An analysis of short-term price forecasting of power market by using ANN

Abstract

In deregulated power markets, forecasting electricity parameters are most essential tasks & basis for any decision making. Price forecasting in competitive electricity markets is critical for consumers and producers in planning their operations and managing their price risk, and it also plays a key role in the economic optimization of the electric energy industry. Accurate, short-term price forecasting is an essential instrument which provides crucial information for power producers and consumers to develop accurate bidding strategies in order to maximize their profit. In this paper artificial intelligence (AI) has been applied in short-term price forecasting that is, the day-ahead hourly forecast of the electricity market price. A new artificial neural network (ANN) has been used to compute the forecasted price in ISO New England market using MATLAB R13. The data used in the forecasting are hourly historical data of the temperature, electricity load and natural gas price of ISO New England market. The simulation results have shown highly accurate day-ahead forecasts with very small error in price forecasting.