of int c2009 a239-2510 v23 a

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

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

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

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

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

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

10amodelica1 aFranke, Rüdiger1 aCasella, Francesco1 aOtter, Martin1 aProelss, Katrin1 aSielemann, Michael1 aWetter, Michael uhttp://www.ep.liu.se/ecp_article/index.en.aspx?issue=043;article=1301592nas a2200169 4500008004100000245013000041210006900171490000900240520096100249100002201210700001801232700002701250700002101277700002101298700001801319856008501337 2009 eng d00aTowards a Very Low Energy Building Stock: Modeling the US Commercial Building Stock to Support Policy and Innovation Planning0 aTowards a Very Low Energy Building Stock Modeling the US Commerc0 v37:53 a

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

1 aCoffey, Brian, E.1 aBorgeson, Sam1 aSelkowitz, Stephen, E.1 aApte, Joshua, S.1 aMathew, Paul, A.1 aHaves, Philip uhttps://simulationresearch.lbl.gov/publications/towards-very-low-energy-building01364nas a2200229 4500008004100000245006400041210006400105260000900169300001200178490000600190520067400196653002200870653001000892653001500902653002300917100001900940700002100959700001800980700002700998700002001025856008901045 2008 eng d00aComparing computer run time of building simulation programs0 aComparing computer run time of building simulation programs c2008 a210-2130 v13 a

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

10acomputer run time10adoe-210aenergyplus10asimulation program1 aHong, Tianzhen1 aBuhl, Walter, F.1 aHaves, Philip1 aSelkowitz, Stephen, E.1 aWetter, Michael uhttps://simulationresearch.lbl.gov/publications/comparing-computer-run-time-building00674nas a2200205 4500008004100000245008400041210006900125260000900194490001500203653001600218653001000234653002300244653001500267653001500282100001900297700002100316700002100337700002100358856008900379 2008 eng d00aComparisons of HVAC Simulations between EnergyPlus and DOE-2.2 for data centers0 aComparisons of HVAC Simulations between EnergyPlus and DOE22 for c20090 v115 Part 110adata center10adoe-210aenergy performance10aenergyplus10asimulation1 aHong, Tianzhen1 aSartor, Dale, A.1 aMathew, Paul, A.1 aYazdanian, Mehry uhttps://simulationresearch.lbl.gov/publications/comparisons-hvac-simulations-between02149nas a2200181 4500008004100000022002200041245021800063210006900281260002400350300001500374490000600389520138300395100003101778700002901809700001801838700002101856856009001877 2008 eng d a978-87-7877-265-700aObject-oriented hygrothermal building physics library as a tool to predict and to ensure a thermal and hygric indoor comfort in building construction by using a Predicted-Mean-Vote (PMV) control ventilation system0 aObjectoriented hygrothermal building physics library as a tool t aCopenhagen, Denmark app.825-8320 v23 a

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

1 aNouidui, Thierry, Stephane1 aNytsch-Geusen, Christoph1 aHolm, Andreas1 aSedlbauer, Klaus uhttps://simulationresearch.lbl.gov/publications/object-oriented-hygrothermal-building00454nas a2200133 4500008004100000245004100041210004100082260003100123100002000154700001800174700002500192700002300217856008000240 2008 eng d00aUsing SPARK as a Solver for Modelica0 aUsing SPARK as a Solver for Modelica aBerkeley, CA, USAc07/20081 aWetter, Michael1 aHaves, Philip1 aMoshier, Michael, A.1 aSowell, Edward, F. uhttps://simulationresearch.lbl.gov/publications/using-spark-solver-modelica01363nas a2200145 4500008004100000245004100041210004100082260003100123520089400154100002001048700001801068700002501086700002301111856008301134 2008 eng d00aUsing SPARK as a solver for Modelica0 aUsing SPARK as a solver for Modelica aBerkeley, CA, USAc08/20083 a

