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Short Term Electricity Price Forecasting Using ANN and Fuzzy Logic under Deregulated Environment

Aarti Gupta, Pankaj Chawla, Sparsh Chawla

Price forecasts are crucial information for the power producers and consumers when planning the bidding strategies in order to have maximum benefits. The choice of forecasting model becomes an important tool how to improve the price forecasting accuracy. In this paper a combination methodology of ANN and fuzzy Inference System (FIS) is used to forecast the short term electricity prices. The Indian electricity market data was used to test the system. These methods are examined on the Indian Electricity Market in year 2012 Comparison of the forecasting performance with ANN and FIS-ANN method is presented. The results indicate that FIS-ANN method improves the price forecasting accuracy. The developed system show considerable improvement in the performance regarding price data, achieving MAPE is less than 3% with FIS-ANN as compared with ANN.