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词条 Building performance simulation
释义

  1. Introduction

  2. History

  3. Accuracy

  4. Technological aspects

  5. Applications

  6. Software tools

  7. BPS in practice

  8. Performance-based compliance

  9. Professional associations and certifications

  10. See also

  11. References

  12. External links

{{about|performance simulation in buildings|computer simulation in general|Computer simulation|the modeling of energy systems more generally|Energy modeling}}

Building performance simulation (BPS) is the replication of aspects of building performance using a computer-based, mathematical model created on the basis of fundamental physical principles and sound engineering practice. The objective of building performance simulation is the quantification of aspects of building performance which are relevant to the design, construction, operation and control of buildings.[1] Building performance simulation has various sub-domains; most prominent are thermal simulation, lighting simulation, acoustical simulation and air flow simulation. Most building performance simulation is based on the use of bespoke simulation software. Building performance simulation itself is a field within the wider realm of scientific computing.

Introduction

From a physical point of view, a building is a very complex system, influenced by a wide range of parameters. A simulation model is an abstraction of the real building which allows to consider the influences on high level of detail and to analyze key performance indicators without cost-intensive measurements. BPS is a technology of considerable potential that provides the ability to quantify and compare the relative cost and performance attributes of a proposed design in a realistic manner and at relatively low effort and cost. Energy demand, indoor environmental quality (incl. thermal and visual comfort, indoor air quality and moisture phenomena), HVAC and renewable system performance, urban level modeling, building automation, and operational optimization are important aspects of BPS.[2][3][4]

Over the last six decades, numerous BPS computer programs have been developed. The most comprehensive listing of BPS software can be found in the BEST directory.[5] Some of them only cover certain parts of BPS (e.g. climate analysis, thermal comfort, energy calculations, plant modeling, daylight simulation etc.). The core tools in the field of BPS are multi-domain, dynamic, whole-building simulation tools, which provide users with key indicators such as heating and cooling load, energy demand, temperature trends, humidity, thermal and visual comfort indicators, air pollutants, ecological impact and costs.[4][6]

A typical building simulation model has inputs for local weather; building geometry; building envelope characteristics; internal heat gains from lighting, occupants and equipment loads; heating, ventilation, and cooling (HVAC) system specifications; operation schedules and control strategies.[2] The ease of input and accessibility of output data varies widely between BPS tools. Advanced whole-building simulation tools are able to consider almost all of the following in some way with different approaches.

Necessary input data for a whole-building simulation:

  • Climate: ambient air temperature, relative humidity, direct and diffuse solar radiation, wind speed and direction
  • Site: location and orientation of the building, shading by topography and surrounding buildings, ground properties
  • Geometry: building shape and zone geometry
  • Envelope: materials and constructions, windows and shading, thermal bridges, infiltration and openings
  • Internal gains: lights, equipment and occupants including schedules for operation/occupancy
  • Ventilation system: transport and conditioning (heating, cooling, humidification) of air
  • Room units: local units for heating, cooling and ventilation
  • Plant: Central units for transformation, storage and delivery of energy to the building
  • Controls: for window opening, shading devices, ventilation systems, room units, plant components

Some examples for key performance indicators:

  • Temperature trends: in zones, on surfaces, in construction layers, for hot or cold water supply or in double glass facades
  • Comfort indicators: like PMV and PPD, radiant temperature asymmetry, CO2-concentration, relative humidity
  • Heat balances: for zones, the whole building or single plant components
  • Load profiles: for heating and cooling demand, electricity profile for equipment and lighting
  • Energy demand: for heating, cooling, ventilation, light, equipment, auxiliary systems (e.g. pumps, fans, elevators)
  • Daylight availability: in certain zone areas, at different time points with variable outside conditions

Other use of BPS software

  • System sizing: for HVAC components like air handling units, heat exchanger, boiler, chiller, water storage tanks, heat pumps and renewable energy systems.
  • Optimizing control strategies: Controller setup for shading, window opening, heating, cooling and ventilation for increased operation performance.

