Combination Method of Mid-Long Term Load Forecasting Based on Support Vector Machine

Affected by many factors,the mid-long term load forecasting will not be satisfied if only a single method is adopted.Combination forecasting model can be used to solve the problem,but it is limited by empirical risk minimization(ERM) principle.In the paper,method based on the least square support vector machine(LS-SVM) is proposed for mid-long term load forecasting.In the model,instead of traditional ERM the principle of structure risk minimization(SRM) is used to fully mine the information of original data and the single method.The LS-SVM combination model which adopts polynomial kernel function is constructed to train the samples obtained from single methods.The simulation results show that the average error is only 1.719% and the proposed method is feasible and effective.