@misc{945c34182a354adab8fcc7a6e35d0a90,
title = "Demographic Information Incorporated Household Energy Consumption Analysis",
abstract = "The high energy consumption from residential buildings provides them large potential to participate in demand response programs. To design appropriate demand response programs for residential buildings, it is important for electric utilities to know the energy consumption characteristics for different types of households so that utilities can send requests to the groups with a higher possibility to successfully respond. In this paper, we develop a load model to generate synthetic load profiles for different types of households incorporating demographical information including Current Population Survey data set and American Time Use Survey data set. The details of each data set and the details of the load models are presented. The synthetic household load profiles are generated by the load model and clustered into different groups based on state, age, number of occupants, income level, and city of the household. The average energy consumption characteristics for different groups of households are analyzed and compared, which will help electric utilities issue demand response signals to appropriate households.",
keywords = "building loads, demand response, energy consumption, household, load profile",
author = "Jiyu Wang and Xiangqi Zhu and Barry Mather",
year = "2023",
language = "American English",
series = "Presented at the 2023 IEEE Power & Energy Society General Meeting, 16-20 July 2023, Orlando, Florida",
type = "Other",
}