History

The history of BPS is approximately as long as that of computers. The very early developments in this direction started in the late 50's and early 60's in the United States and Sweden. During this period, several methods had been introduced for analyzing single system components (e.g. gas boiler) using steady state calculations.The very first reported simulation tool for buildings was BRIS, introduced in 1963 by the Royal Institute of Technology in Stockholm.[7] Until the late 60's, several models with hourly resolution had been developed focusing on energy assessments and heating/cooling load calculations. This effort resulted in more powerful simulation engines released in the early 70's, among those were BLAST, DOE-2, ESP-r, HVACSIM+ and TRNSYS.[8] In the United States, the 1970's energy crisis intensified these efforts, as reducing the energy consumption of buildings became an urgent domestic policy interest. The energy crisis also initiated development of U.S. building energy standards, beginning with ASHRAE 90-75.[9]

The development of building simulation represents a combined effort between academia, governmental institutions, industry, and professional organizations. Over the past decades the building simulation discipline has matured into a field that offers unique expertise, methods and tools for building performance evaluation. Several review papers and state of the art analysis were carried out during that time giving an overview about the development.[10][11][12]

In the 1980s, a discussion about future directions for BPS among a group of leading building simulation specialists started. There was a consensus that most of the tools, that had been developed until then, were too rigid in their structure to be able to accommodate the improvements and flexibility that would be called for in the future.[13] Around this time, the very first equation-based building simulation environment ENET[14] was developed, which provided the foundation of SPARK. In 1989, Sahlin and Sowell presented a Neutral Model Format (NMF) for building simulation models, which is used today in the commercial software IDA ICE.[15] Four years later, Klein introduced the Engineering Equation Solver (EES)[16] and in 1997, Mattsson and Elmqvist reported on an international effort to design Modelica.[17]

BPS still presents challenges relating to problem representation, support for performance appraisal, enabling operational application, and delivering user education, training, and accreditation. Clarke (2015) describes a future vision of BPS with the following, most important tasks which should be addressed by the global BPS community.[18]

  • Better concept promotion
  • Standardization of input data and accessibility of model libraries
  • Standard performance assessment procedures
  • Better embedding of BPS in practice
  • Operational support and fault diagnosis with BPS
  • Education, training, and user accreditation

Accuracy

In the context of building simulation models, error refers to the discrepancy between simulation results and the actual measured performance of the building. There are normally occurring uncertainties in building design and building assessment, which generally stem from approximations in model inputs, such as occupancy behavior. Calibration refers to the process of "tuning" or adjusting assumed simulation model inputs to match observed data from the utilities or Building Management System (BMS).[19][20][21]

The number of publications dealing with accuracy in building modeling and simulation increased significantly over the past decade. Many papers report large gaps between simulation results and measurements,[22][23][24][25] while other studies show that they can match very well.[26][27][28] The reliability of results from BPS depends on many different things, e.g. on the quality of input data,[29] the competence of the simulation engineers[30] and on the applied methods in the simulation engine.[31][32] An overview about possible causes for the widely discussed performance gap from design stage to operation is given by de Wilde (2014) and a progress report by the Zero Carbon Hub (2013). Both conclude the factors mentioned above as the main uncertainties in BPS.[33][34]

ASHRAE Standard 140-2017 "Standard Method of Test for the Evaluation of Building Energy Analysis Computer Programs (ANSI Approved)" provides a method to validate the technical capability and range of applicability of computer programs to calculate thermal performance.[35] ASHRAE Guideline 4-2014 provides performance indices criteria for model calibration.[36] The performance indices used are normalized mean bias error (NMBE), coefficient of variation (CV) of the root mean square error (RMSE), and R2 (coefficient of determination). ASHRAE recommends a R2 greater than 0.75 for calibrated models. The criteria for NMBE and CV RMSE depends on if measured data is available at a monthly or hourly timescale.

Technological aspects

Given the complexity of building energy and mass flows, it is generally not possible to find an analytical solution, so the simulation software employs other techniques, such as response function methods, or numerical methods in finite differences or finite volume, as an approximation.[2] Most of today's whole building simulation programs formulate models using imperative programming languages. These languages assign values to variables, declare the sequence of execution of these assignments and change the state of the program, as is done for example in C/C++, Fortran or MATLAB/Simulink. In such programs, model equations are tightly connected to the solution methods, often by making the solution procedure part of the actual model equations.[37] The use of imperative programming languages limits the applicability and extensibility of models. More flexibility offer simulation engines using symbolic Differential Algebraic Equations (DAEs) with general purpose solvers that increase model reuse, transparency and accuracy. Since some of these engines have been developed for more than 20 years (e.g. IDA ICE) and due to the key advantages of equation-based modeling, these simulation engines can be considered as state of the art technology.[38][39]

Applications

Building simulation models may be developed for both new or existing buildings. Major use categories of building performance simulation include:[3]

  • Architectural Design: quantitatively compare design or retrofit options in order to inform a more energy-efficient building design
  • HVAC Design: calculate thermal loads for sizing of mechanical equipment and help design and test system control strategies
  • Building Performance Rating: demonstrate performance-based compliance with energy codes, green certification, and financial incentives
  • Building Stock Analysis: support development of energy codes and standards and plan large scale energy efficiency programs
  • CFD in buildings: simulation of boundary conditions like surface heat fluxes and surface temperatures for a following CFD study of the situation[40]

