Mid-term electricity market clearing price forecasting using multiple support vector machine

In a deregulated electricity market, offering the appropriate amount of electricity at the right time with the right bidding price is of paramount importance. Mid-term electricity market clearing price (MCP) forecasting has become essential for resources reallocation, maintenance scheduling, bilateral contracting, budgeting and planning purposes. Although there are many techniques available for short-term electricity MCP forecasting, very little has been done in the area of mid-term electricity MCP forecasting. In this paper, a mid-term electricity MCP forecasting model utilizing multiple support vector machine (SVM) is presented. Two modules: data classification and price forecasting modules are designed to first pre-process the input data into corresponding price zones and then forecast the electricity prices. The proposed model showed improved forecasting accuracy on both peak prices and overall system compared to the forecasting model using single SVM. PJM interconnection data are used to test the proposed model.