期刊
ENERGY AND BUILDINGS
卷 251, 期 -, 页码 -出版社
ELSEVIER SCIENCE SA
DOI: 10.1016/j.enbuild.2021.111330
关键词
COVID-19 pandemic; Electricity usage characteristics; Residential peak demand; Monte Carlo simulation; New grid-management challenges
资金
- U.S. Depart-ment of Energy's Office of Energy Efficiency and Renewable Energy (EERE) , under the Building Technologies Office's BENEFIT program [DE-EE-0007864]
This study analyzed the impact of COVID-19 pandemic on residential electricity usage in New York City, predicting potential increases in electricity consumption under stay-at-home orders and warm summer weather. The study also highlighted the potential grid management challenges that could arise from the projected increase in peak demand.
Stay-at-home orders and other health precautions enacted during the COVID-19 pandemic have led to substantial changes in residential electricity usage. We conduct a case study to analyze data from 390 apartments in New York City (NYC) to examine the impacts of two key drivers of residential electricity usage: COVID-19 case-loads and the outdoor temperature. We develop a series of regression models to predict two characteristics of residential electricity usage on weekdays: The average occupied apart-ment's consumption (kWh) over a 9am-5pm window and the hourly peak demand (Watt) over a 12pm-5pm window. Via a Monte Carlo simulation, we forecast the two usage characteristics under a pos-sible scenario in which stay-at-home orders in NYC, or a similar metropolitan region, coincide with warm summer weather. Under the scenario, the 9am-5pm residential electricity usage on weekdays is pre-dicted to be 15% - 24% higher than under prior, pre-pandemic conditions. This could lead to substantially higher utility costs for residents. Additionally, we predict that the residential hourly peak demand between 12pm and 5pm on weekdays could be 35% - 53% higher than that under pre-pandemic condi-tions. We conclude that the projected increase in peak demand -which might arise if stay-at-home guidelines coincided with hot weather conditions -could pose grid management challenges, especially for residential feeders. We also note that, if there is a longer lasting shift towards work and study-from-home, utilities will have to rethink load profile considerations. The applications of our predictive models to managing future smart-grid technology are also highlighted. (c) 2021 Published by Elsevier B.V.
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