COVID-19 pandemic ramifications on residential Smart homes energy use load profiles

Abstract

The COVID-19 pandemic has significantly affected people’s behavioral patterns and schedules because of stay-at-home orders and a reduction of social interactions. Therefore, the shape of electrical loads associated with residential buildings has also changed. In this paper, we quantify the changes and perform a detailed analysis on how the load shapes have changed, and we make potential recommendations for utilities to handle peak load and demand response. Our analysis incorporates data from before and after the onset of the COVID-19 pandemic, from an Alabama Power Smart Neighborhood with energy-efficient/smart devices, using around 40 advanced metering infrastructure data points. This paper highlights the energy usage pattern changes between weekdays and weekends pre– and post–COVID-19 pandemic times. The weekend usage patterns look similar pre– and post–COVID-19 pandemic, but weekday patterns show significant changes. We also compare energy use of the Smart Neighborhood with a traditional neighborhood to better understand how energy-efficient/smart devices can provide energy savings, especially because of increased work-from-home situations. HVAC and water heating remain the largest consumers of electricity in residential homes, and our findings indicate an even further increase in energy use by these systems.

Review of application of high frequency smart meter data in energy economics and policy research

“…Ku et al (2022) used individual hourly power consumption data within a machine learning framework to examine changes in electricity use patterns due to COVID-19 mandates in Arizona. Chinthavali et al (2022) examined changes in energy use patterns on weekdays and weekends before and after the COVID-19 pandemic. Raman and Peng (2021) used residential electricity consumption data to reveal a strong positive correlation between pandemic progress and residential electricity consumption in Singapore.…”

Analysis of the influence of the stay-at-home order on the electricity consumption in Chinese university dormitory buildings during the COVID-19 pandemic

“…To investigate changes in the energy-consumption behaviours of residents in detail, scholars have gradually shifted their attention from a macro perspective to a micro perspective. Existing studies have found that, during the COVID-19 period, the energy peak shifted and the load shape changed significantly [28] , [29] . For example, Chinthavali et al [28] found that the stay-at-home measures implemented during the COVID-19 pandemic led to an overall higher energy consumption in residential buildings, and most of the increased energy consumption occurred before the evening peak.…”

“…Existing studies have found that, during the COVID-19 period, the energy peak shifted and the load shape changed significantly [28] , [29] . For example, Chinthavali et al [28] found that the stay-at-home measures implemented during the COVID-19 pandemic led to an overall higher energy consumption in residential buildings, and most of the increased energy consumption occurred before the evening peak. Fan et al [29] found a decrease in energy consumption during conventional peak hours and an increase in energy consumption during potential new peak hours after the COVID-19 outbreak.…”

COVID-19 triggered residential behavioral changes and electricity consumption of detached houses in Japan

“…Rouleau and Gosselin surveyed 40 detached houses in Canada and found that electricity consumption (excluding hot water supply) increased by 17.5% year-on-year in the first month of the lockdown, from March 25th to April 25th, and did not increase during rest of the lockdown, indicating that the level of lockdown measures appeared only during strict periods [5] . Chinthavali et al investigated the device-level detailed power consumption of 62 smart homes in the United States, and compared the previous year in April and May 2020, to find out that from April and May of 2019 and 2020, the peak of the power load curve showed a shift from evening to daytime [6] . Edomah and Ndulue obtained power data from 259 power delivery points in a grid during the lockdown in Lagos, Nigeria, showing a 7.8% increase in the residential sector [7] .…”