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

摘要

In this chapter, wind power short-term load forecasting method was presented based on the lifting wavelet transform, SVM, and error forecasting. The lifting wavelet was utilized to find out the characteristics of signals. The SVM was adopted to classify the input signals and forecast them well. And the error forecasting can improve the forecasting accuracy. In addition, the error forecasting is a very effective forecasting method which can greatly improve the forecasting accuracy, especially the accuracy of the peaks and valleys. Through analyzing the results of simulation, it can be seen that the combination of the three methods can get a satisfactory wind power short-term forecasting result.