a cross domain approach to analyzing the short run impact of covid 19 on the us electricity sector

• DOI: 10.48550/arxiv.2005.06631
• Publication Date: 2020-01-01
• Authors: Haiwang Zhong; Dongqi Wu; S. Sivaranjani; Chongqing Kang; Guangchun Ruan; Guangchun Ruan; Le Xie; Xiangtian Zheng; Munther A. Dahleh
• Keywords: FOS: Computer and information sciences; Systems and Control (eess.SY); 02 engineering and technology; 16. Peace & justice; Electrical Engineering and Systems Science - Systems and Control; 01 natural sciences; 7. Clean energy; 3. Good health; Computer Science - Computers and Society; Optimization and Control (math.OC); 13. Climate action; Report; Computers and Society (cs.CY); FOS: Electrical engineering, electronic engineering, information engineering; FOS: Mathematics; 0202 electrical engineering, electronic engineering, information engineering; 0101 mathematics; Mathematics - Optimization and Control

The novel coronavirus disease (COVID-19) has rapidly spread around the globe in 2020, with the U.S. becoming the epicenter of COVID-19 cases since late March. As the U.S. begins to gradually resume economic activity, it is imperative for policymakers and power system operators to take a scientific approach to understanding and predicting the impact on the electricity sector. Here, we release a first-of-its-kind cross-domain open-access data hub, integrating data from across all existing U.S. wholesale electricity markets with COVID-19 case, weather, cellular location, and satellite imaging data. Leveraging cross-domain insights from public health and mobility data, we uncover a significant reduction in electricity consumption across that is strongly correlated with the rise in the number of COVID-19 cases, degree of social distancing, and level of commercial activity.<br/>This paper has been accepted for publication by Joule. The manuscript can also be accessed from EnerarXiv: http://www.enerarxiv.org/page/thesis.html?id=1989<br/>