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The impact of COVID-19 measures on intraday electricity load curves in the European Union: A panel approach
This paper examines the impact of the intensity of government measures introduced to reduce the spread of COVID-19 on intraday electricity load curves in 23 European countries. The econometric panel model used covers the entire period from the virus outbreak in Europe up to the release of several va...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The Author(s). Published by Elsevier Ltd.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9484106/ http://dx.doi.org/10.1016/j.segan.2022.100930 |
Sumario: | This paper examines the impact of the intensity of government measures introduced to reduce the spread of COVID-19 on intraday electricity load curves in 23 European countries. The econometric panel model used covers the entire period from the virus outbreak in Europe up to the release of several vaccines; therefore, the estimation considers the introduction, partial lifting, and reintroduction of the interventions. Based on the results, the impacts of the different stringency measures were similar in the 23 analysed EU member states. More stringent interventions had different effects at different times of day: the morning and evening peaks were significantly affected, as was every hour of the day. The impacts were nonlinear, meaning that different measures mutually amplified each other’s impact and led to more substantial changes in electricity consumption and citizens’ lives. The morning and evening peaks are also found to have decreased, causing a flattening of the load curves. In line with this result, the partial effect of an increase in the stringency index depends on the type of day (weekday or weekend), hour of the day, and initial stringency level. Overall, the lockdown measures led to a decrease in hourly electricity consumption of between 1% and 9% on weekdays and between 1% and 13% on weekends. Total daily consumption decreased by up to 9%. Understanding how hourly electricity demand reacts to different stringency measures provides valuable information in operation scheduling and capacity planning. More accurate demand forecasts can support trading decisions and help prevent extreme market mismatches. |
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