Wind power prediction gale data enhancement method considering extreme gale weather

The invention discloses a gale data enhancement method considering extreme gale weather. The method comprises the following steps: acquiring historical actually measured wind speed and power data, and generating original wind speed-power data samples; performing local abnormal point identification on the original wind speed-power data samples according to the wind speed data, and removing outlier samples to obtain gale data initial samples; clustering the gale data initial samples by using an F-DBSCAN clustering algorithm to obtain core point samples of each cluster; calculating a cluster density according to core points of clusters, and synthesizing new gale data samples by using an oversampling algorithm based on the core points and the cluster density of the clusters where the core points are located; expanding the original wind speed-power data samples by using the synthesized new gale data samples to serve as training samples of a wind power prediction model. The invention can be used for effectively sup