Yayın: Market-Clearing Price Forecasting Using Keras in Turkish Day-Ahead Electricity Market
| dc.contributor.author | Kucukaslan, Burak | |
| dc.contributor.author | Pürlü, Mikail | |
| dc.contributor.author | Turkay, Belgin Emre | |
| dc.contributor.author | Andiç, Cenk | |
| dc.contributor.author | Aydın, Esra | |
| dc.contributor.author | Canol, Bi̇lal | |
| dc.date.accessioned | 2026-01-26T02:18:13Z | |
| dc.date.issued | 2022-06-14 | |
| dc.description.abstract | The 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.uri | https://doi.org/10.1109/gpecom55404.2022.9815603 | |
| dc.description.uri | https://avesis.kocaeli.edu.tr/publication/details/545651c6-f667-4904-9e0a-216b6fd6c64d/oai | |
| dc.identifier.doi | 10.1109/gpecom55404.2022.9815603 | |
| dc.identifier.endpage | 522 | |
| dc.identifier.openaire | doi_dedup___::c4568249034b1ae1120fd94336267c43 | |
| dc.identifier.orcid | 0000-0002-1194-3931 | |
| dc.identifier.orcid | 0000-0003-1123-899x | |
| dc.identifier.orcid | 0000-0001-5618-9787 | |
| dc.identifier.startpage | 517 | |
| dc.identifier.uri | https://hdl.handle.net/11527/57248 | |
| dc.publisher | IEEE | |
| dc.relation.ispartof | 2022 4th Global Power, Energy and Communication Conference (GPECOM) | |
| dc.rights | CLOSED | |
| dc.title | Market-Clearing Price Forecasting Using Keras in Turkish Day-Ahead Electricity Market | |
| dc.type | Article | |
| dspace.entity.type | Publication |