A Method for Modeling Household Occupant Behavior to Simulate Residential Energy Consumption

Conference · Wed Jan 01 04:00:00 EST 2014

OSTI ID:1121822

Johnson, Brandon J ^[1]; Starke, Michael R ^[1]; Abdelaziz, Omar ^[1]; Jackson, Roderick K ^[1]; Tolbert, Leon M ^[2]

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1. ORNL
2. University of Tennessee, Knoxville (UTK)

This paper presents a statistical method for modeling the behavior of household occupants to estimate residential energy consumption. Using data gathered by the U.S. Census Bureau in the American Time Use Survey (ATUS), actions carried out by survey respondents are categorized into ten distinct activities. These activities are defined to correspond to the major energy consuming loads commonly found within the residential sector. Next, time varying minute resolution Markov chain based statistical models of different occupant types are developed. Using these behavioral models, individual occupants are simulated to show how an occupant interacts with the major residential energy consuming loads throughout the day. From these simulations, the minimum number of occupants, and consequently the minimum number of multiple occupant households, needing to be simulated to produce a statistically accurate representation of aggregate residential behavior can be determined. Finally, future work will involve the use of these occupant models along side residential load models to produce a high-resolution energy consumption profile and estimate the potential for demand response from residential loads.

• Research Organization: Oak Ridge National Laboratory (ORNL); Building Technologies Research and Integration Center (BTRIC)
• Sponsoring Organization: EE USDOE - Office of Energy Efficiency and Renewable Energy (EE)
• DOE Contract Number: AC05-00OR22725
• OSTI ID: 1121822
• Country of Publication: United States
• Language: English

Related Subjects

American Time Use Survey
Markov chain
Occupant behavior modeling
Residential energy consumption