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Market-Clearing Price Forecasting Using Keras in Turkish Day-Ahead Electricity Market

dc.contributor.authorKucukaslan, Burak
dc.contributor.authorPürlü, Mikail
dc.contributor.authorTurkay, Belgin Emre
dc.contributor.authorAndiç, Cenk
dc.contributor.authorAydın, Esra
dc.contributor.authorCanol, Bi̇lal
dc.contributor.departmentElektrik Mühendisliği Bölümü
dc.contributor.departmentElektrik Mühendisliği Bölümü
dc.contributor.departmentElektrik Mühendisliği Bölümü
dc.contributor.ituauthorAndiç, Cenk
dc.contributor.ituauthorAydın, Esra
dc.contributor.ituauthorTürkay, Belgin
dc.date.accessioned2026-01-26T02:18:13Z
dc.date.issued2022-06-14
dc.description.abstractThe market-clearing price determined in the electricity market is of great importance for the market players trading in electricity. The market-clearing price constitutes the core of the buying and selling transactions in the electricity market. Knowing what the price of the product, service or commodity to be bought and / or sold would be, provides a great competitive advantage to the relevant party over the person or organization carrying out the relevant commercial activity. It is important to successfully predict the market-clearing price in the market in order to set strategy and game plan and implement risk management. For this purpose, in this study, a model using only publicly available input data on Keras, a deep learning library, is used to predict hourly market-clearing price in Turkish Day-Ahead Electricity Market. Despite the high economic and financial uncertainty and price fluctuations in 2021, the proposed model showed a high performance with a MAPE value of 2.5% and it is clear that the model is successful and applicable in real market conditions.
dc.description.urihttps://doi.org/10.1109/gpecom55404.2022.9815603
dc.description.urihttps://avesis.kocaeli.edu.tr/publication/details/545651c6-f667-4904-9e0a-216b6fd6c64d/oai
dc.identifier.doi10.1109/gpecom55404.2022.9815603
dc.identifier.endpage522
dc.identifier.openairedoi_dedup___::c4568249034b1ae1120fd94336267c43
dc.identifier.orcid0000-0002-1194-3931
dc.identifier.orcid0000-0003-1123-899x
dc.identifier.orcid0000-0001-5618-9787
dc.identifier.startpage517
dc.identifier.urihttps://hdl.handle.net/11527/57248
dc.publisherIEEE
dc.relation.ispartof2022 4th Global Power, Energy and Communication Conference (GPECOM)
dc.rightsCLOSED
dc.titleMarket-Clearing Price Forecasting Using Keras in Turkish Day-Ahead Electricity Market
dc.typeArticle
dspace.entity.typePublication
person.identifier.orcid0000-0001-9659-359X
person.identifier.orcid0000-0003-0922-8936

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