02297nas a2200241 4500008004100000022001300041245010400054210006900158260001200227300001400239490000800253520153900261653001601800653001801816653002401834653003301858653001901891653002301910100001401933700001901947700002201966856006701988 2019 eng d a0306261900aData fusion in predicting internal heat gains for office buildings through a deep learning approach0 aData fusion in predicting internal heat gains for office buildin c02/2019 a386 - 3980 v2403 a

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

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

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

10aCity building dataset10aCityGML10aData mapping10aData standards10aUrban Building Energy Modeling1 aChen, Yixing1 aHong, Tianzhen1 aLuo, Xuan1 aHooper, Barry uhttps://linkinghub.elsevier.com/retrieve/pii/S0378778818316852https://api.elsevier.com/content/article/PII:S0378778818316852?httpAccept=text/xmlhttps://api.elsevier.com/content/article/PII:S0378778818316852?httpAccept=text/plain02405nas a2200217 4500008004100000245009900041210006900140520168500209653001901894653002301913653002301936653002101959653001701980653002701997100001202024700001902036700001202055700001502067700001702082856008802099 2017 eng d00aData Analytics and Optimization of an Ice-Based Energy Storage System for Commercial Buildings0 aData Analytics and Optimization of an IceBased Energy Storage Sy3 a

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

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

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

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

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

1 avan der Heijde, Brahm1 aFuchs, Marcus1 aTugores, Carles, Ribas1 aSchweiger, Gerald1 aSartor, Kevin1 aBasciotti, Daniele1 aMuller, Dirk1 aNytsch-Geusen, Christoph1 aWetter, Michael1 aHelsen, Lieve uhttps://simulationresearch.lbl.gov/publications/dynamic-equation-based-thermo02384nas a2200253 4500008003900000245010000039210006900139260001200208300001200220490000700232520158600239653002401825653001501849653002201864653002201886653002101908653002501929653002401954100001401978700001201992700001902004700001702023856009002040 2015 d00aData Analysis and Stochastic Modeling of Lighting Energy Use in Large Office Buildings in China0 aData Analysis and Stochastic Modeling of Lighting Energy Use in  c01/2015 a275-2870 v863 a

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

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

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

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

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

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

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

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

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

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

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

10abuilding simulation10aenergy modeling10aenergyplus10aHeat pump10amodel validation10aVariable refrigerant flow1 aHong, Tianzhen1 aSun, Kaiyu1 aZhang, Rongpeng1 aHinokuma, Ryohei1 aKasahara, Shinichi1 aYura, Yoshinori uhttps://simulationresearch.lbl.gov/publications/development-and-validation-new03531nas a2200241 4500008003900000245007900039210006900118260002200187300001100209490000800220520280200228653001403030653001503044653002403059653001503083653003103098653001303129100001903142700001303161700001603174700001403190856008503204 2014 d00aData and Analytics to Inform Energy Retrofit of High Performance Buildings0 aData and Analytics to Inform Energy Retrofit of High Performance bElsevierc08/2014 a90-1060 v1263 a

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

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

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

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

Project 1 consisted of administrative tasks related to the project.

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

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

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

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

10aapplication programming interface10afault detection and diagnosis10aM&V10aMeasurement and verification10aUniversal Translator1 aHaves, Philip1 aWray, Craig, P.1 aJump, David, A.1 aVeronica, Daniel1 aFarley, Christopher uhttps://simulationresearch.lbl.gov/publications/development-diagnostic-and02003nas a2200217 4500008003900000245008000039210006900119520131400188653002401502653001501526653001301541653001301554653002201567653002101589653002501610100001401635700001201649700001701661700001901678856008801697 2013 d00aData Analysis and Modeling of Lighting Energy Use in Large Office Buildings0 aData Analysis and Modeling of Lighting Energy Use in Large Offic3 a

