One hour ahead price forecast of Ontario electricity market by using ANN

Abstract

In restructured electricity markets, forecasting electricity parameters are most essential tasks & basis for any decision making. Forecasting price in competitive electricity markets is difficult for consumers and producers in order to plan their operations and to manage their price risk, and it also plays a key role in the economic optimization of the deregulated power 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 one hour ahead price forecast of the electricity market. A new artificial neural network (ANN) has been used to compute the forecasted price in Ontario electricity market using MATLAB R13b. The data used in the forecasting are hourly historical data of the electricity load and price of Ontario electricity market. The simulation results have shown highly accurate one hour ahead forecasts with very small error in price forecasting.