Software tools

There are hundreds of software tools available for simulating the performance of buildings and building subsystems, which range in capability from whole-building simulations to model input calibration to building auditing. Among whole-building simulation software tools, it is important to draw a distinction between the simulation engine, which dynamically solves equations rooted in thermodynamics and building science, and the modeler application (interface).[6]

In general, BPS software can be classified into[41]

  • Applications with integrated simulation engine (e.g. EnergyPlus, ESP-r, IES-VE, IDA ICE)
  • Software that docks to a certain engine (e.g. Designbuilder, eQuest, RIUSKA, Sefaira)
  • Plugins for other software enabling certain performance analysis (e.g. DIVA for Rhino, Honeybee, Autodesk Green Building Studio)

Contrary to this presentation, there are some tools that in fact do not meet these sharp classification criteria, such as ESP-r which can also be used as a modeler application for EnergyPlus[42] and there are also other applications using the IDA simulation environment,[43] which makes "IDA" the engine and "ICE" the modeler. Most modeler applications support the user with a graphical user interface to make data input easier. The modeler creates an input file for the simulation engine to solve. The engine returns output data to the modeler application or another visualization tool which in turn presents the results to the user. For some software packages, the calculation engine and the interface may be the same product. The table below gives an overview about commonly used simulation engines and modeler applications for BPS.[41][44]

Simulation engineDeveloperfirst ReleaseTechnologyModeling LanguageLicenselatest VersionModeler applications and GUI
ApacheSim[45]Integrated Environmental Solutions Ltd., UKCommercial6.0VE 2018[46]
Carrier HAP[47]United Technologies, USCommercial5.11Carrier HAP
DOE-2[48]James J. Hirsch & Associates, US1978Freeware2.2eQuest,[49] RIUSKA,[50] EnergyPro,[51] GBS[52]
Energy+[53]Lawrence Berkeley National Laboratory, US2001Freeware8.9.0DesignBuilder,[54] OpenStudio,[55] Many other[56]
ESP-r[57]University of Strathclyde, UK1974Freeware11.11ESP-r
IDA[39]EQUA Simulation AB, SE1998DAENMF, ModelicaCommercial4.8ICE,[39] ESBO[58]
SPARK[59]Lawrence Berkeley National Laboratory, US1986DAEFreeware2.01VisualSPARK
TAS[60]Environmental Design Solutions Limited, UKCommercial9.4.3TAS 3D Modeler
TRNSYS[61]University of Wisconsin-Madison, US1975FORTRAN, C/C++Commercial18.0Simulation Studio,[62] TRNBuild

BPS in practice

Since the 90's, building performance simulation has undergone the transition from a method used mainly for research to a design tool for mainstream industrial projects. However, the utilization in different countries still varies greatly. Building certification programs like LEED (USA), BREEAM (UK) or DGNB (Germany) showed to be a good driving force for BPS to find broader application. Also, national building standards that allow BPS based analysis are of good help for an increasing industrial adoption, such as in the United States (ASHRAE 90.1),[71] Sweden (BBR),[63] Switzerland (SIA)[64] and the United Kingdom (NCM).[65]

The Swedish building regulations are unique in that computed energy use has to be verified by measurements within the first two years of building operation. Since the introduction in 2007, experience shows that highly detailed simulation models are preferred by modelers to reliably achieve the required level of accuracy. Furthermore, this has fostered a simulation culture where the design predictions are close to the actual performance. This in turn has led to offers of formal energy guarantees based on simulated predictions, highlighting the general business potential of BPS.[66]

Performance-based compliance

In a performance-based approach, compliance with building codes or standards is based on the predicted energy use from a building simulation, rather than a prescriptive approach, which requires adherence to stipulated technologies or design features. Performance-based compliance provides greater flexibility in the building design as it allows designers to miss some prescriptive requirements if the impact on building performance can be offset by exceeding other prescriptive requirements.[67] The certifying agency provides details on model inputs, software specifications, and performance requirements.

The following is a list of U.S. based energy codes and standards that reference building simulations to demonstrate compliance:

  • ASHRAE 90.1
  • International Energy Conservation Code (IECC)
  • Leadership in Energy and Environmental Design (LEED)
  • California Title 24
  • EnergyStar Multifamily High rise Program
  • Passive House Institute US (PHIUS)
  • Living Building Challenge

Professional associations and certifications

Professional associations
  • International Building Performance Simulation Association (IBPSA)[68]
  • American Society of Heating, Refrigerating, and Air-conditioning Engineers (ASHRAE)[69]
Certifications
  • BEMP - Building Energy Modeling Professional, administered by ASHRAE[70]
  • BESA - Certified Building Energy Simulation Analyst, administered by AEE[71]