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

1 aWetter, Michael1 aHaves, Philip1 aMoshier, Michael, A.1 aSowell, Edward, F. uhttp://www.ibpsa.us/simbuild2008/technical_sessions/SB08-DOC-TS03-1-Wetter.pdf00580nas a2200157 4500008004100000245008000041210006900121260002600190100001800216700001800234700001500252700002000267700002300287700002600310856008600336 2007 eng d00aCoverage Problem for Sensors Embedded in Temperature Sensitive Environments0 aCoverage Problem for Sensors Embedded in Temperature Sensitive E aAnchorage, ALc5/20071 aSen, Arunabha1 aDas, Nibedita1 aZhou, Ling1 aShen, Bao, Hong1 aMurthy, Sudheendra1 aBhattacharya, Prajesh uhttps://simulationresearch.lbl.gov/publications/coverage-problem-sensors-embedded00576nas a2200133 4500008004100000245013000041210006900171260002800240100002100268700001900289700002400308700002100332856008900353 2007 eng d00aGlobal Efficiency of Direct Flow Vacuum Collectors in Autonomous Solar Desiccant Cooling: Simulation and Experimental Results0 aGlobal Efficiency of Direct Flow Vacuum Collectors in Autonomous aBeijing, Chinac09/20071 aBourdoukan, Paul1 aWurtz, Etienne1 aSpérandio, Maurice1 aJoubert, Patrice uhttps://simulationresearch.lbl.gov/publications/global-efficiency-direct-flow-vacuum00792nas 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-simulation02020nas a2200265 4500008004100000245010800041210006900149260001200218300001400230490000700244520118600251653003801437653002501475653002401500100002601524700001301550700001601563700001301579700001201592700002401604700002201628700002001650700001301670856007101683 2006 eng d00aCharacterization of the Temperature Oscillation Technique to Measure the Thermal Conductivity of Fluids0 aCharacterization of the Temperature Oscillation Technique to Mea c08/2006 a2950-29560 v493 a

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

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

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

10aTemperature oscillation technique10aThermal conductivity10athermal diffusivity1 aBhattacharya, Prajesh1 aNara, S.1 aVijayan, P.1 aTang, T.1 aLai, W.1 aPhelan, Patrick, E.1 aPrasher, Ravi, S.1 aSong, David, W.1 aWang, J. uhttp://www.sciencedirect.com/science/article/pii/S001793100600144X02129nas a2200157 4500008004100000245011200041210006900153260001600222520154600238100001901784700001601803700002201819700002101841700002101862856008801883 2006 eng d00aDehumidification Enhancement of Direct Expansion Systems through Component Augmentation of the Cooling Coil0 aDehumidification Enhancement of Direct Expansion Systems through aOrlando, FL3 a

