The embodiments of the invention provide a wind power generation power determining method and device. The method includes the following steps that: a Gauss regression training model is constructed, and the hyper-parameters of the Gauss regression training model are determined; the hyper-parameters of the Gauss regression training model are screened by adopting a memetic algorithm, and screened-out hyper-parameters are utilized to construct a new Gauss regression training regression model; the new Gauss regression training regression model is utilized to perform computation processing on a first sample data set, so that wind speed data at a wind power generation power prediction time point is obtained; and the new Gauss regression training regression model is utilized to perform computation on the wind speed data at the wind power generation power prediction time point and a second sample data set, so as to obtain predictive wind electricity power. According to the method provided by the technical schemes of the invention, the memetic algorithm is adopt to screen the hyper-parameters of the Gauss regression training model; the screened-out hyper-parameters are utilized to construct the new Gauss regression training regression model; the new Gauss regression training regression model is utilized to predict the wind electricity power; and therefore, the efficiency of the prediction of the wind electricity power can be improved, and the accuracy of prediction results can be improved.