Abstract
Intervention policies against COVID-19 have caused large-scale
disruptions globally, and led to a series of pattern changes in the
power system operation. Analyzing these pandemic-induced patterns is
imperative to identify the potential risks and impacts of this extreme
event. With this purpose, we developed an open-access data hub
(COVID-EMDA+), an open-source toolbox (CoVEMDA), and a few evaluation
methods to explore what the U.S. power systems are experiencing during
COVID-19. These resources could be broadly used for research, policy
making, or educational purposes. Technically, our data hub harmonizes a
variety of raw data such as generation mix, demand profiles, electricity
price, weather observations, mobility, confirmed cases and deaths.
Several support methods and metrics are then implemented in our toolbox,
including baseline estimation, regression analysis, and scientific
visualization. Based on these, we conduct three empirical studies on the
U.S. power systems and markets to introduce some new solutions and
unexpected findings. This conveys a more complete picture of the
pandemic’s impacts, and also opens up several attractive topics for
future work. Python, Matlab source codes, and user manuals are all
publicly shared on a Github repository.