Application of the cascaded correlation network to forecast the marginal clearing price in power market

In the power market, the bidding price of the supplier reflects the cost and the demand-supply of electricity and can decide the amount of the generation of the supplier. For making the bidding price, the forecasted marginal clearing price (MCP) is an important index and has a significant meaning to the supplier. In this paper the cascaded correlation network is applied to forecast the price and the results are compared with a three-layer BP network. The merit of using cascaded correlation network is to avoid the estimation of the structure of the network. Meanwhile a method of adding special data into the training set is used to improve the accuracy of forecasting. The example of forecasting MCP of the next 24 hours of New-England ISO data shows this method's promising.