Papers: Modeling user behaviors and activities adapted to use contexts

An Occupant-Based Energy Consumption Model for User-Focused Design of Residential Buildings

[+] Author and Article Information
Toufic Zaraket

Ecole Centrale Paris,
Laboratoire Genie Industriel,
Grande Voie des Vignes,
Chatenay-Malabry 92290, France
e-mail: toufic.zaraket@ecp.fr

Bernard Yannou

Ecole Centrale Paris,
Laboratoire Genie Industriel,
Grande Voie des Vignes,
Chatenay-Malabry 92290, France

Yann Leroy

Ecole Centrale Paris,
Laboratoire Genie Industriel,
Grande Voie des Vignes,
Chatenay-Malabry 92290, France

Stéphanie Minel, Emilie Chapotot

Ecole Nationale Supérieure de Création Industrielle,
48 rue Saint Sabin,
Paris 75011, France

1Corresponding author.

Contributed by the Design Automation Committee of ASME for publication in the JOURNAL OF MECHANICAL DESIGN. Manuscript received September 14, 2014; final manuscript received March 24, 2015; published online May 19, 2015. Assoc. Editor: Wei Chen.

J. Mech. Des 137(7), 071412 (Jul 01, 2015) (5 pages) Paper No: MD-14-1575; doi: 10.1115/1.4030202 History: Received September 14, 2014; Revised March 24, 2015; Online May 19, 2015

Occupants' behavior exerts a significant influence on the energy performance of residential buildings. Industrial energy simulation tools often account for occupants' as monolithic elements with standard averaged energy consumption profiles. Predictions yielded by these tools can thus deviate dramatically from reality. This paper proposes an activity-based model for forecasting energy and water consumption of households and discusses how such an occupant-focused model may integrate a user-focused design of residential buildings. A literature review is first presented followed by a brief recall of the proposed modeling methodology and a sample of simulation results. The possible integration of the proposed model into the design and energy management processes of residential buildings is then demonstrated through a number of use cases.

Copyright © 2015 by ASME
Your Session has timed out. Please sign back in to continue.


