A comparison between SVM and LSSVM in mid-term electricity market clearing price forecasting

Abstract

The generating companies as well as the bulk sellers in a deregulated environment want to maximize their profits. For these entities, offering the appropriate amount of electricity at the right time with the right bidding price is of paramount importance. A comparison between support vector machine (SVM) and least squares support vector machine (LSSVM) in mid-term electricity MCP forecasting is presented in this paper. Mid-term electricity MCP forecasting has become essential for resources reallocation, maintenance scheduling, bilateral contracting, budgeting and planning purposes. Currently, there are many techniques available for short-term electricity market clearing price (MCP) forecasting, but very little has been done in the area of mid-term electricity MCP forecasting. PJM interconnection data have been utilized to illustrate the proposed model with numerical examples.