Abstract: Wind speed prediction is a key factor for wind farm planning and the operational planning of power grids; accurate forecasting of wind speed can minimize the scheduling errors and in turn increase the reliability of the electric power grid and reduce the power market ancillary service costs. Based on the mesoscale model WRF(Weather Research and Forcasting) for wind speed forecasting, combined with model prediction and statistical analysis using an intelligent optimization algorithm we have greatly improved the forecasting precision of wind speed, employing a new method to correct the model errors. In view of the climatic feature of Chinese wind farms, the wind speed prediction program in China has been enhanced.