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

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

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

10abuilding energy modeling program10abuilding thermal loads10acomparison10adest10aDOE-2.1E10aenergyplus1 aZhu, Dandan1 aHong, Tianzhen1 aYan, Da1 aWang, Chuang uhttps://simulationresearch.lbl.gov/publications/detailed-loads-comparison-three00551nas a2200145 4500008004100000245008000041210006900121260002900190100002300219700001800242700002100260700001500281700002100296856008800317 2011 eng d00aData Enviroments and Processing in Sem-Automated Simulation with EnergyPlus0 aData Enviroments and Processing in SemAutomated Simulation with  aSophia Antipolis, France1 aBazjanac, Vladimir1 aMaile, Tobias1 aO'Donnell, James1 aRose, Cody1 aMrazovic, Natasa uhttps://simulationresearch.lbl.gov/publications/data-enviroments-and-processing-sem00610nas a2200157 4500008004100000245009600041210006900137260003100206100001700237700001800254700002500272700002200297700002100319700002200340856009000362 2011 eng d00aDevelopment of a user interface for the EnergyPlus whole building energy simulation program0 aDevelopment of a user interface for the EnergyPlus whole buildin aSydney, Australiac11/20111 aSee, Richard1 aHaves, Philip1 aSreekanathan, Pramod1 aBasarkar, Mangesh1 aO'Donnell, James1 aSettlemyre, Kevin uhttps://simulationresearch.lbl.gov/publications/development-user-interface-energyplus02003nas a2200193 4500008004100000022001800041245011000059210006900169260004100238520131100279100002201590700001801612700002001630700002001650700002401670700001501694700001801709856008201727 2010 eng d a0-918249-60-000aDevelopment and Testing of Model Predictive Control for a Campus Chilled Water Plant with Thermal Storage0 aDevelopment and Testing of Model Predictive Control for a Campus aAsilomar, California, USAbOmnipress3 a

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

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

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

1 aVictor, Norrefeldt1 aNouidui, Thierry, Stephane1 aGruen, Gunnar uhttps://simulationresearch.lbl.gov/publications/development-isothermal-2d-zonal-air00965nas a2200181 4500008004100000020002300041245006700064210006700131260002500198520039100223653001100614653001700625653001700642100001900659700001900678700002100697856006500718 2008 eng d a978-0-86341-894-5 00aDesign of Underlying Network Infrastructure of Smart Buildings0 aDesign of Underlying Network Infrastructure of Smart Buildings aSeattle, WAc07/20083 a

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

10adesign10aoptimisation10aWireless BMS1 aMcGibney, Alan1 aKlepal, Martin1 aO'Donnell, James uhttp://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=462979000417nas a2200109 4500008004100000245006400041210006400105260001200169100001700181700002000198856008900218 2007 eng d00aDiscussion of strategies for UK zero energy building design0 aDiscussion of strategies for UK zero energy building design c09/20071 aWang, Liping1 aGwilliam, Julie uhttps://simulationresearch.lbl.gov/publications/discussion-strategies-uk-zero-energy02129nas a2200157 4500008004100000245011200041210006900153260001600222520154600238100001901784700001601803700002201819700002101841700002101862856008801883 2006 eng d00aDehumidification Enhancement of Direct Expansion Systems through Component Augmentation of the Cooling Coil0 aDehumidification Enhancement of Direct Expansion Systems through aOrlando, FL3 a

