Quantitative description and simulation of human behavior in residential buildings
Purchase on Springer.com
$39.95 / €34.95 / £29.95*
Rent the article at a discountRent now
* Final gross prices may vary according to local VAT.
An in-depth understanding of building energy use requires a thorough understanding of human behavior. This research gives a quantitative description of human behavior in residential buildings. This quantitative description method can be used to forecast the impact of the human behavior on the indoor building environment and energy use. Human behavior influences the energy use directly and indirectly by changing window openings, air-conditioner usage, lighting, etc. This quantitative description method describes these behavioral effects. Behavior can be divided into several types according to the usage with time related, environmentally related and random modes used to quantitatively describe the behavior. The method is then applied to describe a Beijing household with comparison to on-site observations of the resident’s behavior and measurements of energy use to validate the method. The results show that the human behavior in the real world can be quantified by the quantitative description method. These simulation tools can greatly facilitate building energy conservation by describing the influence of human behavior on building performance and energy use.
- Annex 53 (2010). Total energy use in building—Analysis and evaluation methods. IEA Energy Conservation in Building and Community Systems Programme, www.ecbcsa53.org.
- Bourgeois DJ (2005). Detailed occupancy prediction, occupancy-sensing control and advanced behavioral modelling within whole-building energy simulation. Ph D Thesis, l’Université Laval, Québec.
- Crawley DB, Lawrie LK, Winkelmann FC, Buhl WF, Huang YJ, Pedersen CO, Strand RK, Liesen RJ, Fisher DE, Witte MJ, Glazer J (2001). EnergyPlus: Creating a new-generation building energy simulation program. Energy and Buildings, 33: 319–331. CrossRef
- DeST (2008). DeST-c User Manual. DeST Group, Tsinghua University, China. (in Chinese)
- EneryPlus (2009). Input/Output Rerference, Version 4.0 Documentation. University of Illinois and Ernest Orlando Lawrence Berkeley National Laboratory, USA.
- ESRU (1999). ESP-r: A Building and Plant Energy Simulation Environment, User Guide Version 9 Series. ESRU Publication, University of Strathclyde, Glasgow.
- Hitchcock G (1993). An integrated framework for energy use and behavior in the domestic sector. Energy and Buildings, 20: 151–157. CrossRef
- Hoes P, Hensen JLM, Loomans MGLC, de Vries B, Bourgeois D (2009). User behavior in whole building simulation. Energy and Buildings, 41: 295–302. CrossRef
- IEEA (2008). Residential monitoring to decrease energy use and carbon emissions in Europe.
- Klein SA, Beckman WA, Mitchell JW, Duffie JA, Duffie NA, Freeman TL, Mitchell JC, Braun JE, Evans BL, Kummer JP, Urban RE, Fiksel A, Thornton JW, Blair NJ, Williams PM, Bradley DE, Mcdowell TP, Kummert M (2004). TRNSYS 16—A transient System Simulation Program, User Manual. Solar Energy Laboratory, University of Wisconsin-Madison.
- Korjenic A, Bednar T (2011). Impact of lifestyle on the energy demand of a single family house. Building Simulation, 4: 89–95. CrossRef
- Li Z, Jiang Y (2006). Characteristics of cooling load and energy consumption of air conditioning in residential buildings in Beijing. Heating Ventilating & Air Conditioning, 36(8): 1–6. (in Chinese)
- Mahdavi A, Lambeva L, Mohammadi A, Kabir E, Pröglhöf C (2007). Two case studies on user interactions with buildings’ environmental systems. Bauphysik, 29: 72–75. CrossRef
- Nicol JF (2001). Characterising occupant behaviour in buildings: Towards a stochastic model of occupant use of windows, lights, blinds, heaters and fans. In: Proceedings of IBPSA Building Simulation Conference and Exhibition (pp. 1073–1078), Rio de Janeiro, Brazil.
- O’Doherty J, Lyons S, Tol RSJ (2008). Energy-using appliances and energy-saving features: Determinants of ownership in Ireland. Applied Energy, 85: 650–662. CrossRef
- Ouyang JL, Gao JL, Luo XY, Ge J, Hokao K (2007). A study on the relationship between household lifestyles and energy consumption of residential buildings in China. Journal of South China University of Technology (Natural Science Edition), 35(z1): 171–174. (in Chinese)
- Reinhart CF (2004). Lightswitch-2002: A model for manual and automated control of electric lighting and blinds. Solar Energy, 77: 15–28. CrossRef
- Rijal HB, Tuohy P, Humphreys MA, Nicol JF, Samuel A, Clarke J (2007). Using results from field surveys to predict the effect of open windows on thermal comfort and energy use in buildings. Energy and Buildings, 39: 823–836. CrossRef
- van Raaij WF, Verhallen TMM (1983). A behavioral model of residential energy use. Journal of Economic Psychology, 3: 119–143.
- Yan D, Xia J, Tang W, Song F, Zhang X, Jiang Y (2008). DeST—An integrated building simulation toolkit Part I: Fundamentals. Building Simulation, 1: 95–110. CrossRef
- Yun GY, Steemers K (2008). Time-dependent occupant behavior models of window control in summer. Building and Environment, 43: 1471–1482. CrossRef
- Zhang X, Xia J, Jiang Z, Huang J, Qin R, Zhang Y, Liu Y, Jiang Y (2008). DeST—An integrated building simulation toolkit Part II: Applications. Building Simulation, 1: 193–209. CrossRef
- Quantitative description and simulation of human behavior in residential buildings
Volume 5, Issue 2 , pp 85-94
- Cover Date
- Print ISSN
- Online ISSN
- Tsinghua Press
- Additional Links
- human behavior
- behavioral object
- energy use
- lifestyle model
- time related
- environmentally related