A self-adaptive model for wind power prediction

This paper proposes a new approach for wind power forecasting based on sliding window weighted recursive least squares for the defect of wind power prediction in the traditional prediction method. In this method, the historical data is weighted and the perturbation caused by the historical data is ruled out, which focuses on the current data on the result of prediction. This make the model has the adaptability to the change of the environment data. Final, the simulation is carried out for the real historical data from a wind farm in Liaoning. The simulation results demonstrate the effectiveness of the proposed method.