In determination of electric energy price, most price information coming from bilateral contracts is effective, but the importance of the spot market (pool market) price cannot be ignored. Forecasting the spot market price is very crucial, especially for companies actively participating in the spot market and giving purchase and sale bids. An artificial neural network is a way frequently used for price forecasting research. In this study, simulation studies about price modeling via artificial neural networks and proper artificial neural network configurations are examined. After selection of different network topologies and parameters, attempts are made to observe network performance by error rates and find the best suitable configuration. Moreover, a time series model is made and it is compared with the artificial neural network's error performance.
Artificial neural networks, Turkish electricity market, day-ahead price, time series
KÖLMEK, MEHMET ALİ and NAVRUZ, İSA
"Forecasting the day-ahead price in electricity balancing and settlement market of Turkey by using artificial neural networks,"
Turkish Journal of Electrical Engineering and Computer Sciences: Vol. 23:
3, Article 16.
Available at: https://journals.tubitak.gov.tr/elektrik/vol23/iss3/16