Abstract
The arithmetic of wind power prediction plays an important part in the development of wind power prediction. In this paper, based on the principles of support vector machine (SVM) and wavelet, the wavelet SVM model for short term wind power prediction is built up along with analyzing the characteristics of power curves of wind turbine generator systems. The operation data from a wind farm in North China are used to test the proposed model, the mean relative error of wavelet SVM model is 6.05% less than that of traditional RBF SVM model. For the time frame of one hour ahead, the average error of optimal wind turbine prediction method is 12.07%.
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