Buildings are responsible for approximately 74% of total electricity consumption, the leading contributor of carbon dioxide emissions in the United States. As initiatives aim toward net zero emissions through electrification and clean energy, building energy efficiency measures are crucial to achieve this clean energy transition. Through measuring energy use, this increases the accuracy of building use assumptions, which drive how energy use reduction is investigated and targeted. As disruptive events and technology shift how occupants use residential buildings, this has the potential to shift how they consume their energy. In this thesis, high resolution, disaggregated energy use data is used to model and analyze energy use for two specific disruptions: the COVID-19 pandemic and electric vehicles (EVs). The first study measures how COVID-19 impacted residential building energy use. The findings of this research indicate an increase in energy use for both weather-dependent loads and weather-independent loads during the COVID-19 pandemic. Additional analyses give insight to the pandemic's impact by household income, demonstrating the lowest and highest income groups experiencing larger increases in consumption while remaining populations experienced smaller shifts. The second study analyzes residential EV charging behavior and models the maximum load reduction potential for demand response in the Midcontinent Independent System Operator (MISO) region. The results of this study indicate relatively consistent charging use patterns across a full year, weekend charging is more distributed throughout the daytime compared to weekday charging, and there are significant opportunities to reduce or shift EV loads during typical peak load periods.
Read
