Guo, Zhifeng, O'Hanley, J.R., Gibson, Stuart J. (2024) Influence of population mobility on electricity consumption in seven U.S. cities during the COVID-19 pandemic. Utilities Policy, 90 . Article Number 101804. ISSN 0957-1787. E-ISSN 1878-4356. (doi:10.1016/j.jup.2024.101804) (KAR id:106626)
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Official URL: https://doi.org/10.1016/j.jup.2024.101804 |
Abstract
We examine the impact of the COVID-19 pandemic on electricity consumption in seven U.S. cities. A high-level analysis reveals that reductions in electricity consumption were mostly short-term, mainly when lockdowns were first introduced. Bayesian structural time series modeling was used to decompose electricity consumption into multiple tailored components to better understand the pandemic’s impact. We find that models incorporating population mobility achieved high accuracy rates using pre-pandemic data and even better rates using post-pandemic data. Electricity usage dropped during the first six weeks of the pandemic in all but one of the cities studied.
Item Type: | Article |
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DOI/Identification number: | 10.1016/j.jup.2024.101804 |
Uncontrolled keywords: | electricity demand forecasting; COVID-19 pandemic; Bayesian structural time series |
Subjects: |
H Social Sciences Q Science |
Divisions: |
Divisions > Division of Natural Sciences > Chemistry and Forensics Divisions > Kent Business School - Division > Department of Analytics, Operations and Systems |
Funders: | University of Kent (https://ror.org/00xkeyj56) |
Depositing User: | Jesse O'Hanley |
Date Deposited: | 19 Jul 2024 09:46 UTC |
Last Modified: | 21 Mar 2025 11:31 UTC |
Resource URI: | https://kar.kent.ac.uk/id/eprint/106626 (The current URI for this page, for reference purposes) |
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