Simulating the human-building interaction: Development and validation of an agent-based model of office occupant behaviors

Building and Environment

Volumn 88, Issue , 2015, Pages 27-45

  Langevin, Jared ^a   Wen, Jin ^a   Gurian, Patrick L ^a  

^a Drexel University   (United States)

Author keywords

Agent based modeling; Human building interaction; Occupant behavior; Thermal acceptability; Thermal comfort

Indexed keywords

AIR CONDITIONING; OFFICE BUILDINGS; SENSORY PERCEPTION; THERMAL COMFORT;

AGENT-BASED MODEL; AIR-CONDITIONED OFFICES; HUMAN-BUILDING INTERACTION; OCCUPANT BEHAVIOR; PERSONAL CHARACTERISTICS; PREDICTIVE PERFORMANCE; REGRESSION RELATIONSHIP; THERMAL ACCEPTABILITIES;

COMPUTATIONAL METHODS;

EID: 84939944927     PISSN: 03601323     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.buildenv.2014.11.037     Document Type: Article

References (40)

1. Humphreys M.A. An adaptive approach to thermal comfort. Naturally ventilated buildings: buildings for the senses, economy and society 1997, E & FN Spon, London, UK. D. Clements-Croome (Ed.).
2. Steemers K., Yun G. Household energy consumption: a study of the role of the occupants. Build Res Inf 2009, 37(5-6):625-637.
3. Hong T., Lin H.W. Occupant behavior: impact on energy use of private offices 2013, Lawrence Berkeley National Laboratory, Berkeley.
4. Nicol J.F. Characterizing occupant behavior in buildings: towards a stochastic model of occupant use of windows, lights, blinds, heaters, and fans. Seventh International IBPSA Conference 2001 Aug 13-15, 1073-1078. International Building Performance Simulation Association, Rio de Janerio, BRA.
5. Rijal H.B., Tuohy P., Humphreys M.A., Nicol J.F., Samuel A., Clarke J. Using results from field surveys to predict the effect of open windows on thermal comfort and energy use in buildings. Energy Build 2007, 39:823-836.
6. Yun G.Y., Steemers K. Time-dependent occupant behaviour models of window control in summer. Energy Build 2008, 43:1471-1482.
7. Haldi F., Robinson D. Interactions with window openings by office occupants. Build Environ 2009, 44(12):2378-2395.
8. Haldi F., Robinson D. On the behaviour and adaptation of office occupants. Build Environ 2008, 43(12):2163-2177.
9. International Facilities Management Association Temperature wars: savings vs. comfort 2009, International Facilities Management Association, Houston.
10. Robinson D., Wilke U., Haldi F. Multi agent simulation of occupant's presence and behaviour. 12th Conference of International Building Performance Association 2011 Nov 14-16, International Building Performance Association, Sydney, AU.
11. Macal C.M., North M.J. Tutorial on agent-based modelling and simulation. JSimul 2010, 4:151-162.
12. Andrews C.J., Yi D., Krogmann U., Senick J.A., Wener R.E. Designing buildings for real occupants: an agent-based approach. IEEE Trans Syst Man Cybern Part A - Syst Humans 2011, 41(6):1077-1091.
13. Azar E., Menassa C. Agent-based modeling of occupants and their impact on energy use in commercial buildings. JComput Civ Eng 2012, 26(4):506-518.
14. Lee Y.S., Malkawi A.M. Simulating multiple occupant behaviors in buildings: an agent-based modeling approach. Energy Build 2014, 69:407-416.
15. Chen J., Taylor J.E., Wei H.H. Modeling building occupant network energy consumption decision-making: the interplay between network structure and conservation. Energy Build 2012, 47:515-524.
16. Kashif A., Binh Le X., Dugdale J., Ploix S. Agent based framework to simulate inhabitants' behaviour in domestic settings for energy management. 3rd International Conference on Agents and Artificial Intelligence 2011 Jan 28-30, INSTICC, Rome, ITA.
17. Linkola L., Andrews C.J., Schuetze T. An agent-based model of household water use. Water 2013, 5(3):1082-1100.
