Next day price forecasting for electricity market

This paper proposes new approach to reduce the prediction error at occurrence time of the peak price, and aims to enhance the accuracy of the next day price forecasting. In the proposed method, the weekly variation data is used for input factors of the ANN at occurrence time of the peak price in order to catch the price variation. Moreover, learning data for the ANN is selected by rough sets theory at occurrence time of the peak price. From the simulation results, it is observed that the proposed method provides a more accurate and effective forecasting, which helpful for suitable bidding strategy and risk management tool for market participants in a deregulated electricity market.