SMU Data Science Review
Abstract
In this paper, we present how electrical consumption can reveal insight into the novel COVID-19 pandemic spread. We analyze electrical power consumption provided by PPL Electric Utilities, Department of Labor’s unemployment claims, and the COVID-19 cases/deaths for the State of Pennsylvania to study the impact of the pandemic on the infrastructure. Using a SARIMA model as our benchmark and we analyzed the use of a SARIMAX model to forecast the power consumption in Pennsylvania 14 days ahead. Our work quantifies and illuminates the effect that the strict legislation passed to minimize the spread of COVID19 had a on power consumption. Most importantly, this study helps drive a greater understanding into the hidden cost of a global pandemic such as COVID-19.
Recommended Citation
Au, Jackson; Saldaña, Javier Jr.; Spanswick, Ben; and Santerre, John
(2020)
"Forecasting Power Consumption in Pennsylvania During the COVID-19 Pandemic: A SARIMAX Model with External COVID-19 and Unemployment Variables,"
SMU Data Science Review: Vol. 3:
No.
2, Article 6.
Available at:
https://scholar.smu.edu/datasciencereview/vol3/iss2/6
Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial 4.0 License