In order to predict the wind power generation capacity accurately,an optimal combination forecasting technique combining Artificial Neural Network(ANN)model with gray model(GM)is proposed in this paper.It can reduce the prediction error when it is applied in wind power generation capacity forecasting.Taking the factors affecting the wind power generation capacity into account are wind velocity,wind direction,temperature,and the wind power generation amount in previous years and so on.Combining with the advantages of both ANN and GM model,using the optimal combination forecasting technique can improve the prediction accuracy and reduce the prediction error.The forecasting results from a case provide the forecasting error of optimal combination techniques is less than a single gray prediction or neural network prediction.It has research value for the wind power generation foresting in the future.