Mid-term electricity market clearing price forecasting: A multiple SVM approach

In a deregulated electric market, offering the appropriate amount of electricity at the right time with the right bidding price is of paramount importance for utility companies maximizing their profits. Mid-term electricity market clearing price (MCP) forecasting has become essential for resources reallocation, maintenance scheduling, bilateral contracting, budgeting and planning. 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. A multiple support vector machine (SVM) based mid-term electricity MCP forecasting model is proposed in this paper. Data classification and price forecasting modules are designed to first pre-process the input data into corresponding price zones, and then forecast the electricity price. The proposed model showed improved forecasting accuracy on both peak prices and overall system compared with the forecasting model using a single SVM. PJM interconnection data are used to test the proposed model.