A wind power prediction method based on sequential time clustering support vector machine（SVM） is proposed. Each year is divided into several continuous time series by clustering twice， with one catching the daily similarity to build model by SVM and the proposed model is used to predict statistics of time series corresponding to other years. The SVM model can avoid converging into a local optimal zone compared to neural networks method. Experiments on a wind farm show the effectiveness of the proposed method.