00542nas a2200133 4500008004100000245013400041210006900175490000800244100001900252700002000271700001800291700001700309856008200326 2018 eng d00aBidirectional low temperature district energy systems with agent-based control: Performance comparison and operation optimization0 aBidirectional low temperature district energy systems with agent0 v2091 aBunning, Felix1 aWetter, Michael1 aFuchs, Marcus1 aMuller, Dirk uhttps://simulationresearch.lbl.gov/publications/bidirectional-low-temperature01824nas a2200205 4500008004100000245004000041210003900081490000700120520119400127653002401321653002401345653003601369653002201405653002001427653003001447100001901477700002001496700001501516856008701531 2018 eng d00aBuilding Simulation: Ten Challenges0 aBuilding Simulation Ten Challenges0 v113 a

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

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

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

10amodelica10aModelica Buildings Library10aModelica Occupants Package10aOccupant Behaviour10aOccupant behaviour modelling1 aWang, Zhe1 aHong, Tianzhen1 aJia, Ruoxi uhttps://www.tandfonline.com/doi/full/10.1080/19401493.2018.1543352https://www.tandfonline.com/doi/pdf/10.1080/19401493.2018.154335201503nas a2200181 4500008003900000245009000039210006900129520087000198653003801068653002101106653002701127653002001154100001401174700001201188700001901200700001601219856008601235 2013 d00aBuilding energy modeling programs comparison Research on HVAC systems simulation part0 aBuilding energy modeling programs comparison Research on HVAC sy3 a

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

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

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

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

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

Key research findings were summarized as follows:

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

1 aHong, Tianzhen1 aFeng, Wei1 aLu, Alison1 aXia, Jianjun1 aYang, Le1 aShen, Qi1 aIm, Piljae1 aBhandari, Mahabir uhttps://simulationresearch.lbl.gov/publications/building-energy-monitoring-and01404nas a2200169 4500008003900000245008200039210006900121260001200190520081400202100001801016700002601034700003101060700002001091700001701111700001801128856008801146 2011 d00aBacNet and Analog/Digital Interfaces of the Building Controls Virtual Testbed0 aBacNet and AnalogDigital Interfaces of the Building Controls Vir c11/20113 a

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

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

1 aHaves, Philip1 aBhattacharya, Prajesh1 aNouidui, Thierry, Stephane1 aWetter, Michael1 aLi, Zhengwei1 aPang, Xiufeng uhttps://simulationresearch.lbl.gov/publications/bacnet-and-analogdigital-interfaces00629nas a2200169 4500008004100000245008300041210006900124260003100193300001500224100003100239700002000270700001700290700001800307700002600325700001800351856009000369 2011 eng d00aBACnet and Analog/Digital Interfaces of the Building Controls Virtual Test Bed0 aBACnet and AnalogDigital Interfaces of the Building Controls Vir aSydney, Australiac11/2011 ap. 294-3011 aNouidui, Thierry, Stephane1 aWetter, Michael1 aLi, Zhengwei1 aPang, Xiufeng1 aBhattacharya, Prajesh1 aHaves, Philip uhttps://simulationresearch.lbl.gov/publications/bacnet-and-analogdigital-interfaces-000396nas a2200133 4500008004100000245002700041210002700068100001800095700001800113700002100131700002000152700001500172856007500187 2010 eng d00aBuildWise Final Report0 aBuildWise Final Report1 aKeane, Marcus1 aCosta, Andrea1 aO'Donnell, James1 aMenzel, Karsten1 aDirk, Alan uhttps://simulationresearch.lbl.gov/publications/buildwise-final-report02680nas a2200133 4500008004100000245008800041210006900129260003600198520216900234100001802403700002202421700002002443856008302463 2008 eng d00aBenchmarking and Equipment and Controls Assessment for a ‘Big Box’ Retail Chain0 aBenchmarking and Equipment and Controls Assessment for a Big Box aAsilomar, California, USAc20083 a

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

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

1 aHaves, Philip1 aCoffey, Brian, E.1 aWilliams, Scott uhttps://simulationresearch.lbl.gov/publications/benchmarking-and-equipment-and01584nas a2200169 4500008004100000245014200041210006900183260001800252520098100270653001301251653002301264653002501287653001201312100001801324700001301342856005901355 2007 eng d00aThe Building Controls Virtual Test Bed – a Simulation Environment for Developing and Testing Control Algorithms, Strategies and Systems0 aBuilding Controls Virtual Test Bed a Simulation Environment for  aBejing, China3 a

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

10acontrols10adevelopment system10ahardware-in-the-loop10atesting1 aHaves, Philip1 aXu, Peng uhttp://www.ibpsa.org/proceedings/BS2007/p748_final.pdf00529nas a2200133 4500008004100000245010800041210006900149300001200218490000800230100002200238700002600260700002400286856008500310 2006 eng d00aBrownian Motion Based Convective- Conductive Model for the Effective Thermal Conductivity of Nanofluids0 aBrownian Motion Based Convective Conductive Model for the Effect a588-5950 v1281 aPrasher, Ravi, S.1 aBhattacharya, Prajesh1 aPhelan, Patrick, E. uhttps://simulationresearch.lbl.gov/publications/brownian-motion-based-convective01926nas a2200133 4500008004100000245011300041210006900154300001200223490000700235520142300242100002001665700001801685856008901703 2005 eng d00aBuilding design optimization using a convergent pattern search algorithm with adaptive precision simulations0 aBuilding design optimization using a convergent pattern search a a603-6120 v373 a

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

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

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

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

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

1 aWetter, Michael uhttps://simulationresearch.lbl.gov/publications/buildopt-new-building-energy-001573nas a2200217 4500008004100000245009500041210006900136260001200205300001600217490000700233520084100240653001901081653002101100653004601121100002601167700001501193700002001208700002401228700002201252856008101274 2004 eng d00aBrownian Dynamics Simulation to Determine the Effective Thermal Conductivity of Nanofluids0 aBrownian Dynamics Simulation to Determine the Effective Thermal  c06/2004 a6492–64940 v953 a

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

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

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

1 aWetter, Michael uhttps://simulationresearch.lbl.gov/publications/buildopt-new-building-energy01863nas a2200193 4500008004100000024001500041245007000056210006900126260002800195520122600223100001801449700001901467700001901486700002201505700001601527700001801543700001801561856009001579 2000 eng d aLBNL-4845600aBetter IAQ Through Integrating Design Tools For The HVAC Industry0 aBetter IAQ Through Integrating Design Tools For The HVAC Industr aEspoo, Finlandc08/20003 a

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

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

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

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

10abuilding simulation1 aHong, Tianzhen1 aChou, Siaw, K.1 aBong, T.Y. uhttps://simulationresearch.lbl.gov/publications/building-simulation-overview