An Overview of Electricity Consumption in Europe: Models for Prediction of the Electricity Usage for Heating and Cooling

dc.authorscopusid 55062130900
dc.authorscopusid 58068396000
dc.authorscopusid 7005981141
dc.authorscopusid 24823628300
dc.contributor.author Yukseltan,E.
dc.contributor.author Bilge, Ayşe Hümeyra
dc.contributor.author Aktunc,E.A.
dc.contributor.author Bilge,A.H.
dc.contributor.author Yucekaya,A.
dc.contributor.other Industrial Engineering
dc.date.accessioned 2024-06-23T21:39:22Z
dc.date.available 2024-06-23T21:39:22Z
dc.date.issued 2024
dc.department Kadir Has University en_US
dc.department-temp Yukseltan E., Department of Industrial Engineering, Kadir Has University, Istanbul, Turkey; Aktunc E.A., Department of Industrial Engineering, Kadir Has University, Istanbul, Turkey; Bilge A.H., Department of Industrial Engineering, Kadir Has University, Istanbul, Turkey; Yucekaya A., Department of Industrial Engineering, Kadir Has University, Istanbul, Turkey en_US
dc.description.abstract Although aggregate electricity consumption provides valuable information for market analysis, demand composition, including industrial, residential, illumination, and other uses, and special days, such as national or religious holidays and annual industrial shutdowns, differ for each country. This paper analyzes the hourly electricity consumption of European countries in the European Transmission System Operation for Electricity (ENTSO-E) grid from 2006 to 2018. We propose an outlier detection method to identify special days and a modulated Fourier Series Expansion model to determine the breakdown of industrial versus household consumption and heating versus cooling consumption. The proposed outlier detection method uses the time series for each hour and checks whether a day has more than a threshold number of hours with exceptional electricity consumption levels. The proposed demand prediction model has a 3% average error when electricity usage for heating is not dominant. It also allows country classification based on consumption patterns to efficiently manage regional or country-based electricity markets. © 2024, Econjournals. All rights reserved. en_US
dc.identifier.citationcount 0
dc.identifier.doi 10.32479/ijeep.15514
dc.identifier.endpage 111 en_US
dc.identifier.issn 2146-4553
dc.identifier.issue 2 en_US
dc.identifier.scopus 2-s2.0-85188273586
dc.identifier.scopusquality Q2
dc.identifier.startpage 96 en_US
dc.identifier.uri https://doi.org/10.32479/ijeep.15514
dc.identifier.uri https://hdl.handle.net/20.500.12469/5865
dc.identifier.volume 14 en_US
dc.language.iso en en_US
dc.publisher Econjournals en_US
dc.relation.ispartof International Journal of Energy Economics and Policy en_US
dc.relation.publicationcategory Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı en_US
dc.rights info:eu-repo/semantics/openAccess en_US
dc.scopus.citedbyCount 1
dc.subject Electricity Consumption Composition Analysis en_US
dc.subject Fourier Series Expansion en_US
dc.subject Special Days Detection en_US
dc.title An Overview of Electricity Consumption in Europe: Models for Prediction of the Electricity Usage for Heating and Cooling en_US
dc.type Article en_US
dspace.entity.type Publication
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