Probabilistic day-ahead system marginal price forecasting with ANN for the Turkish electricity market

OZGUNER E., TOR O. B., GÜVEN A. N.

TURKISH JOURNAL OF ELECTRICAL ENGINEERING AND COMPUTER SCIENCES, cilt.25, sa.6, ss.4923-4935, 2017 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 25 Sayı: 6
  • Basım Tarihi: 2017
  • Doi Numarası: 10.3906/elk-1612-206
  • Dergi Adı: TURKISH JOURNAL OF ELECTRICAL ENGINEERING AND COMPUTER SCIENCES
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, TR DİZİN (ULAKBİM)
  • Sayfa Sayıları: ss.4923-4935
  • Anahtar Kelimeler: Artificial neural networks, electricity market, price forecasting, system marginal price, ARTIFICIAL NEURAL-NETWORKS
  • Orta Doğu Teknik Üniversitesi Adresli: Evet

Özet

This study presents a system day-ahead hourly market clearing price forecasting tool for the day-ahead (DA) market and a system DA hourly marginal price forecasting tool for the real-time market of the Turkish electric market (TEM). These forecasting tools are developed based on artificial neural networks (ANNs). A series of historical price data of the TEM are utilized to model and optimize the ANN structure and to develop the ANN-based price forecasting tool. The methodology used to select the optimum ANN architecture provides the minimum daily mean absolute percentage error for both day-ahead market prices in the TEM. Performances of the proposed ANN model and the multiple linear regression model in forecasting the day-ahead hourly market clearing price are compared. The proposed ANN model is modified using volatility analysis and the Bienayme Chebyshev inequality in order to forecast system marginal prices probabilistically within a lower and an upper boundary.