18. Chu J., Wang C., Chen J., Wang H. Agent-based residential water use behavior simulation and policy implications: a case study in Beijing city. Water Resour Manag 2009, 23(15):3267-3295.
19. Langevin J., Wen J., Gurian P.L. Tracking long-term occupant IEQ outcomes: a longitudinal survey tool. IAQ 2013 2013 Oct 15-18, ASHRAE, Vancouver, CAN.
20. Powers W.T. Behavior: the control of perception 1973, Benchmark, New Canaan, CT.
21. Grimm V., et al. Astandard protocol for describing individual-based and agent-based models. Ecol Model 2006, 198:115-126.
22. Grimm V., Berger U., DeAngelis D., Polhill G., Giske J., Railsback S. The ODD protocol: a review and first update. Ecol Model 2010, 221(23):2760-2768.
23. Schweiker M., Shukuya M. Comparison of theoretical and statistical models of air-conditioning-unit usage behaviour in a residential setting under Japanese climatic conditions. Build Environ 2009, 44(10):2137-2149.
24. Rijal H.B., Tuohy P.G., Humphreys M.A., Nicol F., Samuel A.A. An algorithm to represent occupant use of windows and fans including situation-specific motivations and constraints. Build Simul 2011, 4(2):117-134.
25. American Society of Heating, Refrigeration, and Air-Conditioning Engineers Standard 55-2010: thermal environmental conditions for human occupancy 2010, American Society of Heating, Refrigeration, and Air-Conditioning Engineers, Atlanta, GA.
26. Langevin J., Wen J., Gurian P.L. Modeling thermal comfort holistically: Bayesian estimation of thermal sensation, acceptability, and preference distributions for office building occupants. Build Environ 2013, 69:206-226.
27. Fanger P.O. Thermal comfort: analysis and applications in environmental engineering 1970, Danish Technical Press, Copenhagen.
28. Metz C.E. Basic principles of ROC analysis. Seminars Nucl Med 1978, 8(4):283-298.
29. Fawcett T. Introduction to ROC analysis. Pattern Recognit Lett 2006, 27:861-874.
30. Montomery D.C., Jennings C.L., Kulahci M. Introduction to time series analysis 2008, Wiley, Hoboken, NJ.
31. Rand W.M., Rust R.T. Agent-based modeling in marketing: guidelines for rigor. Int J Res Mark 2011, 181-193.
32. European Committee for Standardization Indoor environmental input parameters for design and assessment of energy performance in buildings: addressing indoor air quality, thermal environment, lighting and acoustics 2007, European Committee for Standardization, Brussels.
33. Humphreys M.A., Hancock M. Do people like to feel 'neutral'?: exploring the variation of the desired thermal sensation on the ASHRAE scale. Energy Build 2007, 39(7):867-874.
34. Rijal H.B., Tuohy P., Humphreys M.A., Nicol J.F., Samuel A., Raja I.A., et al. Development of adaptive algorithms for the operation of windows, fans and doors to predict thermal comfort and energy use in Pakistani buildings. ASHRAE Trans 2008, 114(2):555-573.
35. Chartered Institution of Building Services Engineers Guide A: environmental design 2006, Chartered Institution of Building Services Engineers, London.
36. Langevin J., Gurian P.L., Wen J. Including occupants in building performance simulation: integration of an agent-based occupant behavior algorithm with EnergyPlus. ASHRAE/IBPSA-USA 2014 Simulation Conference 2014 Sep 10-12, ASHRAE/IBPSA, Atlanta, GA.
37. Haldi F., Robinson D. Adaptive actions on shading devices in response to local visual stimuli. JBuild Perform Simul 2010, 3(2):135-153.
38. Hunt D.R.G. Predicting artificial lighting use - a method based upon observed patterns of behavior. Light Res Technol 1980, 12(1):7-14.
39. Reinhart C.F. Lightswitch 2002: a model for manual control of electric lighting and blinds. Sol Energy 2004, 77(1):15-28.
40. Goto T., Toftum J., de Dear R., Fanger P.O. Thermal sensation and thermophysiological responses to metabolic step-changes. Int J Biometeorology 2006, 50(5):323-332.