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

Mikail Purlu, Belgin Emre Turkay, Cenk Andic, Esra Aydin, Bilal Canol, Burak Kucukaslan

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Citation (Scopus)

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.

Original languageEnglish
Title of host publicationProceedings - 2022 IEEE 4th Global Power, Energy and Communication Conference, GPECOM 2022
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages517-522
Number of pages6
ISBN (Electronic)9781665469258
DOIs
Publication statusPublished - 2022
Event4th IEEE Global Power, Energy and Communication Conference, GPECOM 2022 - Cappadocia, Turkey
Duration: 14 Jun 202217 Jun 2022

Publication series

NameProceedings - 2022 IEEE 4th Global Power, Energy and Communication Conference, GPECOM 2022

Conference

Conference4th IEEE Global Power, Energy and Communication Conference, GPECOM 2022
Country/TerritoryTurkey
CityCappadocia
Period14/06/2217/06/22

Bibliographical note

Publisher Copyright:
© 2022 IEEE.

Keywords

  • deep learning
  • electricity market
  • forecasting
  • keras
  • market-clearing price

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