Changes in hourly electricity consumption under COVID mandates: A glance to future hourly residential power consumption pattern with remote work in Arizona. (15th March 2022)

• Record Type: Journal Article
• Authors: Ku, Arthur Lin; Qiu, Yueming (Lucy); Lou, Jiehong; Nock, Destenie; Xing, Bo
• Is Part Of: Applied energy. Volume 310(2022)
• Publication Date: 2022-03-15
• Subjects: Electricity load forecast -- COVID mandates -- High-frequency consumer-level data -- Random forest -- Race and income -- Time-of-use rate; Power (Mechanics) -- Periodicals; Energy conservation -- Periodicals; Energy conversion -- Periodicals; 621.042
• DOI: 10.1016/j.apenergy.2022.118539
• Languages: English
• ISSNs: 0306-2619

Abstract

Highlights: We use a large sample of consumer-level high frequency smart meter data. Power load in winter changes from a two-peaked shape to a one-peaked shape. COVID mandates increase the power consumption in the afternoon by 13%. Race and income are correlated with the electricity consumption changes. Modifying time-of-use electricity pricing can alleviate the impact of remote work. Abstract: The transition to remote work brings uncertainty to the future power consumption pattern. The COVID mandates in 2020 have accelerated the transition to remote work, generating major uncertainty regarding how residential power consumption patterns will shift. Understanding these shifts is vital for regional operators who will need to implement long-term planning strategies if companies continue to adopt remote work practices. Additionally, if new COVID variants prompt extended stay-at-home mandates, the resulting behavior shifts will decide the optimal combination of power generation in a region. Our study examines changes in hourly residential power consumption patterns resulting from COVID mandates in Arizona. We estimate how the COVID mandates and subsequent remote work practices could change the power consumption patterns using individual-consumer-level hourly power consumption data for 6, 309 consumers and a machine learning framework. We also simulate how the hourly power consumption pattern will change with increasing penetration of remote work under winter and summer temperature settings. We then use our simulations to test the policy effectiveness of changing time-of-use (TOU) rates. Our results show that COVID mandates likely increase the power consumption in the afternoon by 13%, and can change the power consumption pattern in winter from a two-peaked shape to a one-peaked shape. Furthermore, we show that the residents' income, race, and house size are significantly correlated with the changes in power consumption, and the correlation is not linear. We find that, by increasing the peak hour prices and decreasing the off-peak hour prices by 10% of the TOU pricing, the peak electricity demand could be reduced by 10%. Our results show under the new remote work era: (1) the need for modifying previous energy generation combination planning due to changing peak demand hours; (2) equity concerns regarding TOU pricing and the inability of vulnerable groups to shift electricity consumption; (3) the ability of governments and utilities to lower the maximum load of power consumption by modifying the TOU rates.