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. 2020 Aug 17:8:151523-151534.
doi: 10.1109/ACCESS.2020.3016912. eCollection 2020.

Impact of the COVID-19 Pandemic on the U.S. Electricity Demand and Supply: An Early View From Data

Duzgun Agdas  1 , Prabir Barooah  2
Affiliations

Impact of the COVID-19 Pandemic on the U.S. Electricity Demand and Supply: An Early View From Data

Duzgun Agdas et al. IEEE Access. .

Abstract

After the onset of the recent COVID-19 pandemic, a number of studies reported on possible changes in electricity consumption trends. The overall theme of these reports was that "electricity use has decreased during the pandemic, but the power grid is still reliable"-mostly due to reduced economic activity. In this paper, we analyze electricity data until the end of May 2020, examining both electricity demand and variables that can indicate stress on the power grid. We limit this study to three states in the U.S. California, Florida and New York. The results indicate that the effect of the pandemic on electricity demand is not a simple reduction, and there are noticeable differences among regions analyzed. The variables that can indicate stress on the grid (e.g., daily peak and trough of the hourly demand, demand ramp rate, demand forecast error, and net electricity interchange) also conveyed mixed messages: some indicate an increase in stress, some indicate a decrease, and some do not indicate any clear difference. A positive message is that some of the changes that were observed around the time stay-at-home orders were issued appeared to revert back by May 2020. A key challenge in ascribing any observed change to the pandemic is correcting for weather as it can be challenging to accurately define it for large geographic regions. We provide a weather-correction method, apply it to a small city-wide area in North Central Florida, and discuss the implications of the estimated changes in demand. The results indicate that a 10% (95% CI [2%, 18%]) increase in electricity demand is likely to have occurred due to COVID-19 for the city analyzed.

Keywords: COVID-19; Electricity; forecasting; power grid operation; regression; weather correction.

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Figures

FIGURE 1.
FIGURE 1.
Daily electricity demand for Florida for March-May 2019 and 2020 (The first Monday of March for both years are vertically aligned).
FIGURE 2.
FIGURE 2.
Daily Electricity Demand for California for March-May 2019 and 2020 (The first Monday of March for both years are vertically aligned).
FIGURE 3.
FIGURE 3.
Daily electricity demand for New York for March-May 2019 and 2020 (The first Monday of March for both years are vertically aligned).
FIGURE 4.
FIGURE 4.
Distributions of daily peak demand (of hourly energy) in three regions in the US. Data from Jan - May, during 2019 and 2020, are used to estimate the pdfs.
FIGURE 5.
FIGURE 5.
Daily peak-trough of hourly demand for each day, March-May 2019 and 2020 (The first Monday of March 2019 is aligned with the first Monday of March 2020).
FIGURE 6.
FIGURE 6.
Probability densities of hourly demand ramp rate, with 4 weeks of data after the stay-home order in 2020, and the corresponding period in 2019.
FIGURE 7.
FIGURE 7.
Probability densities of hourly demand ramp rate, during months away from the pandemic (before and after).
FIGURE 8.
FIGURE 8.
Daily average of the hourly demand forecast error, 2020 vs. 2019.
FIGURE 9.
FIGURE 9.
Hourly demand forecast error probability densities, with data from a four week period starting on the day stay-at-home order was issued. The 2019 data was for the corresponding period.
FIGURE 10.
FIGURE 10.
Empirical probability densities of the hourly demand forecast errors. Each pdf is computed with data from a four week period, except for those for May 2020.
FIGURE 11.
FIGURE 11.
Mean interchange, 2020 vs. 2019.
FIGURE 12.
FIGURE 12.
Hourly demand prediction for 3 distinct years by the model (1) trained with 2019 March data. The x-axis starts on the first Monday of March for each year.
FIGURE 13.
FIGURE 13.
Weather corrected daily energy demand in 2020 for GRU: difference between 2020 demand and its predicted value by the model (1). The stay-at-home order was issued by the Alachua county to take effect on March 24, 2020.
FIGURE 14.
FIGURE 14.
Change in weather corrected daily energy demand for GRU during March-April for two pre-pandemic datasets. The model is trained with 2019 data, so the top plot shows the in-sample prediction error.
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