Mid-term electricity market clearing price forecasting utilizing hybrid support vector machine and auto-regressive moving average with external input

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. Mid-term electricity MCP forecasting has become essential for resources reallocation, maintenance scheduling, bilateral contracting, budgeting and planning purposes. A hybrid mid-term electricity MCP forecasting model combining both support vector machine (SVM) and auto-regressive moving average with external input (ARMAX) modules is presented in this paper. The proposed hybrid model showed improved forecasting accuracy compared to forecasting models using a single SVM, a single least squares support vector machine (LSSVM) and hybrid LSSVM-ARMAX. PJM interconnection data have been utilized to illustrate the proposed model with numerical examples.