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

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

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

1 aHaves, Philip1 aHitchcock, Robert, J.1 aGillespie, Kenneth, L.1 aBrook, Martha1 aShockman, Christine1 aDeringer, Joseph, J1 aKinney, Kristopher, L. uhttp://www.aceee.org/proceedings-paper/ss06/panel03/paper1000480nas a2200133 4500008004100000245005400041210005400095260003600149100001700185700002000202700002000222700001900242856008500261 2006 eng d00aHalfway to Zero Energy in a Large Office Building0 aHalfway to Zero Energy in a Large Office Building aPacific Grove, CA, USAc08/20061 aHanson, Mark1 aCarlson, Steven1 aSammartano, Dan1 aTaylor, Thomas uhttps://simulationresearch.lbl.gov/publications/halfway-zero-energy-large-office00350nas a2200109 4500008004100000245002900041210002900070260002400099100002200123700002100145856007400166 2006 eng d00aIFC to CONTAM Translator0 aIFC to CONTAM Translator aBoston, MAc08/20061 aBasarkar, Mangesh1 aSwami, Muthasamy uhttps://simulationresearch.lbl.gov/publications/ifc-contam-translator00445nas a2200109 4500008004100000245006700041210006700108260003200175100001900207700002400226856008500250 2006 eng d00aImplementation of an Earth Tube System Into EnergyPlus Program0 aImplementation of an Earth Tube System Into EnergyPlus Program aCambridge, MA, USAc08/20061 aLee, Kwang, Ho1 aStrand, Richard, K. uhttps://simulationresearch.lbl.gov/publications/implementation-earth-tube-system00641nas a2200169 4500008004100000020001800041245009600059210007000155260003000225100002900255700001900284700002000303700002300323700003100346700002100377856007300398 2006 eng d a3-934681-45-X00aMOSILAB: Ein Modelica-Simulationswerkzeug zur energetischen Gebäude- und Anlagensimulation0 aMOSILAB Ein ModelicaSimulationswerkzeug zur energetischen Gebäud aBad Staffelstein, Germany1 aNytsch-Geusen, Christoph1 aNordwig, Andre1 aVetter, Mathias1 aWittwer, Christoph1 aNouidui, Thierry, Stephane1 aSchneider, Peter uhttps://simulationresearch.lbl.gov/publications/mosilab-ein-modelica00634nas a2200181 4500008004100000245008100041210006900122260003100191100001600222700002600238700001300264700001200277700002400289700002200313700002000335700001300355856008400368 2005 eng d00aEffect of Particle Material on the Static Thermal Conductivity of Nanofluids0 aEffect of Particle Material on the Static Thermal Conductivity o aSan Francisco, CAc07/20051 aVijayan, P.1 aBhattacharya, Prajesh1 aNara, S.1 aLai, W.1 aPhelan, Patrick, E.1 aPrasher, Ravi, S.1 aSong, David, W.1 aWang, J. uhttps://simulationresearch.lbl.gov/publications/effect-particle-material-static01543nas a2200217 4500008004100000020001800041245013200059210006900191260003100260520078000291100001301071700002601084700001601110700001201126700001801138700002401156700002201180700002001202700001701222856008601239 2005 eng d a0-7918-4221-500aExperimental Determination of the Effect of Varying Base Fluid and Temperature on the Static Thermal Conductivity of Nanofluids0 aExperimental Determination of the Effect of Varying Base Fluid a aOrlando, FLbASMEc11/20053 a

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

1 aNara, S.1 aBhattacharya, Prajesh1 aVijayan, P.1 aLai, W.1 aRosenthal, W.1 aPhelan, Patrick, E.1 aPrasher, Ravi, S.1 aSong, David, W.1 aWang, Jinlin uhttps://simulationresearch.lbl.gov/publications/experimental-determination-effect00873nas 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-based01573nas a2200217 4500008004100000245009500041210006900136260001200205300001600217490000700233520084100240653001901081653002101100653004601121100002601167700001501193700002001208700002401228700002201252856008101274 2004 eng d00aBrownian Dynamics Simulation to Determine the Effective Thermal Conductivity of Nanofluids0 aBrownian Dynamics Simulation to Determine the Effective Thermal  c06/2004 a6492–64940 v953 a

