Probabilistic day-ahead system marginal price forecasting with ANN for the Turkish electricity market
Turkish Journal of Electrical Engineering and Computer Sciences, cilt.25, sa.6, ss.4923-4935, 2017 (SCI-Expanded, Scopus, TRDizin)
- 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
- TED Üniversitesi Adresli: Hayır
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.