A medium term wind power generation capacity prediction method based on Grey theory and neural network is proposed.The purpose is to use the exponential growth law of the grey theory model and the nonlinear learning ability of the chaotic neural network model to realize the wind power generation capacity prediction of the wind farm,and provide the power generation basis for the power grid dispatching.First,the grey metabolism prediction model is designed,and the monthly power generation curve predicted by the grey metabolism model is simulated and compared with the actual power generation curve.Secondly,the prediction results of grey metabolism model and chaotic neural network model are optimized by the linear weighting method,and the combined model is simulated and compared with the actual curve.Finally,the conclusion that the prediction error of the combined model prediction value is the smallest is obtained,which can effectively improve the accuracy of the mid-term prediction of wind farm power generation capacity.
