Quantitative Assessment of the Impact of Extreme Events on Electricity Consumption

Dan Xiong, Yiming Yan (), Mengjiao Qin, Sensen Wu and Renyi Liu
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Dan Xiong: School of Earth Sciences, Zhejiang University, 866 Yuhangtang Road, Hangzhou 310027, China
Yiming Yan: School of Earth Sciences, Zhejiang University, 866 Yuhangtang Road, Hangzhou 310027, China
Mengjiao Qin: School of Earth Sciences, Zhejiang University, 866 Yuhangtang Road, Hangzhou 310027, China
Sensen Wu: School of Earth Sciences, Zhejiang University, 866 Yuhangtang Road, Hangzhou 310027, China
Renyi Liu: School of Earth Sciences, Zhejiang University, 866 Yuhangtang Road, Hangzhou 310027, China

Energies, 2023, vol. 17, issue 1, 1-18

Abstract: Global energy consumption is growing rapidly, with the frequency and intensity of extreme events constantly increasing, posing a long-term threat to power supply and consumption. Therefore, analyzing the spatiotemporal characteristics of electricity consumption and quantitatively assessing the impact of extreme events on electricity consumption are of great significance. Based on fine-grained electricity consumption data from Europe for the years 2019–2022, this paper employs a data mining perspective and four methods including Z-score, Isolation Forest, Local Outlier Factor, and Autoencoder to detect abnormal electricity consumption during extreme events. Additionally, it combines indicators such as elastic loss, vulnerability, and duration to measure the impact of extreme events on electricity consumption. It is found that low temperatures could lead to abrupt changes in electricity consumption, with Northern Europe being more significantly affected by low temperatures. The COVID-19 pandemic had the most significant impact on electricity consumption in Europe, with the middle part of Europe being the hardest hit during the first wave of the pandemic. Electricity anomalies during the pandemic period were related to national pandemic control policies and exhibited some lag. High temperatures persisted for a longer duration in the middle part of Europe.

Keywords: electricity consumption; extreme events; Europe; anomaly detection (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2023
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