Energy price forecasting in the Ontario competitive power system market

This paper introduces a method for forecasting energy prices using artificial intelligence methods, such as neural networks and fuzzy logic, and a combination of the two. The new approach is compared with some of the exiting methods. Various factors affecting the market clearing price are investigated. Results for the Ontario electricity market are presented. Index Terms--Artificial intelligence, energy price forecasting, fuzzy logic, neural networks, open access market.