A Comparative Study of Ensemble Support Vector Regression Methods for Short-term Load Forecasting

The accuracy of short-term load forecasting has a vital function in the safety, stability and economic operation of the power grid. Support vector regression (SVR) have achieved good results in short-term load forecasting (STLF). In order to further enhance the performance of STLF, diverse ensemble SVR methods have been put forward in the literature. This paper is aim to compare the performance of several ensemble SVR methods with two data sets. It shows that these methods outperform SVR model. The simpler ensemble SVR methods performs better than sophisticated ones.