Influence of population mobility on electricity consumption in seven US cities during the COVID-19 pandemic

被引:2
作者
Guo, Zhifeng [1 ]
O'Hanley, Jesse R. [1 ,2 ]
Gibson, Stuart [3 ]
机构
[1] Univ Kent, Kent Business Sch, Canterbury CT2 7PE, England
[2] Univ Kent, Ctr Logist & Sustainabil Analyt, Canterbury, England
[3] Univ Kent, Sch Phys Sci, Canterbury, England
关键词
Electricity demand forecasting; COVID-19; pandemic; Bayesian structural time series; IMPACT;
D O I
10.1016/j.jup.2024.101804
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
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.
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收藏
页数:13
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