Behavioral and Population Data-Driven Distribution System Load Modeling

Issac Bromley-Dulfano, Xiangqi Zhu, Barry Mather

Research output: Contribution to conferencePaperpeer-review

1 Scopus Citations


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.

Original languageAmerican English
Number of pages6
StatePublished - 2022
Event49th IEEE Photovoltaics Specialists Conference, PVSC 2022 - Philadelphia, United States
Duration: 5 Jun 202210 Jun 2022


Conference49th IEEE Photovoltaics Specialists Conference, PVSC 2022
Country/TerritoryUnited States

Bibliographical note

Publisher Copyright:
© 2022 IEEE.

NREL Publication Number

  • NREL/CP-6A40-81349


  • American Time Use Survey
  • Behavior-based Load Profile Modeling
  • Markov chain Monte Carlo
  • U.S. Census


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