Electricity Price Forecasting for PJM Day-Ahead Market

In competitive electricity markets, price forecasting is becoming increasingly relevant to power producers and consumers. Price forecasts provide crucial information for power producers and consumers to develop bidding strategies in order to maximize benefit. This paper provides a method for predicting day-ahead electricity prices in the PJM market using artificial neural network (ANN) computing technique, which is based on similar days approach. Publicly available data acquired from the PJM electricity market were used for training and testing the ANN. Comparison of forecasting performance with the proposed ANN is presented. The results obtained through the simulation show that the proposed algorithm is efficient, accurate and produces better results