Data-Driven Analysis: Examining the Impact of COVID-19 from the Perspective of Residential and Non-Residential Electricity Consumption

Abstract

Due to the pandemic’s widespread effects on daily life in the past few years, evaluating and analyzing the impact of COVID-19 on large cities in China accurately and timely has become increasingly significant. The existing research lacks studies on the electricity consumption of residents and non-residents during the pandemic. So based on the four-year electricity consumption data of a large city in China, this paper examines COVID-19’s impact from the perspective of residential and non-residential electricity consumption through the COVID-19-Power framework and its extended version that predicts electricity consumption in 2020 without the outbreak of COVID-19 for comparison with the actual values. For residential electricity consumption, through comparative analysis of different administrative districts on geographic location and historical electricity consumption habits, the impact of the pandemic on residential electricity consumption is found to be relatively small. For non-residential electricity consumption, we infer that power-related factors including real estate development and investment, etc. contribute to perception of the special impacts of the pandemic. We conduct predictive analysis of non-residential electricity consumption for different administrative districts by geographic location, different electricity consumption categories. We verify the significant negative impact of the pandemic on the real estate sector by the analysis of electricity consumption across different sectors. Through these research results, details about the impact of the pandemic on people’s lives and electrical load in China’s large cities can be captured by power enterprises to adjust power supply strategies more effectively and pertinently.

Keywords

• covid-19
• social computing
• electricity consumption analysis
• forecasting models