01791nas a2200229 4500008004100000245007800041210006900119260001200188520103000200653003101230653002001261653002001281653001401301653001801315653002701333653002701360653002801387100002001415700002301435700002101458856008201479 2019 eng d00aAssessing the Potential to Reduce U.S. Building CO2 Emissions 80% by 20500 aAssessing the Potential to Reduce US Building CO2 Emissions 80 b c08/20193 a

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

10aBuilding energy efficiency10adecarbonization10aelectrification10aemissions10aenergy models10aenergy policy analysis10anational climate goals10apathways building stock1 aLangevin, Jared1 aHarris, Chioke, B.1 aReyna, Janet, L. uhttps://simulationresearch.lbl.gov/publications/assessing-potential-reduce-us02860nas a2200253 4500008004100000022001300041245017500054210006900229260001200298300001400310490000800324520184700332653002402179653000902203653002902212653002602241100001602267700001502283700001802298700002202316700002002338700001502358856023302373 2019 eng d a0306261900aPractical factors of envelope model setup and their effects on the performance of model predictive control for building heating, ventilating, and air conditioning systems0 aPractical factors of envelope model setup and their effects on t c02/2019 a410 - 4250 v2363 a

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

10abuilding simulation10ahvac10aModel predictive control10aSystem identification1 aBlum, David1 aArendt, K.1 aRivalin, Lisa1 aPiette, Mary, Ann1 aWetter, Michael1 aVeje, C.T. uhttps://linkinghub.elsevier.com/retrieve/pii/S0306261918318099https://api.elsevier.com/content/article/PII:S0306261918318099?httpAccept=text/xmlhttps://api.elsevier.com/content/article/PII:S0306261918318099?httpAccept=text/plain02188nas 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-framework02422nas a2200217 4500008004100000022001400041245009700055210006900152260001200221300000900233520152700242653002301769653002201792653002801814653002201842653002501864100001901889700001901908700001801927856025901945 2018 eng d a1570-646X00aA critical review on questionnaire surveys in the field of energy-related occupant behaviour0 acritical review on questionnaire surveys in the field of energyr c07/2018 a1-213 a

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

10abehaviour modeling10aenergy efficiency10aEnergy use in buildings10aoccupant behavior10aquestionnaire survey1 aBelafi, Zsofia1 aHong, Tianzhen1 aReith, Andras uhttp://link.springer.com/10.1007/s12053-018-9711-zhttp://link.springer.com/content/pdf/10.1007/s12053-018-9711-z.pdfhttp://link.springer.com/content/pdf/10.1007/s12053-018-9711-z.pdfhttp://link.springer.com/article/10.1007/s12053-018-9711-z/fulltext.html02103nas a2200181 4500008004100000245008900041210006900130520146500199653003601664653001001700653002301710653002901733653001501762100001901777700001901796700001801815856008801833 2018 eng d00aA Library of Building Occupant Behaviour Models Represented in a Standardised Schema0 aLibrary of Building Occupant Behaviour Models Represented in a S3 a

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

10abuilding performance simulation10aobXML10aOccupant Behaviour10aoccupant behaviour model10aXML schema1 aBelafi, Zsofia1 aHong, Tianzhen1 aReith, Andras uhttps://simulationresearch.lbl.gov/publications/library-building-occupant-behaviour02081nas 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-building02543nas 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/plain00991nas 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-procedures02859nas a2200229 4500008004100000022003900041245011200080210006900192260001200261300001200273490000700285520208600292653002302378653003602401653001502437653002302452653001702475100001902492700001902511700001802530856008102548 2017 eng d aPrint 1996-3599; Online 1996-874400aSmart Building Management vs. Intuitive Human Control — Lessons learnt from an office building in Hungary0 aSmart Building Management vs Intuitive Human Control Lessons lea c12/2017 a811-8280 v103 a

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

10abuilding operation10abuilding performance simulation10acase study10aOccupant Behaviour10aoptimization1 aBelafi, Zsofia1 aHong, Tianzhen1 aReith, Andras uhttps://simulationresearch.lbl.gov/publications/smart-building-management-vs00936nas 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.pdf02384nas 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-system02052nas 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-energy02003nas 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-lighting00650nas a2200181 4500008003900000245010300039210006900142260001200211100002100223700001800244700001500262700002100277700002100298700002100319700002100340700002300361856008400384 2013 d00aTransforming BIM to BEM: Generation of Building Geometry for the NASA Ames Sustainability Base BIM0 aTransforming BIM to BEM Generation of Building Geometry for the  c01/20131 aO'Donnell, James1 aMaile, Tobias1 aRose, Cody1 aMrazovic, Natasa1 aMorrissey, Elmer1 aRegnier, Cynthia1 aParrish, Kristen1 aBazjanac, Vladimir uhttps://simulationresearch.lbl.gov/publications/transforming-bim-bem-generation02060nas a2200277 4500008003900000245009300039210006900132260001200201520117000213653001701383653001801400653001501418653003601433653002301469653001501492100001901507700002301526700001801549700003101567700001701598700001701615700002501632700001701657700002001674856008801694 2012 d00aMonitoring-based HVAC Commissioning of an Existing Office Building for Energy Efficiency0 aMonitoringbased HVAC Commissioning of an Existing Office Buildin c10/20123 a