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

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

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

1 aHaves, Philip1 aHitchcock, Robert, J.1 aGillespie, Kenneth, L.1 aBrook, Martha1 aShockman, Christine1 aDeringer, Joseph, J1 aKinney, Kristopher, L. uhttp://www.aceee.org/proceedings-paper/ss06/panel03/paper1000582nas a2200133 4500008004100000245012900041210006900170260003600239100002000275700002200295700002200317700002200339856008700361 2006 eng d00aDynamic Controls for Energy Efficiency and Demand Response: Framework Concepts and a New Construction Case Study in New York0 aDynamic Controls for Energy Efficiency and Demand Response Frame aPacific Grove, CA, USAc08/20061 aKiliccote, Sila1 aPiette, Mary, Ann1 aWatson, David, S.1 aHughes, Glenn, D. uhttps://simulationresearch.lbl.gov/publications/dynamic-controls-energy-efficiency00511nas a2200121 4500008004100000245008500041210006900126260003000195100003500225700002100260700001800281856009000299 2005 eng d00aDesign of the Natural Ventilation System for the New San Diego Children's Museum0 aDesign of the Natural Ventilation System for the New San Diego C aMontreal, Canadac08/20051 ada Graça, Guilherme, Carrilho1 aLinden, Paul, F.1 aBrook, Martha uhttps://simulationresearch.lbl.gov/publications/design-natural-ventilation-system-new01971nas a2200157 4500008004100000024001500041245009400056210006900150300001200219490000700231520145700238100003501695700002101730700001801751856004401769 2004 eng d aLBNL-5601000aDesign and Testing of a Control Strategy for a Large Naturally Ventilated Office Building0 aDesign and Testing of a Control Strategy for a Large Naturally V a223-2390 v253 aThe design for the new Federal Building for San Francisco includes an office tower that is to be naturally ventilated. Each floor is designed to be cross-ventilated, through upper windows that are controlled by the building management system. Users have control over lower level windows, which can be as much as 50% of the total openable area. There are significant differences in the performance and the control of the windward and leeward sides of the building, and separate monitoring and control strategies are determined for each side. The performance and control of the building has been designed and tested using a modified version of EnergyPlus. Results from studies with EnergyPlus and computational fluid dynamics are used in designing the control strategy. Wind-driven cross-ventilation produces a main jet through the upper openings of the building, across the ceiling from the windward to the leeward side. Below this jet, the occupied regions are subject to a recirculating airflow. Results show that temperatures within the building are predicted to be satisfactory, provided a suitable control strategy is implemented that uses night cooling in periods of hot weather. The control strategy has 10 window opening modes. EnergyPlus was extended to simulate the effects of these modes, and to assess the effects of different forms of user behaviour. The results show how user behaviour can significantly influence the building performance.1 ada Graça, Guilherme, Carrilho1 aLinden, Paul, F.1 aHaves, Philip uhttp://bse.sagepub.com/content/25/3/22302088nas a2200157 4500008004100000050001500041245009400056210006900150300001200219490000700231520153000238100003501768700002101803700001801824856008801842 2004 eng d aLBNL-5601000aDesign and Testing of a Control Strategy for a Large Naturally Ventilated Office Building0 aDesign and Testing of a Control Strategy for a Large Naturally V a211-2210 v253 a

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

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

1 ada Graça, Guilherme, Carrilho1 aLinden, Paul, F.1 aHaves, Philip uhttps://simulationresearch.lbl.gov/publications/design-and-testing-control-strategy00504nas a2200121 4500008004100000245009000041210006900131260002600200100002600226700002400252700002200276856008400298 2004 eng d00aDetermining the Effective Viscosity of a Nanofluid Using Brownian Dynamics Simulation0 aDetermining the Effective Viscosity of a Nanofluid Using Brownia aHonolulu, HIc03/20041 aBhattacharya, Prajesh1 aPhelan, Patrick, E.1 aPrasher, Ravi, S. uhttps://simulationresearch.lbl.gov/publications/determining-effective-viscosity00572nas a2200169 4500008004100000245006500041210006500106260000900171300001200180490000700192653001500199653004000214100002000254700001900274700002200293856008700315 2004 eng d00aDevelopment of a Thermal Energy Storage Model for EnergyPlus0 aDevelopment of a Thermal Energy Storage Model for EnergyPlus c2004 a807-8140 v3610aenergyplus10athermal energy storage (tes) system1 aIhm, Pyeongchan1 aKrarti, Moncef1 aHenze, Gregor, P. uhttps://simulationresearch.lbl.gov/publications/development-thermal-energy-storage00468nas a2200121 4500008004100000245006200041210006100103260003600164100001900200700002000219700002700239856008000266 2004 eng d00aDevelopment of Trade-Off Equations for EnergyStar Windows0 aDevelopment of TradeOff Equations for EnergyStar Windows aBoulder, Colorado, USAc08/20041 aHuang, Yu, Joe1 aMitchell, Robin1 aSelkowitz, Stephen, E. uhttps://simulationresearch.lbl.gov/publications/development-trade-equations00585nas a2200145 4500008004100000024001500041245009400056210006900150260003600219100003500255700002100290700002000311700001800331856009000349 2003 eng d aLBNL-5601000aDesign and Testing of a Control Strategy for a Large Naturally Ventilated Office Building0 aDesign and Testing of a Control Strategy for a Large Naturally V aEindhoven, Netherlandsc08/20031 ada Graça, Guilherme, Carrilho1 aLinden, Paul, F.1 aMcConahey, Erin1 aHaves, Philip uhttps://simulationresearch.lbl.gov/publications/design-and-testing-control-strategy-100573nas a2200145 4500008004100000245010100041210006900142260002700211100002600238700001500264700002000279700002400299700002200323856008200345 2003 eng d00aDetermining the Effective Thermal Conductivity of a Nanofluid Using Brownian Dynamics Simulation0 aDetermining the Effective Thermal Conductivity of a Nanofluid Us aLas Vegas, NVc07/20031 aBhattacharya, Prajesh1 aSaha, S.K.1 aYadav, Ajay, K.1 aPhelan, Patrick, E.1 aPrasher, Ravi, S. uhttps://simulationresearch.lbl.gov/publications/determining-effective-thermal01526nas a2200145 4500008004100000245008300041210006900124260002400193520099600217100002201213700002201235700001501257700001801272856009001290 2001 eng d00aDemand Relief and Weather Sensitivity in Large California Commercial Buildings0 aDemand Relief and Weather Sensitivity in Large California Commer aAustin, TXc07/20013 a

