# Evaluating the Impact of the COVID-19 Pandemic on Residential Energy Use in Los Angeles
## 1 Introduction  
In 2020, changes in energy use and emissions were seen worldwide as a direct effect of the COVID-19 pandemic [1, 2, 3, 4, 5, 6]. Mandatory stay-at-home periods globally reduced jet and aviation fuel by 50%, gasoline by 30%, and electricity (on average) about 10 percent during the early pandemic where shelter-in-place (SIP) orders were widespread across many regions. This reduction was followed by partial rebounds for all mentioned energy types later in 2020 [7, 8, 9, 10, 11]. While commercial transport and mobility to support commercial activities (e.g., commuting for work) were greatly reduced by a curtailment in overall business activities, the impact on residential energy use is harder to directly assess frompublicly available electrical grid regional operator data. Preliminary results from studies early in the pandemic suggest increased residential energy use, but results vary [12; 13; 14]. Further, little attention has been paid to understanding the mechanisms leading to this change in energy use during both the early pandemic SIP periods and periods following, in addition to regressive periods due to regional re-closures due to increased COVID-19 cases. Analysis of total energy use for a given region provides conclusions for macro trends. However, analyzing data comprised of heavily mixed sectors (residential and commercial loads) and as a combined set across all day types (weekends and weekdays) provides limited utility for sector-based analysis, and complicates actionable model adjustments for energy planning and conservation efforts. Approximately 21% of energy use nationwide is from residential customers [15]. Residential energy efficiency is a substantial focus for utility programs, but sector changes can be obscured within direct regional load figures. While a general decrease in energy use was broadly observed across most regions worldwide during the 2020 COVID-19 pandemic, modeling and planning difficulties when predicting future demand led to service disruptions. Most notably, poor forecasting models for pandemic-related changes in energy use directly led to widespread rolling blackouts in California in mid-August of 2020 during a substantial heatwave [16; 17]. The 2020 pandemic period exhibited increased reliance on non-dispatchable, low carbon energy sources, with increases of 22.3% solar production and 13.5% wind production in the US compared to 2019 [18]. Understanding sector-focused changes in energy use helps improve demand predictions for future widespread lockdown events in an era of increasing effects of climate change and increased reliance on non-dispatchable and distributed generation. Residential electric load is primarily comprised of the following major load categories: electricity-driven space conditioning (air conditioning, ventilation/forced air circulation, and electric heaters), lighting, major appliances, miscellaneous (plug) loads, constant building loads, and electric transportation. Of these categories, only space conditioning is directly temperature sensitive. Demand from three other categories--lighting, major appliances, and plug loads--is largely driven by occupancy without substantial regard to ambient temperature. With 42% of US residential use due to space conditioning, ambient temperature is a primary driver of residential electricity use, especially with high air conditioning penetration [15; 18; 19]. Despite the mild climate in Southern California, [PERSON] et al. assessed a substantial (69% estimated) regional household penetration for air conditioning [19; 20]. This includes residential air conditioning systems in different form factors and cooling capacities. For temperature-sensitive loads, both increased occupancy and the reaction of occupants to change in the ambient temperature affect energy use. For the remaining categories, changes in daily occupancy rates (occupied by none versus one or more individuals) and resulting changes in device use behavior (i.e., which loads or devices are used and how they are used) are the main considerations.