Saidur, R., Masjuki, H. H., and Jamaluddin, M. Y., 2007, “An Application of Energy and Exergy Analysis in Residential Sector of Malaysia,” Energy Policy, 35(2), pp. 1050–1063. [CrossRef]
Masoso, O. T., and Grobler, L. J., 2010, “The Dark Side of Occupants' Behaviour on Building Energy Use,” Energy Build., 42(2), pp. 173–177. [CrossRef]
Hoes, P., Hensen, J., Loomans, M., De Vries, B., and Bourgeois, D., 2009, “User Behavior in Whole Building Simulation,” Energy Build., 41(3), pp. 295–302. [CrossRef]
EPBD, 2014, “Concerted Action Energy Performance of Buildings Directive,” Accessed Sept. 13, 2014, http://www.epbd-ca.eu/
Vierra, S., 2011, “Green Building Standards and Certification Systems | Whole Building Design Guide,” Accessed Sept. 13, 2014, http://www.wbdg.org/resources/gbs.php
CPE, 2012, “Contrats de performance énergétique—Ministère du Développement durable,” Accessed Feb. 10, 2014, http://www.developpement-durable.gouv.fr/Contrats-de-performance,28987.html
Page, J., Robinson, D., Morel, N., and Scartezzini, J. L., 2008, “A Generalised Stochastic Model for the Simulation of Occupant Presence,” Energy Build., 40(2), pp. 83–98. [CrossRef]
Yu, Z., Fung, B. C. M., Haghighat, F., Yoshino, H., and Morofsky, E., 2011, “A Systematic Procedure to Study the Influence of Occupant Behavior on Building Energy Consumption,” Energy Build., 43(6), pp. 1409–1417. [CrossRef]
Pachauri, S., 2004, “An Analysis of Cross-Sectional Variations in Total Household Energy Requirements in India Using Micro Survey Data,” Energy Policy, 32(15), pp. 1723–1735. [CrossRef]
Fabi, V., Andersen, R., Corgnati, S., and Olesen, B., 2012, “Occupants' Window Opening Behaviour: A Literature Review of Factors Influencing Occupant Behaviour and Models,” Build. Environ., 58(12), pp. 188–198. [CrossRef]
Swan, L. G., and Ugursal, V. I., 2009, “Modeling of End-Use Energy Consumption in the Residential Sector: A Review of Modeling Techniques,” Renewable Sustainable Energy Rev., 13(8), pp. 1819–1835. [CrossRef]
Clevenger, C. M., and Haymaker, J., 2006, “The Impact of the Building Occupant on Energy Modeling Simulations,” Proceedings of the Joint International Conference on Computing and Decision Making in Civil and Building Engineering, Montreal, Canada, June 14–16, pp. 1–10.
Seryak, J., and Kissock, K., 2003, “Occupancy and Behavioral Affects on Residential Energy Use,” Proceedings of the Solar Conference, Austin, TX, pp. 717–722.
Emery, A. F., and Kippenhan, C. J., 2006, “A Long Term Study of Residential Home Heating Consumption and the Effect of Occupant Behavior on Homes in the Pacific Northwest Constructed According to Improved Thermal Standards,” Energy, 31(5), pp. 677–693. [CrossRef]
Malavazos, C., Tzovaras, D., Kehagias, D., and Ioannidis, D., 2011, “Energy and Behavioural Modelling and Simulation for EE-Buildings Design,” Proceedings of the CIB W78-W102 2011: International Conference, Sophia Antipolis, France, Oct. 26–28, pp. 92–105.
Kashif, A., Ploix, S., Dugdale, J., and Binh Le, X. H., 2013, “Simulating the Dynamics of Occupant Behaviour for Power Management in Residential Buildings,” Energy Build., 56(1), pp. 85–93. [CrossRef]
Bourgeois, D., Reinhart, C., and Macdonald, I., 2006, “Adding Advanced Behavioural Models in Whole Building Energy Simulation: A Study on the Total Energy Impact of Manual and Automated Lighting Control,” Energy Build., 38(7), pp. 814–823. [CrossRef]
Chiou, Y.-S., 2009, “Deriving U.S. Household Energy Consumption Profiles From American Time Use Survey Data a Bootstrap Approach,” Proceedings of the 11th International Building Performance Simulation Association Conference and Exhibition, Glasgow, Scotland, July 27–30, pp. 151–158.
Zaraket, T., 2014, “Stochastic Activity-Based Approach of Occupant-Related Energy Consumption in Residential Buildings,” Doctoral dissertation, Ecole Centrale Paris, Châtenay-Malabry, France.
Ellegård, K., and Palm, J., 2011, “Visualizing Energy Consumption Activities as a Tool for Making Everyday Life More Sustainable,” Appl. Energy, 88(5), pp. 1920–1926. [CrossRef]
Pennavaire, C., 2010, “Comprehensive Modeling of Energy Use in Households. An Agent Based Case Study on Potential Behavioural and Technical Measures Towards an Energy Neutral Urban Environment,” Master's thesis, Master of Science in Construction Management and Engineering, University of Technology, Eindhoven, The Netherlands.
Kashif, A., Ploix, S., Dugdale, J., and Le, X. H. B., 2011, “Agent Based Framework to Simulate Inhabitants' Behaviour in Domestic Settings for Energy Management,” Proceedings of the 3rd International Conference on Agents and Artificial Intelligence (ICAART 2011), Rome, Italy, Jan. 28–30, pp. 190–199.
Swan, L. G., and Ugursal, V. I., 2009, “Modeling of End-Use Energy Consumption in the Residential Sector: A Review of Modeling Techniques,” Renewable Sustainable Energy Rev., 13(8), pp. 1819–1835. [CrossRef]
Yao, R., and Steemers, K., 2005, “A Method of Formulating Energy Load Profile for Domestic Buildings in the UK,” Energy Build., 37(6), pp. 663–671. [CrossRef]
Yun, G. Y., and Steemers, K., 2011, “Behavioural, Physical and Socio-Economic Factors in Household Cooling Energy Consumption,” Appl. Energy, 88(6), pp. 2191–2200. [CrossRef]
Paauw, J., Roossien, B., Aries, M. B. C., and Santin, O. G., 2009, “Energy Pattern Generator; Understanding the Effect of User Behaviour on Energy Systems,” Proceedings of the 1st European Conference Energy Efficiency and Behaviour, Maastricht, The Netherlands, Oct. 18–19, pp. 9–10.
