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Power Load Forecast System for Turkish Electric Market

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dc.contributor.authorBozkurt, O. Ozgur
dc.contributor.authorTaysi, Z. Cihan
dc.contributor.authorBiricik, Goksel
dc.date.accessioned2026-06-27T13:54:00Z
dc.date.issued2015
dc.description.abstractForecasting the electric load demand in advance is very important in deregulated market conditions to give proper production, purchase, maintenance and investment decisions. Correct price forecasts also depend on accurate load prediction. In this study, effects of calendar, historical price and load data on short-term load forecast for Turkish Deregulated Electricity market are tested using feed forward neural networks. The impact of each data on forecast performance is evaluated and best performance is obtained using a combination of historical and predicted load, calendar information and historical price informationen
dc.identifier.endpage572
dc.identifier.isbn978-1-4673-7386-9
dc.identifier.issn2165-0608
dc.identifier.startpage569
dc.identifier.urihttps://hdl.handle.net/20.500.14981/55453
dc.identifier.wos000380500900121
dc.language.isotur
dc.publisherIEEE
dc.relation.conference23nd Signal Processing and Communications Applications Conference (SIU)
dc.relation.ispartof2015 23RD SIGNAL PROCESSING AND COMMUNICATIONS APPLICATIONS CONFERENCE (SIU)
dc.subjectelectric market
dc.subjectload prediction
dc.subjectartificial neural networks
dc.subjectMODEL
dc.subjectEngineering
dc.subjectTelecommunications
dc.titlePower Load Forecast System for Turkish Electric Market
dc.typeProceedings Paper
dspace.entity.typePublication
local.import.sourceWOS

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