Short-Term Wind Power Forecasting Based on Lifting Wavelet, SVM and Error Forecasting

In order to improve the forecasting accuracy, a novel forecasting method using wavelet, support vector machine (SVM), and error forecasting technology is presented in this chapter. Firstly, it utilizes lifting wavelet method to decompose data to extract the data’s main characteristics. And then it establishes the SVM forecasting model and error forecasting model to realize the wind power load forecasting, relative error forecasting, and wind load data correcting. Finally, the actual data is adopted for simulation. The experimental results show that the method based on lifting wavelet transform, SVM, and error forecasting can improve the forecasting accuracy greatly. The test shows that the method used for the wind power load forecast is feasible and effective.