PNNL

The Science

COVID-19 changed when and where we use electricity. A new study explored the impact of COVID-19 on electricity consumption and its variability across time, space, and customer type. Researchers compared and contrasted three unique datasets of electricity consumption before and during the pandemic. Importantly, the analysis shows that the apparent impact of COVID-19 varied depending on the spatiotemporal scale and level of aggregation of the examined data. The COVID-19 signal was most apparent in the customer class-specific dataset. It became diluted in datasets that combined customer class loads and aggregated loads over large regions. The researchers identified offsetting signals that masked the true impacts of COVID-19 on aggregate scale electricity loads.

The Impact

The novelty of this work is its analysis of three independent observed electricity consumption datasets at different scales and sectoral resolutions. Combined, these datasets provide a comprehensive view of the impact of COVID-19 on electricity demand, from the hourly demand of individual customers to monthly state-level impacts. The analysis shows the importance of modeling diurnal load patterns by customer class to understand changes in the total load profile due to COVID-19. Analyses focused on total load or a single scale may miss important changes visible when examining the load by region or customer class. This research could be used to improve future load forecasts to account for the persistence of COVID-19-induced changes in patterns of electricity consumption.

Summary

COVID-19 induced changes to when and where we use electricity, creating an unprecedented source of uncertainty for the electric grid. COVID-19 affected electricity consumption in multiple ways, with the type of impact varying by scale. At the customer class scale, weekday residential load profiles in the spring and summer of 2020 looked like historical weekend load profiles. Commercial loads were significantly smaller in the spring and summer of 2020 but maintained a shape consistent with previous years. At the balancing authority scale, weekend-like load profiles occurring on weekdays were recognizable in the spring of 2020 but became undiscernible after June. However, COVID-19 impacts were apparent in the summer of 2020 when the load was analyzed zone-by-zone within the balancing authority. COVID-19 impacts were masked at the state scale because residential and commercial sector usage moved in opposite directions.

Researchers also identified several types of offsetting effects that acted to mute the COVID-19 signal in overall electricity demand:

• The impact of COVID-19 was dampened across all scales because changes in residential and non-residential loads had a similar magnitude but opposite signs.
• Summer loads became more strongly dependent on diurnal temperature variations and less dependent on inhabitance schedules. This acted to reduce the impact of more people staying home during the day.
• Phased reopening and spatial variability in reopening during summer 2020 masked the COVID-19 signal when total load data were analyzed at the aggregate balancing authority scale.

The observed and potential shifts in electricity load profiles documented in the study motivate new approaches for predicting the long-term changes in total hourly loads that explicitly represent potential shifts in consumer behavior and economics. While some changes to the ways Americans work and live are likely to revert to pre-COVID-19 conditions, others like widespread teleworking may become permanent fixtures. The results suggest that the “new normal” may not be a singular permanent change in how people consume electricity, but rather an increase in the variability of electricity consumption patterns across sectors and scales.

PNNL Contact

Jennie Rice, Pacific Northwest National Laboratory, jennie.rice@pnnl.gov

Funding

This research was supported by the Department of Energy, Office of Science, as part of research in the MultiSector Dynamics, Earth and Environmental System Modeling Program.