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

1 aKinney, Satkartar1 aPiette, Mary, Ann1 aGu, Lixing1 aHaves, Philip uhttps://simulationresearch.lbl.gov/publications/demand-relief-and-weather-sensitivity01723nas a2200217 4500008004100000245005700041210005500098260001200153300001200165490000700177520108800184653002401272653001501296653001001311653002601321653001701347100001901364700001901383700001501402856008801417 1999 eng d00aA design day for building load and energy estimation0 adesign day for building load and energy estimation c07/1999 a469-4770 v343 a

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

10abuilding simulation10adesign day10adoe-210apeak load calculation10aweather data1 aHong, Tianzhen1 aChou, Siaw, K.1 aBong, T.Y. uhttps://simulationresearch.lbl.gov/publications/design-day-building-load-and-energy01440nas a2200265 4500008004100000024002400041245008600065210006900151250000600220260001600226490000800242520064800250653002100898653001400919653001800933653001300951653001500964653001200979653001400991100001801005700002001023700002201043700002301065856008601088 1996 eng d aPaper no. AT-96-1-100aDevelopment and Testing of a Prototype Tool for HVAC Control System Commissioning0 aDevelopment and Testing of a Prototype Tool for HVAC Control Sys a1 aAtlanta, GA0 v1023 a

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

10aair conditioning10aautomatic10acommissioning10acontrols10aprototypes10atesting10ayear 19961 aHaves, Philip1 aJorgensen, D.R.1 aSalsbury, Tim, I.1 aDexter, Arthur, L. uhttps://simulationresearch.lbl.gov/publications/development-and-testing-prototype00980nas a2200109 4500008004100000245007100041210006900112260002500181520058600206100001800792856006000810 1995 eng d00aDetailed Modelling and Simulation of a VAV Air-Conditioning System0 aDetailed Modelling and Simulation of a VAV AirConditioning Syste aMadison, WIc08/19953 aThe paper describes a component-based dynamic simulation of a variable air volume (VAV) airconditioning system. The model is based closely on the design of one floor of a real commercial office building in London. The model includes an air handling unit and a duct system incorporating pressure-independent VAV boxes. The paper describes the simulation environment used to test control systems and to develop fault detection and diagnosis procedures and presents results of simulations that illustrate how the simulation can be used to study the interactions between control loops.1 aHaves, Philip uhttp://www.ibpsa.org/proceedings/BS1995/BS95_056_63.pdf00474nas a2200121 4500008004100000245008700041210006900128490000800197100001900205700001800224700002000242856009000262 1994 eng d00aDesign, Construction and Commissioning of Building Emulators for EMCS Applications0 aDesign Construction and Commissioning of Building Emulators for 0 v1001 aWang, Shengwei1 aHaves, Philip1 aNusgens, Pierre uhttps://simulationresearch.lbl.gov/publications/design-construction-and-commissioning00488nas a2200121 4500008004100000245008500041210006900126260002800195100002300223700001800246700002000264856008200284 1993 eng d00aDevelopment of Techniques to Assist in the Commissioning of HVAC Control Systems0 aDevelopment of Techniques to Assist in the Commissioning of HVAC aManchester, UKc05/19931 aDexter, Arthur, L.1 aHaves, Philip1 aJorgensen, D.R. uhttps://simulationresearch.lbl.gov/publications/development-techniques-assist01357nas a2200145 4500008004100000245006500041210006400106260001200170300001200182490000600194520088100200100001801081700002501099856008701124 1988 eng d00aDaylight in Dynamic Thermal Modelling Programs: a Case Study0 aDaylight in Dynamic Thermal Modelling Programs a Case Study c11/1988 a183-1880 v93 a

