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 | Aktunc,E.A. | |
dc.contributor.author | Bilge,A.H. | |
dc.contributor.author | Yucekaya,A. | |
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.citation | 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.institutionauthor | Bilge, Ayşe Hümeyra | |
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.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 | |
relation.isAuthorOfPublication | 1b50a6b2-7290-44da-b8d5-f048fea8b315 | |
relation.isAuthorOfPublication.latestForDiscovery | 1b50a6b2-7290-44da-b8d5-f048fea8b315 |