Wind power forecasting based on time series and SVM
Ran Li, KE Yong-qin, Xiaoqian Zhang, Fan Tang · Electric Power · 2012
The accurate wind power forecasting can relieve the adverse effects of wind power plants on power systems and enhance the competitive ability of wind power plants in electricity markets.A wind power forecasting method is proposed based on time series method and support vector machine(SVM).The mathematical model was built by time series method.The factors which have significant impacts on the wind power were selected as SVM's inputs.In order to improve forecasting accuracy,a method based on time series trace evolution was used to find SVM training samples which similar to the power at the forecasting point.The actual examples prove the improvement of wind power forecasting accuracy by using the time series-SVM method.