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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.

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Figures

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Fig. 1

Architecture of SABEC model

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Fig. 2

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

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Fig. 3

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

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Fig. 4

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

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Fig. 5

Comparison of electricity consumption for both design alternatives

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