A Neural Network Based Approach for the Short-term Forecasting of Electricity Market Price

In this study, an improved cascaded neural network is utilized to determine a Marketing Clearing Price (MCP) for energy in the wholesale market Russian. Research on MCP prediction has attracted lot of attention recent years. This study recommends unique approach based customized back propagation algorithm retraining, testing, and testing pricing over many months. research contributed development methodology. MATLAB R 2015a (8.1.0.602) software simulation will be used carry out suggested action. As part strategy framework, we provide that can reduce load time while also reducing MAPE, MSE, RMSE. The proposed method's end goal forecast clearing price. MAPE our technique smallest all have been reported literature. calculated 1.9%. method may number different types electric boards clean, stable electricity