See also

  • Energy modeling
  • Computer simulation

References

1. ^{{Cite book|title=Building Performance Analysis|last=de Wilde|first=Pieter|publisher=Wiley-Blackwell|year=2018|isbn=978-1-119-34192-5|location=Chichester|pages=325–422}}
2. ^1 2 {{Cite book|title=Energy simulation in building design|last=Clarke|first=J. A.|date=2001|publisher=Butterworth-Heinemann|isbn=978-0750650823|edition=2nd|location=Oxford|pages=|oclc=46693334}}
3. ^1 {{Cite book|title=Building performance simulation for design and operation|date=2011|publisher=Spon Press|others=Hensen, Jan., Lamberts, Roberto.|isbn=9780415474146|location=Abingdon, Oxon|oclc=244063540}}
4. ^1 {{Cite journal|last=Clarke|first=J. A.|last2=Hensen|first2=J. L. M.|date=2015-09-01|title=Integrated building performance simulation: Progress, prospects and requirements|journal=Building and Environment|series=Fifty Year Anniversary for Building and Environment|volume=91|pages=294–306|doi=10.1016/j.buildenv.2015.04.002}}
5. ^{{Cite web|url=http://www.buildingenergysoftwaretools.com/|title=Best Directory {{!}} Building Energy Software Tools|website=www.buildingenergysoftwaretools.com|language=en|access-date=2017-11-07}}
6. ^1 {{Cite journal|last=Crawley|first=Drury B.|last2=Hand|first2=Jon W.|last3=Kummert|first3=Michaël|last4=Griffith|first4=Brent T.|date=2008-04-01|title=Contrasting the capabilities of building energy performance simulation programs|journal=Building and Environment|series=Part Special: Building Performance Simulation|volume=43|issue=4|pages=661–673|doi=10.1016/j.buildenv.2006.10.027}}
7. ^{{cite journal|last1=Brown|first1=Gösta|title=The BRIS simulation program for thermal design of buildings and their services|journal=Energy and Buildings|date=January 1990|volume=14|issue=4|pages=385–400|doi=10.1016/0378-7788(90)90100-W}}
8. ^{{Cite web|url=http://www.ibpsa.org/%5Cproceedings%5CBS1999%5CBS99_P-01.pdf|title=Early history and future prospects of building system simulation|last=Kusuda|first=T.|date=1999|website=IBPSA Proceedings|archive-url=|archive-date=|dead-url=|access-date=2017-07-07}}
9. ^{{Cite journal|last=Sukjoon|first=Oh|date=2013-08-19|title=Origins of Analysis Methods in Energy Simulation Programs Used for High Performance Commercial Buildings|url=http://oaktrust.library.tamu.edu/handle/1969.1/151151|language=en}}
10. ^{{Cite journal|last=Augenbroe|first=Godfried|last2=Hensen|first2=Jan|date=2004-08-01|title=Simulation for better building design|journal=Building and Environment|series=Building Simulation for Better Building Design|volume=39|issue=8|pages=875–877|doi=10.1016/j.buildenv.2004.04.001}}
11. ^Hensen, J. (2006). About the current state of building performance simulation and ibpsa. In 4th national IBPS-CZ conference (p. 2).
12. ^{{Cite journal|last=Wang|first=Haidong|last2=Zhai|first2=Zhiqiang (John)|date=2016-09-15|title=Advances in building simulation and computational techniques: A review between 1987 and 2014|journal=Energy and Buildings|volume=128|pages=319–335|doi=10.1016/j.enbuild.2016.06.080}}
13. ^Clarke, J.A.; Sowell, E.F.; the Simulation Research Group (1985): A Proposal to Develop a Kernel System for the Next Generation of Building Energy Simulation Software, Lawrence Berkeley Laboratory, Berkeley, CA, Nov. 4, 1985
14. ^Low, D. and Sowell, E.F. (1982): ENET, a PC-based building energy simulation system, Energy Programs Conference, IBM Real Estate and Construction Division, Austin, Texas (1982), pp. 2-7
15. ^Sahlin, P. and Sowell, E.F. (1989). A neutral format for building simulation models, Proceedings of the Second International IBPSA Conference, Vancouver, BC, Canada, pp. 147-154, http://www.ibpsa.org/proceedings/BS1989/BS89_147_154.pdf
16. ^{{Cite journal|last=Klein|first=S. A.|date=1993-01-01|title=Development and integration of an equation-solving program for engineering thermodynamics courses|journal=Computer Applications in Engineering Education|language=en|volume=1|issue=3|pages=265–275|doi=10.1002/cae.6180010310|issn=1099-0542}}
