Predicting Power Deviation in the Turkish Power Market Based on Adaptive Factor Impacts

Denizhan Guven*, Avni Ozozen, Gülgün Kayakutlu, M. Ozgur Kayalica

*Corresponding author for this work

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

2 Citations (Scopus)

Abstract

Energy market models are generally focused on energy balancing using the optimum energy mix. In countries where the energy markets are not fully liberalised, the State Regulators reflect any cost of being off-balance on the utility companies and this affects the consumers as well. The right short term prediction of the market trends is beneficial both to optimise the physical energy flow and commercial revenue balance for suppliers and utility companies. This study is aimed to predict the sign trends in the power market by selecting the influencing factors adaptive to the conditions of the day ahead, 10 h, 5 h, 2 h and 1 h before the electricity balance is active. There are numerous factors consisting of weather conditions, resource costs, operation costs, renewable energy conditions, regulations, etc. with a considerable impact on the predictions. The contribution of this paper is to choose the factors with the highest impacts using the Genetic Algorithm (GA) with Akaike Information Criteria (AIC), which are then used as input of a Recursive Neural Network (RNN) model for forecasting the deviation trends. The proposed hybrid method does not only reduce the prediction errors but also avoid dependency on expert knowledge. Hence this paper will allow both the market regulator and the suppliers to take precautions based on a confident prediction.

Original languageEnglish
Title of host publicationArtificial Intelligence for Knowledge Management - 8th IFIP WG 12.6 International Workshop, AI4KM 2021, Held at IJCAI 2020, Revised Selected Papers
EditorsEunika Mercier-Laurent, Mieczyslaw Lech Owoc, M. Özgür Kayalica
PublisherSpringer Science and Business Media Deutschland GmbH
Pages213-234
Number of pages22
ISBN (Print)9783030808464
DOIs
Publication statusPublished - 2021
Event8th IFIP WG 12.6 International Workshop on Artificial Intelligence for Knowledge Management, AI4KM 2021 held in conjunction with International Joint Conference on Artificial Intelligence, IJCAI 2020 - Virtual, Online
Duration: 7 Jan 20218 Jan 2021

Publication series

NameIFIP Advances in Information and Communication Technology
Volume614
ISSN (Print)1868-4238
ISSN (Electronic)1868-422X

Conference

Conference8th IFIP WG 12.6 International Workshop on Artificial Intelligence for Knowledge Management, AI4KM 2021 held in conjunction with International Joint Conference on Artificial Intelligence, IJCAI 2020
CityVirtual, Online
Period7/01/218/01/21

Bibliographical note

Publisher Copyright:
© 2021, IFIP International Federation for Information Processing.

Keywords

  • Adaptive prediction
  • Auxiliary power market modeling
  • Energy market balancing
  • Genetic algorithm and recursive neural networks
  • Turkish power market

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