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Influence of population mobility on electricity consumption in seven U.S. cities during the Covid-19 pandemic

Bibliographic Data

ID12246363
AuthorsZhifeng Guo (0000-0003-0937-7667, University of Kent), J R O’Hanley (0000-0003-3522-8585, University of Kent, corresponding author), Stuart Gibson (0000-0002-7981-241X, University of Kent)
Year2024
Volume90
Pages101804-101804
Publication date2024-07-26
Open AccessYes
TypeARTICLE
VenueUtilities Policy (JOURNAL)
Journal identifiersISSN: 0957-1787 • E-ISSN: 1878-4356
PublisherElsevier BV (PUBLISHER)
DOI10.1016/j.jup.2024.101804
OpenAlexW4401025676
LanguageEN
Citations received2
References cited20

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

2019-20 coronavirus outbreak · Bayesian probability · Consumption (sociology · Coronavirus disease 2019 (COVID-19 · Econometrics · Economics · Electricity · Geography · Mains electricity · Pandemic · Population · Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2 · Sociology · Statistics · COVID-19 epidemiological studies · COVID-19 impact on air quality · COVID-19 Pandemic Impacts · Demography · Engineering · Mathematics · Medicine · Virology

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Citations per year2
Citation span2025 - 2026 (2)
Highly citedNo

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