A novel algorithm of optimization model for wind speed forecasting

To improve the wind speed forecasting accuracy, a hybrid algorithm integrating time series analysis with divided difference filter (DDF) is proposed. First, by use of time series analysis theory, the non-stationary modeling for wind speed signals of wind farm is proceeded to obtain the model equation and the wind speed forecasted by the simplex time series model equation. Second, by means of the obtained model equation, the state equation and observational equation are deduced, and the wind speed is forecasted respectively by KF and DDF forecasting recurrence equation. Finally, the forecasting experiments for varying wind speed measured in a certain wind farm at JiShan is conducted to validate the proposed hybrid algorithm. Experimental results show that by using this hybrid algorithm the forecasting accuracy of wind speed can be improved and DDF is a effective in wind speed forecasting.