Power distribution load forecasting using artificial neural networks

dc.contributor.authorEminoglu U.
dc.contributor.authorYalcinoz T.
dc.contributor.authorHerdem S.
dc.date.accessioned2019-08-01T13:38:39Z
dc.date.available2019-08-01T13:38:39Z
dc.date.issued2003
dc.departmentNiğde ÖHÜ
dc.descriptionMinistry of Macedonia;Aristotle University of Thessaloniki, Thessaloniki, Greece;Insitiute of Electrical Engineers, IEE;Institute of Electrical and Electronic Engineers, IEEE;Technical Chamber of Greece, TCG
dc.descriptionUPEC 2003, 38th International Universities' Power Engineering Conference -- 1 September 2003 through 3 September 2003 -- Thessaloniki -- 62394
dc.description.abstractThis paper presents a load forecasting method applied to electricity consumption in Nigde region. The load forecasting method is based on the Multi-Layered Perceptron (MLP) neural network (NN). Three MLP structures are compared for obtaining the best forecasting results. Then, the results of the best MLP structure are compared with the moving average method. The suitability of the proposed method is illustrated through an application to real load shapes form Turkish Electricity Distribution Corporation (TEDAS) in Nigde. The data represents the monthly electricity consumption in Nigde, Turkey. The proposed method is applied to the data from January 1991 to December 2001.
dc.identifier.endpage493
dc.identifier.scopus2-s2.0-1442278651
dc.identifier.scopusqualityN/A
dc.identifier.startpage490
dc.identifier.urihttps://hdl.handle.net/11480/1326
dc.identifier.volume38
dc.indekslendigikaynakScopus
dc.institutionauthor[0-Belirlenecek]
dc.language.isoen
dc.relation.ispartofProceedings of the Universities Power Engineering Conference
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.titlePower distribution load forecasting using artificial neural networks
dc.typeConference Object

Dosyalar