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{{Short description|Replication of aspects of building performance}}
{{about|performance simulation in buildings|computer simulation in general|Computer simulation|the modeling of energy systems more generally|Energy modeling}}
[[File:Building performance simulation.png|thumb|Building performance simulation model with input and some resulting output|348x348px]]
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From a physical point of view, a building is a very complex system, influenced by a wide range of parameters. A [[Simulation modeling|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 comfort|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.<ref name=":0">{{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|oclc=46693334}}</ref><ref name=":6">{{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}}</ref><ref name=":32">{{Cite journal|last1=Clarke|first1=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|url=https://strathprints.strath.ac.uk/52580/1/Clarke_Hensen_BuildEnv_2015_Integrated_building_performance_simulation_progress_prospects_and_requirements.pdf}}</ref>
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.<ref>{{
A typical building simulation model has inputs for local weather such as [[Typical Meteorological Year|Typical Meteorological Year (TMY)]] file; building geometry; [[building envelope]] characteristics; internal heat gains from [[lighting]], occupants and [[Plug load|equipment loads]]; heating, ventilation, and cooling (HVAC) system specifications; operation schedules and control strategies.<ref name=":0" /> 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.
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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 energy assessment|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 automation|Building Management System]] (BMS).<ref>{{Cite journal|last1=Raftery|first1=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}}</ref><ref>{{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}}</ref><ref>{{Cite journal|last1=Heo|first1=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}}</ref>
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,<ref>{{Cite journal|last1=Coakley|first1=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|s2cid=56419662 |url=https://escholarship.org/uc/item/88z3g017}}</ref><ref>{{Cite journal|last1=Li|first1=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|doi-access=free}}</ref><ref>{{Cite journal|last1=Hong|first1=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|doi-access=free}}</ref><ref>{{Cite journal|last1=Mustafaraj|first1=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}}</ref> while other studies show that they can match very well.<ref>{{Cite journal|last1=Christensen|first1=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|doi-access=free}}</ref><ref>{{Cite journal|last1=Cornaro|first1=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}}</ref><ref>{{Cite journal|last1=Cornaro|first1=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}}</ref> The reliability of results from BPS depends on many different things, e.g. on the quality of input data,<ref>{{Cite journal|last1=Dodoo|first1=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}}</ref> the competence of the simulation engineers<ref>{{Cite journal|last1=Imam|first1=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|s2cid=55153560|url=http://opus.bath.ac.uk/53934/1/ImamColeyWalker2017.pdf}}</ref> and on the applied methods in the simulation engine.<ref>{{Cite journal|last1=Nageler|first1=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|s2cid=117446952 }}</ref><ref name=":02">{{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}}</ref> 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.<ref>{{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}}</ref><ref>{{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 Between Design and As-Built Performance|date=July 2013|website=www.zerocarbonhub.org|publisher=Zero Carbon Hub|access-date=2017-06-30|archive-date=2021-12-02|archive-url=https://web.archive.org/web/20211202151136/https://www.zerocarbonhub.org/sites/default/files/resources/reports/Closing_the_Gap_Bewteen_Design_and_As-Built_Performance_Interim_Report.pdf|url-status=dead}}</ref>
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.<ref>{{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|___location=Atlanta, GA}}</ref> ASHRAE Guideline 4-2014 provides performance indices criteria for model calibration.<ref>{{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|___location=Atlanta, GA}}</ref> The performance indices used are normalized mean bias error (NMBE), [[coefficient of variation]] (CV) of the [[Root-mean-square deviation|root mean square error]] (RMSE), and R<sup>2</sup> ([[coefficient of determination]]). ASHRAE recommends a R<sup>2</sup> 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.
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* '''Building Performance Rating:''' demonstrate [[#Performance-Based Compliance|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 in buildings|CFD]] study of the situation<ref>{{Cite journal|last1=Tian|first1=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|osti=1432688|url=https://scholar.colorado.edu/concern/articles/q811kk637 |doi-access=free}}</ref>
== Software tools ==
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|Carrier HAP
|-
|COMFIE<ref>{{Cite journal|last1=Peuportier|first1=Bruno|last2=Blanc-Sommereux|first2=Isabelle|date=1990|title=Simulation Tool with Its Expert Interface for the Thermal Design of Multizone Buildings|journal=International Journal of Solar Energy|volume=8|issue=2|pages=109–120|doi=10.1080/01425919008909714|bibcode=1990IJSE....8..109P }}</ref>
|[[Mines ParisTech]], then IZUBA énergies, FR
|1994
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|Pleiades
|-
|DOE-2<ref>{{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
|James J. Hirsch & Associates, US
|1978
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|Freeware
|9.4.0
|DesignBuilder,<ref>{{Cite journal|last=Tindale|first=A|date=2005|title=Designbuilder Software|journal=Design-Builder Software Ltd}}</ref> [[OpenStudio]],<ref>{{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|pages=442–449|access-date=2017-12-08|archive-url=https://web.archive.org/web/20170809022750/http://www.ibpsa.org/proceedings/BS2011/P_1245.pdf|archive-date=2017-08-09|url-status=dead}}</ref> cove.tool,<ref>{{Cite web |title=cove
|-
|ESP-r<ref name=":5">{{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|archive-url=https://web.archive.org/web/20171108100137/https://www.strath.ac.uk/research/energysystemsresearchunit/applications/esp-r/|archive-date=2017-11-08|url-status=dead}}</ref>
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== BPS in practice ==
Since the 1990s, building performance simulation has undergone the transition from a method used mainly for research to a design tool for mainstream industrial projects. However, the
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.<ref>{{Cite web|url=http://www.gbpn.org/databases-tools/bc-detail-pages/sweden#Summary|title=Swedish code summarized in global performance network|access-date=2018-03-29|archive-date=2021-01-17|archive-url=https://web.archive.org/web/20210117160506/https://www.gbpn.org/databases-tools/bc-detail-pages/sweden#Summary|url-status=dead}}</ref>
== Performance-based compliance ==
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* [[Energy modeling]]
* [[Computer simulation]]
* [[Energy signature]]
== References ==
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* Simulation modeling instruction and discussion: http://energy-models.com/forum
{{Computer simulation}}
[[Category:Architecture]]
[[Category:Building engineering]]
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