17. ^{{Cite journal|last=Mattsson|first=Sven Erik|last2=Elmqvist|first2=Hilding|date=April 1997|title=Modelica - An International Effort to Design the Next Generation Modeling Language|journal=IFAC Proceedings Volumes|series=7th IFAC Symposium on Computer Aided Control Systems Design (CACSD '97), Gent, Belgium, 28–30 April|volume=30|issue=4|pages=151–155|doi=10.1016/S1474-6670(17)43628-7|citeseerx=10.1.1.16.5750}}
18. ^{{Cite journal|last=Clarke|first=Joe|date=2015-03-04|title=A vision for building performance simulation: a position paper prepared on behalf of the IBPSA Board|journal=Journal of Building Performance Simulation|volume=8|issue=2|pages=39–43|doi=10.1080/19401493.2015.1007699|issn=1940-1493}}
19. ^{{Cite journal|last=Raftery|first=Paul|last2=Keane|first2=Marcus|last3=Costa|first3=Andrea|date=2011-12-01|title=Calibrating whole building energy models: Detailed case study using hourly measured data|journal=Energy and Buildings|volume=43|issue=12|pages=3666–3679|doi=10.1016/j.enbuild.2011.09.039}}
20. ^{{Cite journal|last=Reddy|first=T. Agami|date=2006|title=Literature Review on Calibration of Building Energy Simulation Programs: Uses, Problems, Procedures, Uncertainty, and Tools.|url=http://web.a.ebscohost.com/abstract?direct=true&profile=ehost&scope=site&authtype=crawler&jrnl=00012505&AN=21489891&h=p8ojDgTz25mLEtPl4J%2f86zfAUGKoYzTVsDcvoE2LFrNnW0vox%2bp0QW8edSwoCq%2bDwUzsmlj6wPJVrbTSmFK79g%3d%3d&crl=c&resultNs=AdminWebAuth&resultLocal=ErrCrlNotAuth&crlhashurl=login.aspx%3fdirect%3dtrue%26profile%3dehost%26scope%3dsite%26authtype%3dcrawler%26jrnl%3d00012505%26AN%3d21489891|journal=ASHRAE Transactions|volume=112 |issue=1|pages=226–240|via=}}
21. ^{{Cite journal|last=Heo|first=Y.|last2=Choudhary|first2=R.|last3=Augenbroe|first3=G.A.|title=Calibration of building energy models for retrofit analysis under uncertainty|journal=Energy and Buildings|language=en|volume=47|pages=550–560|doi=10.1016/j.enbuild.2011.12.029|year=2012}}
22. ^{{Cite journal|last=Coakley|first=Daniel|last2=Raftery|first2=Paul|last3=Keane|first3=Marcus|date=2014-09-01|title=A review of methods to match building energy simulation models to measured data|journal=Renewable and Sustainable Energy Reviews|volume=37|pages=123–141|doi=10.1016/j.rser.2014.05.007}}
23. ^{{Cite journal|last=Li|first=Nan|last2=Yang|first2=Zheng|last3=Becerik-Gerber|first3=Burcin|last4=Tang|first4=Chao|last5=Chen|first5=Nanlin|title=Why is the reliability of building simulation limited as a tool for evaluating energy conservation measures?|journal=Applied Energy|volume=159|pages=196–205|doi=10.1016/j.apenergy.2015.09.001|year=2015}}
24. ^{{Cite journal|last=Hong|first=Taehoon|last2=Kim|first2=Jimin|last3=Jeong|first3=Jaemin|last4=Lee|first4=Myeonghwi|last5=Ji|first5=Changyoon|title=Automatic calibration model of a building energy simulation using optimization algorithm|journal=Energy Procedia|volume=105|pages=3698–3704|doi=10.1016/j.egypro.2017.03.855|year=2017}}
25. ^{{Cite journal|last=Mustafaraj|first=Giorgio|last2=Marini|first2=Dashamir|last3=Costa|first3=Andrea|last4=Keane|first4=Marcus|title=Model calibration for building energy efficiency simulation|journal=Applied Energy|language=en|volume=130|pages=72–85|doi=10.1016/j.apenergy.2014.05.019|year=2014}}
26. ^{{Cite journal|last=Christensen|first=Jørgen Erik|last2=Chasapis|first2=Kleanthis|last3=Gazovic|first3=Libor|last4=Kolarik|first4=Jakub|date=2015-11-01|title=Indoor Environment and Energy Consumption Optimization Using Field Measurements and Building Energy Simulation|journal=Energy Procedia|series=6th International Building Physics Conference, IBPC 2015|volume=78|pages=2118–2123|doi=10.1016/j.egypro.2015.11.281}}
