The invention discloses a wind power prediction correction method. The method includes the steps that 1, the total capacity of a selected wind power plant is obtained, and wind power prediction data and wind power actual measurement data of the whole field in a recent civil year of the wind power plant are obtained; 2, normalization processing is carried out on the wind power data, obtained from the step1, of the wind power plant by means of the total capacity of the wind power plant; 3, an input and output data set is formed according to the wind power prediction data and the wind power actual measurement data obtained after preprocessing in the step 2; 4, 2 / 3 of the input and output data set obtained in the step 3 is selected randomly to serve as a training set, and the remaining 1 / 3 serves as a testing set; 5, a kernel function and training parameters of the support vector machine are selected, training is carried out by means of the training set obtained from the step 4, and the testing set is used for testing; 6, a grid searching method is utilized to correct the parameters of the support vector machine, and an average absolute percentage error and a root-mean-square relative error of a correction result are utilized to serve as evaluation criteria to obtain a local optimum support vector machine training model, namely a local optimum wind power prediction correction model.