Market Clearing Price prediction using ANN in Indian Electricity Markets

The electricity industry is evolving into a distributed and competitive in which market forces drive the price of the electricity and reduce the net cost through increased competition. Forecasting system Market Clearing Volume (MCV) and Market Clearing Price (MCP) has become even more important in order to make optimal bidding and profit maximization. This research work presents Artificial Neural Network (ANN) based forecasting model to estimate future Market Clearing Prices in Indian Electricity Markets. The model is verified by comparing the results of ANN with Regression model. The performance of the ANN and Regression models are evaluated on the data available on Indian Energy Exchange (IEX) site for the period January 2013 to March 2014. This paper forecasts the daily MCPs for the months of January, February and March for the year 2014. It is found that the forecasted MCPs in the Indian Electricity Markets have the less agreement with the ANN model and appropriate agreement with the Regression model. Consequently, it confirms about the unreliability and highly sensitiveness of ANN with respect to regression model. The Mean Absolute Percentage Errors (MAPEs) are evaluated to check the robustness of the two proposed methodologies.