Abstract

An accurate representation of occupancy schedules is needed to assess potential energy savings from occupancy-based controls in residential buildings. In this study the variation in US residential occupancy profiles is developed by household income level, age group, household size, and day of the week using 14 years of American Time Use Survey and Current Population Survey data. Based on cluster analysis results, the most common occupancy profiles were Day absence and Stay home where, the time of absence varies from less than 5 to 15 h per day. Low-income individuals and households spent significantly more time at home compared to higher income groups. Finally, a preliminary survey conducted to analyse the impacts of the COVID-19 pandemic suggests that it has substantially impacted occupancy patterns and is likely to do so post-pandemic as well. The results of this research help improve the representation of occupancy schedules in building energy simulation methods.

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