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The electricity demand forecasting in the UK under the impact of the COVID-19 pandemic

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Abstract

The COVID-19 pandemic has caused fluctuations in electricity demand, altering people's lifestyles and electricity usage patterns, thereby affecting the accuracy of demand predictions. However, existing studies on electricity forecasting have not adequately considered the incorporation of COVID-19-related features and the analysis of electricity usage characteristics across different regions of the UK. Therefore, this paper, based on data of the UK's national electricity demand, conducts an analysis around the scenario of a large-scale health emergency in society. We explore the changing patterns and regional characteristics of electricity consumption during the COVID-19 pandemic, comparing the forecast results before and during the pandemic to illustrate its impact on the UK's electricity demand. By introducing COVID-19-related features into the models, we compare the forecast results before and after their inclusion. The results indicate that the COVID-19 pandemic has had a certain impact on the electricity prediction in the UK, leading to a 22.8% decrease in prediction accuracy. However, the models' correlation improved with the inclusion of COVID-19-related features, resulting in a 13.2% enhancement in prediction accuracy compared to the previous models. Additionally, the study summarizes other factors influencing electricity demand, such as power imports/exports and clean energy usage, as considerations for electricity distribution planning. This contributes to improving the accuracy of predicting the UK's electricity demand during COVID-19 pandemic, enabling the government to adjust power dispatching plans reasonably based on relevant factors, achieving rational distribution and efficient scheduling of power resources.

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Data availability

The electricity demand dataset for the United Kingdom is sourced from the National Grid Electricity System Operator (ESO), which is updated every two hours and can be used for time series forecasting. The website for accessing this dataset is the ESO Data Portal: Home | National Grid Electricity System Operator (nationalgrideso.com). The pandemic-related data is obtained from the UK government website, specifically from the England Summary | Coronavirus (COVID-19) in the UK (data.gov.uk). The data related to electricity production quantity and production types in the UK is acquired from Kaggle. The website for accessing this dataset is Hourly Electricity Consumption and Production | Kaggle.

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Acknowledgements

The authors wish to express their sincere thanks to the Beijing University of Technology for its valuable support and assistance to the current work.

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Authors and Affiliations

  1. Faculty of Information Technology, Beijing University of Technology, Beijing, China

    Youliang Dong, Changshun Yan & Yong Shao

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  1. Youliang Dong
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  2. Changshun Yan
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Contributions

Conceptualization, Y.D.; methodology, Y.D.; validation, Y.D; formal analysis, Y.D.; investigation, Y.D.; resources, Y.D.; data curation, Y.D.; writing—original draft preparation, Y.D.; writing—review and editing, C.Y.; visualization, Y.D.; supervision, C.Y.; project administration, Y.S.; All authors have read and agreed to the published version of the manuscript.

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Correspondence to Yong Shao.

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Dong, Y., Yan, C. & Shao, Y. The electricity demand forecasting in the UK under the impact of the COVID-19 pandemic. Electr Eng (2024). https://doi.org/10.1007/s00202-023-02233-3

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