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

1 aHaves, Philip1 aLittlefair, Paul, J. uhttps://simulationresearch.lbl.gov/publications/daylight-dynamic-thermal-modelling00432nas a2200109 4500008004100000245006600041210006500107260002500172100002400197700001800221856008300239 1986 eng d00aDevelopment of SERI-RES within the UK Passive Solar Programme0 aDevelopment of SERIRES within the UK Passive Solar Programme aBoulder, COc06/19861 aLittler, John, G.F.1 aHaves, Philip uhttps://simulationresearch.lbl.gov/publications/development-seri-res-within-uk00671nas a2200193 4500008003900000245006700039210006200106260004300168490000800211100002400219700002100243700002400264700001700288700001600305700002200321700002100343700003000364856008300394 1985 d00aThe DOE-2 Computer Program for Thermal Simulation of Buildings0 aDOE2 Computer Program for Thermal Simulation of Buildings bAmerican Institute of Physicsc01/19850 v1351 aBirdsall, Bruce, E.1 aBuhl, Walter, F.1 aCurtis, Richard, B.1 aErdem, Ender1 aEto, Joseph1 aHirsch, James, J.1 aOlson, Karen, H.1 aWinkelmann, Frederick, C. uhttps://simulationresearch.lbl.gov/publications/doe-2-computer-program-thermal00595nas a2200181 4500008003900000245004700039210004200086260002300128100002400151700002400175700002100199700001700220700002000237700002200257700002100279700003000300856008300330 1984 d00aThe DOE-2 Building Energy Analysis Program0 aDOE2 Building Energy Analysis Program aSingaporec05/19841 aCurtis, Richard, B.1 aBirdsall, Bruce, E.1 aBuhl, Walter, F.1 aErdem, Ender1 aEto, Joseph, H.1 aHirsch, James, J.1 aOlson, Karen, H.1 aWinkelmann, Frederick, C. uhttps://simulationresearch.lbl.gov/publications/doe-2-building-energy-analysis00493nas a2200121 4500008004100000245008400041210006900125260002700194100001800221700002100239700002200260856008900282 1982 eng d00aDehumidification and Passive Cooling for Retrofit and Conventional Construction0 aDehumidification and Passive Cooling for Retrofit and Convention aKnoxville, TNc07/19821 aHaves, Philip1 aLoxsom, Fred, M.1 aDoderer, Earl, S. uhttps://simulationresearch.lbl.gov/publications/dehumidification-and-passive-cooling00512nas a2200109 4500008004100000245014100041210006900182260002300251100002200274700001800296856008800314 1981 eng d00aDesign and Operating Strategies and Sizing Relationships for Solar Regenerated Desiccant Dehumidifiers Used with Passive Cooling Systems0 aDesign and Operating Strategies and Sizing Relationships for Sol aMiami, FLc11/19811 aNelson, Peter, E.1 aHaves, Philip uhttps://simulationresearch.lbl.gov/publications/design-and-operating-strategies-and