27. ^{{Cite journal|last=Cornaro|first=Cristina|last2=Puggioni|first2=Valerio Adoo|last3=Strollo|first3=Rodolfo Maria|date=2016-06-01|title=Dynamic simulation and on-site measurements for energy retrofit of complex historic buildings: Villa Mondragone case study|journal=Journal of Building Engineering|volume=6|pages=17–28|doi=10.1016/j.jobe.2016.02.001}}
28. ^{{Cite journal|last=Cornaro|first=Cristina|last2=Rossi|first2=Stefania|last3=Cordiner|first3=Stefano|last4=Mulone|first4=Vincenzo|last5=Ramazzotti|first5=Luigi|last6=Rinaldi|first6=Zila|title=Energy performance analysis of STILE house at the Solar Decathlon 2015: lessons learned|journal=Journal of Building Engineering|volume=13|pages=11–27|doi=10.1016/j.jobe.2017.06.015|year=2017}}
29. ^{{Cite journal|last=Dodoo|first=Ambrose|last2=Tettey|first2=Uniben Yao Ayikoe|last3=Gustavsson|first3=Leif|title=Influence of simulation assumptions and input parameters on energy balance calculations of residential buildings|journal=Energy|volume=120|pages=718–730|doi=10.1016/j.energy.2016.11.124|year=2017}}
30. ^{{Cite journal|last=Imam|first=Salah|last2=Coley|first2=David A|last3=Walker|first3=Ian|date=2017-01-18|title=The building performance gap: Are modellers literate?|journal=Building Services Engineering Research and Technology|language=en|volume=38|issue=3|pages=351–375|doi=10.1177/0143624416684641|url=http://opus.bath.ac.uk/53934/1/ImamColeyWalker2017.pdf}}
31. ^{{Cite journal|last=Nageler|first=P.|last2=Schweiger|first2=G.|last3=Pichler|first3=M.|last4=Brandl|first4=D.|last5=Mach|first5=T.|last6=Heimrath|first6=R.|last7=Schranzhofer|first7=H.|last8=Hochenauer|first8=C.|title=Validation of dynamic building energy simulation tools based on a real test-box with thermally activated building systems (TABS)|journal=Energy and Buildings|volume=168|pages=42–55|doi=10.1016/j.enbuild.2018.03.025|year=2018}}
32. ^{{Cite journal|last=Choi|first=Joon-Ho|title=Investigation of the correlation of building energy use intensity estimated by six building performance simulation tools|journal=Energy and Buildings|volume=147|pages=14–26|doi=10.1016/j.enbuild.2017.04.078|year=2017}}
33. ^{{Cite journal|last=de Wilde|first=Pieter|date=2014-05-01|title=The gap between predicted and measured energy performance of buildings: A framework for investigation|journal=Automation in Construction|volume=41|pages=40–49|doi=10.1016/j.autcon.2014.02.009}}
34. ^{{Cite web|url=http://www.zerocarbonhub.org/sites/default/files/resources/reports/Closing_the_Gap_Bewteen_Design_and_As-Built_Performance_Interim_Report.pdf|title=Closing the Gap Bewteen Design and As-Built Performance|last=|first=|date=July 2013|website=www.zerocarbonhub.org|publisher=Zero Carbon Hub|archive-url=|archive-date=|dead-url=|access-date=2017-06-30}}
35. ^{{Cite book|title=ASHRAE/ANSI Standard 140-2017--Standard Method of Test for the Evaluation of Building Energy Analysis Computer Programs|last=ASHRAE|publisher=American Society of Heating, Refrigerating, and Air-Conditioning Engineers, Inc.|year=2017|isbn=|location=Atlanta, GA|pages=}}
36. ^{{Cite book|title=Guideline 14-2014 Measurement of Energy Demand Savings; Technical Report|last=ASHRAE|publisher=American Society of Heating, Refrigerating and Air-Conditioning Engineers.|year=2014|isbn=|location=Atlanta, GA|pages=}}
37. ^{{Cite journal|last=Wetter|first=Michael|last2=Bonvini|first2=Marco|last3=Nouidui|first3=Thierry S.|date=2016-04-01|title=Equation-based languages – A new paradigm for building energy modeling, simulation and optimization|journal=Energy and Buildings|volume=117|pages=290–300|doi=10.1016/j.enbuild.2015.10.017}}
38. ^{{Cite journal|last=Sahlin|first=Per|last2=Eriksson|first2=Lars|last3=Grozman|first3=Pavel|last4=Johnsson|first4=Hans|last5=Shapovalov|first5=Alexander|last6=Vuolle|first6=Mika|date=2004-08-01|title=Whole-building simulation with symbolic DAE equations and general purpose solvers|journal=Building and Environment|series=Building Simulation for Better Building Design|volume=39|issue=8|pages=949–958|doi=10.1016/j.buildenv.2004.01.019}}