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

10abenchmarking10acommissioning10aenergyplus10afault detection and diagnostics10afunctional testing10atrend data1 aEarni, Shankar1 aWoodworth, Spencer1 aPang, Xiufeng1 aHernandez-Maldonado, Jorge1 aYin, Rongxin1 aWang, Liping1 aGreenberg, Steve, E.1 aFiegel, John1 aRubalcava, Alma uhttps://simulationresearch.lbl.gov/publications/monitoring-based-hvac-commissioning00620nas a2200169 4500008004100000245008700041210006900128260003100197100002300228700001800251700001500269700002100284700002100305700002100326700002000347856008300367 2011 eng d00aAn Assessment of the use of Building Energy Performance Simulation in Early Design0 aAssessment of the use of Building Energy Performance Simulation  aSydney, Australiac11/20111 aBazjanac, Vladimir1 aMaile, Tobias1 aRose, Cody1 aO'Donnell, James1 aMrazovic, Natasa1 aMorrissey, Elmer1 aWelle, Benjamin uhttps://simulationresearch.lbl.gov/publications/assessment-use-building-energy01832nas a2200229 4500008004100000245007600041210006900117260001200186300001400198490000700212520112800219653001601347653001601363653001301379653001501392653002001407653003201427100001801459700001801477700002101495856008601516 2011 eng d00aCalibrating whole building energy models: An evidence-based methodology0 aCalibrating whole building energy models An evidencebased method c09/2011 a2356-23640 v433 a

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

10acalibration10aMethodology10aretrofit10asimulation10aVersion control10aWhole building energy model1 aRaferty, Paul1 aKeane, Marcus1 aO'Donnell, James uhttps://simulationresearch.lbl.gov/publications/calibrating-whole-building-energy00551nas 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-sem02272nas 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-whole02428nas a2200217 4500008004100000245013000041210006900171300001200240490000600252520155800258653001401816653003301830653003301863653009601896653001701992653004902009100002802058700002002086700002102106856008302127 2010 eng d00aA comparison of global optimization algorithms with standard benchmark functions and real-world applications using EnergyPlus0 acomparison of global optimization algorithms with standard bench a103-1200 v33 a

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

10aalgorithm10aapplication using energyplus10abuilding energy minimization10acovariance matrix adaptation evolution strategy algorithm and hybrid differential evolution10aoptimization10aparticle swarm optimization and hooke-jeeves1 aKämpf, Jérôme, Henri1 aWetter, Michael1 aRobinson, Darren uhttps://simulationresearch.lbl.gov/publications/comparison-global-optimization00514nas a2200133 4500008004100000245009100041210006900132260002000201100001800221700001800239700002100257700001800278856008400296 2010 eng d00aEnergy Monitoring Systems value, issues and recommendations based on five case studies0 aEnergy Monitoring Systems value issues and recommendations based aAntalya, Turkey1 aRaferty, Paul1 aKeane, Marcus1 aO'Donnell, James1 aCosta, Andrea uhttps://simulationresearch.lbl.gov/publications/energy-monitoring-systems-value01151nas a2200145 4500008004100000245008900041210006900130260002200199520065200221100001800873700001800891700001800909700002100927856005700948 2009 eng d00aKey Factors - Methodology for Enhancement and Support of Building Energy Performance0 aKey Factors Methodology for Enhancement and Support of Building  aGlasgow, Scotland3 a

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

1 aCosta, Andrea1 aKeane, Marcus1 aRaferty, Paul1 aO'Donnell, James uhttp://zuse.ucc.ie/iruse/papersNew/AndreaGlasgow.pdf00477nas a2200145 4500008004100000245004300041210003000084260002700114100001700141700001500158700002300173700002600196700001500222856009400237 2009 eng d00a“The Monitoring,” Panel: Chill-Off0 aMonitoring Panel ChillOff aSunnyvale, CAc10/20091 aNelson, Dean1 aDay, Brian1 aBell, Geoffrey, C.1 aBhattacharya, Prajesh1 aRyan, Mike uhttps://simulationresearch.lbl.gov/publications/%E2%80%9C-monitoring%E2%80%9D-panel-chill02848nas a2200145 4500008004100000024002000041245004500061210004500106260002400151520237200175100002102547700002202568700002202590856009002612 2008 eng d aESL-HH-08-12-2700aReducing Energy Use In Florida Buildings0 aReducing Energy Use In Florida Buildings aDallas, TXc12/20083 a