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

10acomplex fluids10aDisperse systems10aThermal conduction in nonmetallic liquids1 aBhattacharya, Prajesh1 aSaha, S.K.1 aYadav, Ajay, K.1 aPhelan, Patrick, E.1 aPrasher, Ravi, S. uhttps://simulationresearch.lbl.gov/publications/brownian-dynamics-simulation00468nas a2200121 4500008004100000245006200041210006100103260003600164100001900200700002000219700002700239856008000266 2004 eng d00aDevelopment of Trade-Off Equations for EnergyStar Windows0 aDevelopment of TradeOff Equations for EnergyStar Windows aBoulder, Colorado, USAc08/20041 aHuang, Yu, Joe1 aMitchell, Robin1 aSelkowitz, Stephen, E. uhttps://simulationresearch.lbl.gov/publications/development-trade-equations00835nas a2200277 4500008004100000245002600041210002500067260003600092100002300128700002200151700002500173700003000198700002300228700002400251700002400275700002100299700001900320700002600339700001800365700002300383700002100406700002400427700002100451700001500472856007000487 2004 eng d00aEnergyPlus: An Update0 aEnergyPlus An Update aBoulder, Colorado, USAc08/20041 aCrawley, Drury, B.1 aLawrie, Linda, K.1 aPedersen, Curtis, O.1 aWinkelmann, Frederick, C.1 aWitte, Michael, J.1 aStrand, Richard, K.1 aLiesen, Richard, J.1 aBuhl, Walter, F.1 aHuang, Yu, Joe1 aHenninger, Robert, H.1 aGlazer, Jason1 aFisher, Daniel, E.1 aShirley, Don, B.1 aGriffith, Brent, T.1 aEllis, Peter, G.1 aGu, Lixing uhttps://simulationresearch.lbl.gov/publications/energyplus-update00745nas a2200181 4500008004100000245019400041210006900235260002500304100002600329700001600355700001300371700001300384700002400397700002200421700001300443700002000456856008700476 2004 eng d00aEvaluation of the Temperature Oscillation Technique to Calculate Thermal Conductivity of Water and Systematic Measurement of the Thermal Conductivity of Aluminum Oxide – Water Nanofluiids0 aEvaluation of the Temperature Oscillation Technique to Calculate aAnaheim, CAc11/20041 aBhattacharya, Prajesh1 aVijayan, P.1 aTang, T.1 aNara, S.1 aPhelan, Patrick, E.1 aPrasher, Ravi, S.1 aWang, J.1 aSong, David, W. uhttps://simulationresearch.lbl.gov/publications/evaluation-temperature-oscillation01717nas 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-000465nas a2200121 4500008004100000245005400041210005400095260003600149100002400185700002400209700002300233856008700256 2004 eng d00aResources for Teaching Building Energy Simulation0 aResources for Teaching Building Energy Simulation aBoulder, Colorado, USAc08/20041 aStrand, Richard, K.1 aLiesen, Richard, J.1 aWitte, Michael, J. uhttps://simulationresearch.lbl.gov/publications/resources-teaching-building-energy00506nas a2200121 4500008004100000245008400041210006900125260003600194100002100230700002400251700002600275856008300301 2004 eng d00aSimulation of Tubular Daylighting Devices and Daylighting Shelves in EnergyPlus0 aSimulation of Tubular Daylighting Devices and Daylighting Shelve aBoulder, Colorado, USAc08/20041 aEllis, Peter, G.1 aStrand, Richard, K.1 aBaumgartner, Kurt, T. uhttps://simulationresearch.lbl.gov/publications/simulation-tubular-daylighting00573nas a2200145 4500008004100000245010100041210006900142260002700211100002600238700001500264700002000279700002400299700002200323856008200345 2003 eng d00aDetermining the Effective Thermal Conductivity of a Nanofluid Using Brownian Dynamics Simulation0 aDetermining the Effective Thermal Conductivity of a Nanofluid Us aLas Vegas, NVc07/20031 aBhattacharya, Prajesh1 aSaha, S.K.1 aYadav, Ajay, K.1 aPhelan, Patrick, E.1 aPrasher, Ravi, S. uhttps://simulationresearch.lbl.gov/publications/determining-effective-thermal01937nas a2200169 4500008004100000024001500041245006700056210006700123260002900190520137000219100002301589700002001612700001801632700001701650700001301667856008701680 2002 eng d aLBNL-5136500aHVAC Component Data Modeling Using Industry Foundation Classes0 aHVAC Component Data Modeling Using Industry Foundation Classes aLiège, Belgiumc12/20023 a

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

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

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

1 aBazjanac, Vladimir1 aForester, James1 aHaves, Philip1 aSucic, Darko1 aXu, Peng uhttps://simulationresearch.lbl.gov/publications/hvac-component-data-modeling-using00551nas 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-parameter02019nas a2200121 4500008004100000245007200041210006900113260002400182520156300206100002201769700001801791856008801809 2001 eng d00aComparison of Chiller Models for use in Model-Based Fault Detection0 aComparison of Chiller Models for use in ModelBased Fault Detecti aAustin, TXc07/20013 a

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

1 aSreedharan, Priya1 aHaves, Philip uhttps://simulationresearch.lbl.gov/publications/comparison-chiller-models-use-model02170nas a2200217 4500008004100000245007200041210006900113260001200182300001200194490000700206520147200213653002801685653002901713653003001742653002001772653002001792653001701812100002301829700001801852856008201870 2001 eng d00aEfficient Solution Strategies for Building Energy System Simulation0 aEfficient Solution Strategies for Building Energy System Simulat c04/2001 a309-3170 v333 a