Weber, C., and Perrels, A., 2000, “Modelling Lifestyle Effects on Energy Demand and Related Emissions,” Energy Policy, 28(8), pp. 549–566. [CrossRef]
Mansouri, I., Newborough, M., and Probert, D., 1996, “Energy Consumption in UK Households: Impact of Domestic Electrical Appliances,” Appl. Energy, 54(3), pp. 211–285. [CrossRef]
Lutzenhiser, L., and Bender, S., 2008, “The ‘Average American’ Unmasked: Social Structure and Differences in Household Energy Use and Carbon Emissions,” Proceedings of the 2008 ACEEE Summer Study on Energy Efficiency in Buildings, American Council for an Energy Efficient Economy, Washington, DC, pp. 191–204.
Guerin, D. A., Yust, B. L., and Coopet, J. G., 2000, “Occupant Predictors of Household Energy Behavior and Consumption Change as Found in Energy Studies Since 1975,” Fam. Consum. Sci. Res. J., 29(1), pp. 48–80. [CrossRef]
Nugroho, S. B., Fujiwara, A., Zhang, J., Kanemoto, K., Moersidik, S. S., and Abbas, S., 2010, “Development of a Household Energy Consumption Model for Megacities in Asia,” The 16th Annual International Sustainable Development Research Conference, Hong Kong, China, May 30–June 1.
Yun, G. Y., Tuohy, P., and Steemers, K., 2009, “Thermal Performance of a Naturally Ventilated Building Using a Combined Algorithm of Probabilistic Occupant Behaviour and Deterministic Heat and Mass Balance Models,” Energy Build., 41(5), pp. 489–499. [CrossRef]
McLoughlin, F., Duffy, A., and Conlon, M., 2012, “Characterising Domestic Electricity Consumption Patterns by Dwelling and Occupant Socio-Economic Variables: An Irish Case Study,” Energy Build., 48(2), pp. 240–248. [CrossRef]
Yohanis, Y. G., Mondol, J. D., Wright, A., and Norton, B., 2008, “Real-Life Energy Use in the UK: How Occupancy and Dwelling Characteristics Affect Domestic Electricity Use,” Energy Build., 40(6), pp. 1053–1059. [CrossRef]
Tanimoto, J., Hagishima, A., and Sagara, H., 2008, “Validation of Probabilistic Methodology for Generating Actual Inhabitants' Behavior Schedules for Accurate Prediction of Maximum Energy Requirements,” Energy Build., 40(3), pp. 316–322. [CrossRef]
Richardson, I., Thomson, M., Infield, D., and Delahunty, A., 2009, “Domestic Lighting: A High-Resolution Energy Demand Model,” Energy Build., 41(7), pp. 781–789. [CrossRef]
Richardson, I., Thomson, M., Infield, D., and Clifford, C., 2010, “Domestic Electricity Use: A High-Resolution Energy Demand Model,” Energy Build., 42(10), pp. 1878–1887. [CrossRef]
Widén, J., and Wäckelgård, E., 2010, “A High-Resolution Stochastic Model of Domestic Activity Patterns and Electricity Demand,” Appl. Energy, 87(6), pp. 1880–1892. [CrossRef]
Muratori, M., 2013, “A Highly Resolved Modeling Technique to Simulate Residential Power Demand,” Appl. Energy, 107(7), pp. 465–473. [CrossRef]
Subbiah, R., 2013, “An Activity-Based Energy Demand Modeling Framework for Buildings: A Bottom-Up Approach,” Master's thesis, Virginia Polytechnic Institute and State University, Blacksburg, VA.
Zaraket, T., Yannou, B., Leroy, Y., Minel, S., and Chapotot, E., 2013, “A Usage Model-Driven Approach for Forecasting Occupant-Related Energy Consumption in Residential Buildings,” Proceedings of CONFERE 2013, Biarritz, France. Available at: http://www.lgi.ecp.fr/uploads/Intranet/2013-05-17_PresentationZaraket.pdf
Zaraket, T., Yannou, B., Leroy, Y., Minel, S., and Chapotot, E., 2014, “A Stochastic Activity-Based Approach for Forecasting Occupant-Related Energy Consumption in Residential Buildings,” ASME Paper No. DETC2014-35528.
CPE, 2014, “Le site des contrats de performance énergétique,” Accessed Dec. 11, 2014, http://www.lecpe.fr/
Lemoniteur, 2011, “Energy Pass, nouvel outil de maîtrise des charges dans les bâtiments neufs,” Accessed Jan. 19, 2014, http://www.lemoniteur.fr/145-logement/article/actualite/860961-energy-pass-nouvel-outil-de-maitrise-des-charges-dans-les-batiments-neufs
Picon, L., Yannou, B., Zaraket, T., Minel, S., Bertoluci, G., Cluzel, F., and Farel, R., 2013, “Use-Phase Memory: A Tool for the Sustainable Construction and Renovation of Residential Buildings,” Autom. Constr., 36(12), pp. 53–70. [CrossRef]


Grahic Jump Location
Fig. 1

Architecture of SABEC model

Grahic Jump Location
Fig. 2

Cumulative distribution of electricity consumption values for the activity “watching TV” for a sample of 1000 randomly generated households

Grahic Jump Location
Fig. 3

Simulation results of electricity consumption for the activity “watching TV”: comparison between five household-type clusters of the French population

Grahic Jump Location
Fig. 4

Simulation results of electricity consumption for the activity “washing laundry”: variability of consumption as a function of the income cluster

Grahic Jump Location
Fig. 5

Comparison of electricity consumption for both design alternatives




Some tools below are only available to our subscribers or users with an online account.

Related Content

Customize your page view by dragging and repositioning the boxes below.

Related Journal Articles
Related eBook Content
Topic Collections

Sorry! You do not have access to this content. For assistance or to subscribe, please contact us:

  • TELEPHONE: 1-800-843-2763 (Toll-free in the USA)
  • EMAIL: asmedigitalcollection@asme.org
Sign In