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

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

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

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

1 aRaustad, Richard1 aBasarkar, Mangesh1 aVieira, Robin, K. uhttps://simulationresearch.lbl.gov/publications/reducing-energy-use-florida-buildings00480nas a2200121 4500008004100000245008900041210006900130260001200199100002400211700002500235700001500260856008300275 2006 eng d00aAssessment of the Technical Potential for Achieving Zero-Energy Commercial Buildings0 aAssessment of the Technical Potential for Achieving ZeroEnergy C c08/20061 aGriffith, Brent, T.1 aTorcellini, Paul, A.1 aRyan, John uhttps://simulationresearch.lbl.gov/publications/assessment-technical-potential02129nas 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-direct00526nas a2200121 4500008004100000245008900041210006900130260003200199100003100231700002700262700002700289856008800316 2006 eng d00aLow Energy Cooling Technologies for Sub-Tropical/Warm Humid Climate Building Systems0 aLow Energy Cooling Technologies for SubTropicalWarm Humid Climat aCambridge, MA, USAc08/20061 aChowdhury, Ashfaque, Ahmed1 aRasul, Mohammad, Golam1 aKamal, Mohammad, Masud uhttps://simulationresearch.lbl.gov/publications/low-energy-cooling-technologies-sub01543nas 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-effect00476nas a2200109 4500008004100000245009800041210006900139260003000208100002300238700002000261856008500281 2005 eng d00aModeling Ground Source Heat Pump Systems in a Building Energy Simulation Program (EnergyPlus)0 aModeling Ground Source Heat Pump Systems in a Building Energy Si aMontreal, canadac08/20051 aFisher, Daniel, E.1 aRees, Simon, J. uhttps://simulationresearch.lbl.gov/publications/modeling-ground-source-heat-pump01389nas a2200229 4500008004100000245009200041210006900133260001200202300001200214490000700226520069500233653002100928653002500949653002900974653001101003653001801014653001601032653001501048100002001063700001801083856005801101 2001 eng d00aA Nodal Model for Displacement Ventilation and Chilled Ceiling Systems in Office Spaces0 aNodal Model for Displacement Ventilation and Chilled Ceiling Sys c07/2001 a753-7620 v363 a

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

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

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

1 aRees, Simon, J.1 aMcGuirk, James, J.1 aHaves, Philip uhttp://www.sciencedirect.com/science/article/pii/S001793100000348301273nas 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-american01143nas a2200121 4500008004100000245009200041210006900133260002600202520069700228100002000925700001800945856005800963 1999 eng d00aA Nodal Model for Displacement Ventilation and Chilled Ceiling Systems in Office Spaces0 aNodal Model for Displacement Ventilation and Chilled Ceiling Sys aKyoto, Japanc09/19993 a

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

1 aRees, Simon, J.1 aHaves, Philip uhttp://www.ibpsa.org/proceedings/BS1999/BS99_D-05.pdf01646nas 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-000484nas a2200109 4500008004100000245011100041210006900152260002500221100002000246700001800266856009000284 1995 eng d00aA Model of a Displacement Ventilation/Chilled Ceiling Cooling System Suitable for Annual Energy Simulation0 aModel of a Displacement VentilationChilled Ceiling Cooling Syste aMadison, WIc08/19951 aRees, Simon, J.1 aHaves, Philip uhttps://simulationresearch.lbl.gov/publications/model-displacement-ventilationchilled00453nas a2200121 4500008004100000245005900041210005900100260002700159100001800186700002000204700001900224856008800243 1995 eng d00aModelling and Simulation of Low Energy Cooling Systems0 aModelling and Simulation of Low Energy Cooling Systems aBejing, Chinac09/19951 aHaves, Philip1 aRees, Simon, J.1 aHarrington, L. uhttps://simulationresearch.lbl.gov/publications/modelling-and-simulation-low-energy00422nas a2200121 4500008004100000245004900041210004900090260002600139100001800165700001400183700001600197856008700213 1992 eng d00aClimate Change and Passive Cooling in Europe0 aClimate Change and Passive Cooling in Europe aAuckland, New Zealand1 aHaves, Philip1 aKenny, G.1 aRoaf, Susan uhttps://simulationresearch.lbl.gov/publications/climate-change-and-passive-cooling00489nas a2200133 4500008004100000020001500041245005600056210005600112260005000168100001800218700001600236700002200252856008100274 1992 eng d a047021952100aEnvironmental Control in Energy Efficient Buildings0 aEnvironmental Control in Energy Efficient Buildings aOxfordbBlackwell Scientific Publications Ltd1 aHaves, Philip1 aRoaf, Susan1 aHancock, Mary, E. uhttps://simulationresearch.lbl.gov/publications/environmental-control-energy