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Electricity Price Modelling for Turkey

In: Operations Research Proceedings 2011

Author

Listed:
  • Miray Hanım Yıldırım

    (Middle East Technical Univ.
    Çankaya Univ.)

  • Ayşe Özmen

    (Middle East Technical Univ.)

  • Özlem Türker Bayrak

    (Çankaya Univ.)

  • Gerhard Wilhelm Weber

    (Middle East Technical Univ.)

Abstract

This paper presents customized models to predict next-day’s electricity price in short-term periods for Turkey’s electricity market. Turkey’s electricity market is evolving from a centralized approach to a competitive market. Fluctuations in the electricity consumption show that there are three periods; day, peak, and night. The approach proposed here is based on robust and continuous optimization techniques, which ensures achieving the optimum electricity price to minimize error in periodic price prediction. Commonly, next-day’s electricity prices are forecasted by using time series models, specifically dynamic regression model. Therefore electricity price prediction performance was compared with dynamic regression. Numerical results show that CMARS and RCMARS predicts the prices with 30% less error compared to dynamic regression.

Suggested Citation

  • Miray Hanım Yıldırım & Ayşe Özmen & Özlem Türker Bayrak & Gerhard Wilhelm Weber, 2012. "Electricity Price Modelling for Turkey," Operations Research Proceedings, in: Diethard Klatte & Hans-Jakob Lüthi & Karl Schmedders (ed.), Operations Research Proceedings 2011, edition 127, pages 39-44, Springer.
  • Handle: RePEc:spr:oprchp:978-3-642-29210-1_7
    DOI: 10.1007/978-3-642-29210-1_7
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    Cited by:

    1. Avci-Surucu, Ezgi & Aydogan, A. Kursat & Akgul, Doganbey, 2016. "Bidding structure, market efficiency and persistence in a multi-time tariff setting," Energy Economics, Elsevier, vol. 54(C), pages 77-87.
    2. Matinfard, Sahar & Yaghoubi, Saeed & Kharaji Manouchehrabadi, Maedeh, 2024. "A coordinated approach for a three-echelon solar-wind energy supply with government intervention," Utilities Policy, Elsevier, vol. 86(C).
    3. Soheyl Khalilpourazari & Saman Khalilpourazary & Aybike Özyüksel Çiftçioğlu & Gerhard-Wilhelm Weber, 2021. "Designing energy-efficient high-precision multi-pass turning processes via robust optimization and artificial intelligence," Journal of Intelligent Manufacturing, Springer, vol. 32(6), pages 1621-1647, August.

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