39. ^1 2 {{Cite journal|last=Sahlin|first=Per|last2=Eriksson|first2=Lars|last3=Grozman|first3=Pavel|last4=Johnsson|first4=Hans|last5=Shapovalov|first5=Alexander|last6=Vuolle|first6=Mika|date=August 2003|title=Will equation-based building simulation make it?-experiences from the introduction of IDA Indoor Climate And Energy|url=https://www.academia.edu/16918862|journal=Proceedings of Building …|language=en|volume=|pages=|via=}}
40. ^{{Cite journal|last=Tian|first=Wei|last2=Han|first2=Xu|last3=Zuo|first3=Wangda|last4=Sohn|first4=Michael D.|title=Building energy simulation coupled with CFD for indoor environment: A critical review and recent applications|journal=Energy and Buildings|volume=165|pages=184–199|doi=10.1016/j.enbuild.2018.01.046|year=2018}}
41. ^1 {{Cite journal|last=Østergård|first=Torben|last2=Jensen|first2=Rasmus L.|last3=Maagaard|first3=Steffen E.|date=2016-08-01|title=Building simulations supporting decision making in early design – A review|journal=Renewable and Sustainable Energy Reviews|volume=61|pages=187–201|doi=10.1016/j.rser.2016.03.045}}
42. ^{{Cite web|url=http://lists.strath.ac.uk/archives/esp-r/2015/003176.html|title=Exporting ESP-r models to E+ .idf files|last=|first=|date=|website=Answered question in the ESP-r support forum|archive-url=|archive-date=|dead-url=|access-date=2017-07-04}}
43. ^{{Cite web|url=http://www.equa.se/de/tunnel|title=IDA Tunnel|last=|first=|date=|website=Software "Tunnel" uses IDA simulation environment|archive-url=|archive-date=|dead-url=|access-date=2017-07-04}}
44. ^{{Cite book|title=Annex 43/Task 34 Final Task Management Report - Testing and Validation of Building Energy Simulation Tools|last=Judkoff|first=Ron|publisher=International Energy Agency (IEA)|year=2008|isbn=|location=|pages=}}
45. ^{{Cite web|url=http://www.iesve.com/software/ve-for-engineers/module/ApacheSim/482|title=APACHESIM|last=Integrated Environmental Solutions, Ltd|date=2017|website=|archive-url=|archive-date=|dead-url=|access-date=2017-11-07}}
46. ^{{Cite web|url=https://www.iesve.com/VE2018|title=VE2018 Website|last=|first=|date=|website=|archive-url=|archive-date=|dead-url=|access-date=2018-09-26}}
47. ^{{Cite web|url=https://www.carrier.com/commercial/en/us/software/hvac-system-design/hourly-analysis-program/|title=Hourly Analysis Program HVAC System Design Software {{!}} Carrier Building Solutions|website=Building Solutions|language=en-US|access-date=2017-11-07}}
48. ^{{Cite journal|last=Lokmanhekim|first=M.|display-authors=et al|date=1979|title=DOE-2: a new state-of-the-art computer program for the energy utilization analysis of buildings.|url=|journal=Lawrence Berkeley Lab|volume=Report CBC-8977|pages=|via=}}
49. ^{{Cite web|url=http://doe2.com/equest/index.html|title=eQUEST|last=Hirsch|first=Jeff|website=doe2.com|access-date=2017-11-07}}
50. ^{{Cite web|url=http://www.granlund.fi/en/software/riuska/|title=RIUSKA Website|last=Granlund Consulting Oy|date=|website=|archive-url=|archive-date=|dead-url=|access-date=2018-04-03}}
51. ^{{Cite web|url=http://www.energysoft.com/|title=EnergySoft – World Class Building Energy Analysis Software|website=www.energysoft.com|language=en-US|access-date=2017-11-07}}
52. ^{{Cite web|url=https://gbs.autodesk.com/GBS/|title=Green Building Studio|website=gbs.autodesk.com|access-date=2017-11-07}}
53. ^{{Cite web|url=https://energyplus.net/|title=Energy+ Homepage|last=US Departement of Energy's|first=Building Technology office|date=|website=|archive-url=|archive-date=|dead-url=|access-date=2018-04-03}}
54. ^{{Cite journal|last=Tindale|first=A|date=2005|title=Designbuilder Software|url=|journal=Design-Builder Software Ltd|volume=|pages=|via=}}
55. ^{{Cite journal|last=Guglielmetti|first=Rob|display-authors=et al|date=2011|title=OpenStudio: An Open Source Integrated Analysis Platform|url=http://www.ibpsa.org/proceedings/BS2011/P_1245.pdf|journal=Proceedings of Building Simulation 2011: 12th Conference of International Building Performance Simulation Association|volume=|pages=442–449|via=}}
