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Impacts of COVID-19 related stay-at-home restrictions on residential electricity use and implications for future grid stability

“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 electr...

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Detalles Bibliográficos
Autores principales: Li, Lechen, Meinrenken, Christoph J., Modi, Vijay, Culligan, Patricia J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Published by Elsevier B.V. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8995371/
https://www.ncbi.nlm.nih.gov/pubmed/35431417
http://dx.doi.org/10.1016/j.enbuild.2021.111330
Descripción
Sumario:“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 apartment’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 possible 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 predicted 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 conditions. 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.