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

10abuilding energy systems10acomputational efficiency10agraph theory applications10ahvac simulation10ahvacsim+ models10aspark models1 aSowell, Edward, F.1 aHaves, Philip uhttps://simulationresearch.lbl.gov/publications/efficient-solution-strategies01366nas a2200145 4500008004100000245010700041210006900148260002800217520080900245100001801054700002201072700002001094700001901114856008701133 2001 eng d00aUse of Whole Building Simulation in On-Line Performance Assessment: Modeling and Implementation Issues0 aUse of Whole Building Simulation in OnLine Performance Assessmen aRio de Janeiroc08/20013 a

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

1 aHaves, Philip1 aSalsbury, Tim, I.1 aClaridge, David1 aLiu, Mingsheng uhttps://simulationresearch.lbl.gov/publications/use-whole-building-simulation-line01273nas 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/21/2/12501529nas a2200157 4500008004100000245009000041210006900131300001000200490000600210520097900216100002001195700002501215700002301240700001801263856009001281 2000 eng d00aQualitative Comparison of North American and U.K. Cooling Load Calculation Procedures0 aQualitative Comparison of North American and UK Cooling Load Cal a75-990 v63 a

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

1 aRees, Simon, J.1 aSpitler, Jeffrey, D.1 aDavies, Morris, G.1 aHaves, Philip uhttps://simulationresearch.lbl.gov/publications/qualitative-comparison-north-american02073nas 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-based00471nas 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-commissioning00468nas a2200121 4500008004100000245007400041210006900115490000800184100001800192700002200210700002500232856008900257 1996 eng d00aCondition Monitoring in HVAC Subsystems using First Principles Models0 aCondition Monitoring in HVAC Subsystems using First Principles M0 v1021 aHaves, Philip1 aSalsbury, Tim, I.1 aWright, Jonathan, A. uhttps://simulationresearch.lbl.gov/publications/condition-monitoring-hvac-subsystems01440nas a2200265 4500008004100000024002400041245008600065210006900151250000600220260001600226490000800242520064800250653002100898653001400919653001800933653001300951653001500964653001200979653001400991100001801005700002001023700002201043700002301065856008601088 1996 eng d aPaper no. AT-96-1-100aDevelopment and Testing of a Prototype Tool for HVAC Control System Commissioning0 aDevelopment and Testing of a Prototype Tool for HVAC Control Sys a1 aAtlanta, GA0 v1023 a

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

10aair conditioning10aautomatic10acommissioning10acontrols10aprototypes10atesting10ayear 19961 aHaves, Philip1 aJorgensen, D.R.1 aSalsbury, Tim, I.1 aDexter, Arthur, L. uhttps://simulationresearch.lbl.gov/publications/development-and-testing-prototype00506nas 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-method00600nas 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-fault01768nas a2200169 4500008004100000245009200041210006900133260002500202300001200227490000600239520120000245100001801445700001601463700001801479700001501497856008601512 1982 eng d00aAccuracy of a Simple Method of Estimating the Minimum Temperature of a Sealed Roof Pond0 aAccuracy of a Simple Method of Estimating the Minimum Temperatur aHouston, TXc07/1982 a709-7140 v53 a

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

1 aSchutt, Brady1 aClark, Gene1 aHaves, Philip1 aMerino, M. uhttps://simulationresearch.lbl.gov/publications/accuracy-simple-method-estimating01170nas a2200133 4500008004100000245006500041210006100106260002500167490000800192520072500200100001500925700001800940856007800958 1980 eng d00aThe Thermal Benefits and Cost Effectiveness of Earth Berming0 aThermal Benefits and Cost Effectiveness of Earth Berming aAmherst, MAc10/19800 v5.13 a

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

1 aSpeltz, J.1 aHaves, Philip uhttps://simulationresearch.lbl.gov/publications/thermal-benefits-and-cost00825nas 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-extended01622nas a2200301 4500008004100000245004700041210004300088260001200131300001200143490000800155520072700163653002600890653003200916653001900948653001900967653002300986653004001009653001201049653002501061653002001086653002501106653001801131653002601149100001801175700002201193700002001215856008501235 1974 eng d00aThe Polarization of Radio Sources at 31 CM0 aPolarization of Radio Sources at 31 CM c10/1974 a117-1310 v1693 a

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

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

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

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