56. ^{{Cite web|url=https://www.buildingenergysoftwaretools.com/?capabilities=Whole-building+Energy+Simulation&keywords=EnergyPlus|title=List of graphical user interfaces for Energy+|last=BEST directory|date=|website=|archive-url=|archive-date=|dead-url=|access-date=2018-04-03}}
57. ^{{Cite web|url=https://www.strath.ac.uk/research/energysystemsresearchunit/applications/esp-r/|title=ESP-r {{!}} University of Strathclyde|website=www.strath.ac.uk|language=en|access-date=2017-11-08}}
58. ^{{Cite web|url=https://www.equa.se/en/esbo|title=IDA ESBO Homepage|last=EQUA Simulation AB|date=|website=|archive-url=|archive-date=|dead-url=|access-date=2018-04-03}}
59. ^{{Cite web|url=https://simulationresearch.lbl.gov/projects/spark|title=Project SPARK|last=LBNL|first=US Departement of Energy|date=|website=|archive-url=|archive-date=|dead-url=|access-date=2018-04-03}}
60. ^{{Cite web|url=http://www.edsl.net/#|title=EDSL TAS website|last=|first=|date=|website=|archive-url=|archive-date=|dead-url=|access-date=2018-04-03}}
61. ^{{Cite journal|last=Beckman|first=William A.|last2=Broman|first2=Lars|last3=Fiksel|first3=Alex|last4=Klein|first4=Sanford A.|last5=Lindberg|first5=Eva|last6=Schuler|first6=Mattias|last7=Thornton|first7=Jeff|title=TRNSYS The most complete solar energy system modeling and simulation software|journal=Renewable Energy|language=en|volume=5|issue=1–4|pages=486–488|doi=10.1016/0960-1481(94)90420-0|year=1994}}
62. ^{{Cite web|url=http://web.mit.edu/parmstr/Public/Documentation/02-SimulationStudio.pdf|title=Manual for Simulation Studio|last=|first=|date=|website=|archive-url=|archive-date=|dead-url=|access-date=2018-03-29}}
63. ^{{Cite web|url=https://www.boverket.se/en/start-in-english/|title=BBR - Swedish building regulation|last=|first=|date=|website=|archive-url=|archive-date=|dead-url=|access-date=2018-03-29}}
64. ^{{Cite web|url=http://www.sia.ch/en/the-sia/|title=Swiss society of architects and engineers (SIA)|last=|first=|date=|website=|archive-url=|archive-date=|dead-url=|access-date=2018-03-29}}
65. ^{{Cite web|url=https://www.uk-ncm.org.uk/|title=UKs National Calculation Method|last=|first=|date=|website=|archive-url=|archive-date=|dead-url=|access-date=2018-03-29}}
66. ^{{Cite web|url=http://www.gbpn.org/databases-tools/bc-detail-pages/sweden#Summary|title=Swedish code summarized in global performance network|last=|first=|date=|website=|archive-url=|archive-date=|dead-url=|access-date=2018-03-29}}
67. ^{{Cite web|url=http://cbei.psu.edu/eeb-codes-performance-based-codes/|title=A new paradigm for building codes|last=Senick|first=Jennifer|date=|website=cbei.psu.edu|language=en-US|archive-url=|archive-date=|dead-url=|access-date=2017-11-07}}
68. ^{{cite web| title = IBPSA-USA| url = http://www.ibpsa.us/| publisher = IBPSA-USA| accessdate = 13 June 2014}}
69. ^1 {{Cite web|url=https://www.ashrae.org/|title=Home {{!}} ashrae.org|website=www.ashrae.org|access-date=2017-11-08}}
70. ^{{cite web|url=https://www.ashrae.org/professional-development/ashrae-certification/certification-types/bemp-building-energy-modeling-professional-certification|title=Building Energy Modeling Professional Certification|last=|first=|date=|website=ashrae.org|publisher=ASHRAE|archive-url=|archive-date=|dead-url=|accessdate=2018-04-03}}
71. ^{{cite web|url=https://www.aeecenter.org/certifications/certifications/certified-building-energy-simulation-analyst|title=Certified Building Energy Simulation Analyst|last=|first=|date=2016-08-04|website=aeecenter.org|publisher=Association of Energy Engineers|archive-url=|archive-date=|dead-url=|accessdate=2018-04-03}}

External links

  • Bldg-sim mailing list for building simulation professionals: http://lists.onebuilding.org/listinfo.cgi/bldg-sim-onebuilding.org
  • Simulation modeling instruction and discussion: http://energy-models.com/forum

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