  Distribution system residential load modeling and analysis for different
geographic areas within a utility or an independent system operator territory
are critical for enabling small-scale, aggregated distributed energy resources
to participate in grid services under Federal Energy Regulatory Commission
Order No. 2222 [1]. In this study, we develop a methodology of modeling
residential load profiles in different geographic areas with a focus on human
behavior impact. First, we construct a behavior-based load profile model
leveraging state-of-the-art appliance models. We simulate human activity and
occupancy using Markov chain Monte Carlo methods calibrated with the American
Time Use Survey data set. Second, we link our model with cleaned Current
Population Survey data from the U.S. Census Bureau. Finally, we populate two
sets of 500 households using California and Texas census data, respectively, to
perform an initial analysis of the load in different geographic areas with
various group features (e.g., different income levels). To distinguish the
effect of population behavior differences on aggregated load, we simulate load
profiles for both sets assuming fixed physical household parameters and weather
data. Analysis shows that average daily load profiles vary significantly by
income and income dependency varies by locality.
