Wind speed optimisation method of numerical prediction for wind farm based on Kalman filter method - Hua, Shenbing; Wang, Shu; Jin, Shuanglong; Feng, Shuanglei; Wang, Bo (Journal of engineering (Stevenage, England), 2017)
In recent years, with the rapid increase of wind turbine install, the volatility and randomness of wind speed restrict the development of wind power industry. The uncertainty of wind speed forecast has the mainly impact on wind power prediction. The subject of this manuscript is to study the impact of wind speed prediction on wind power prediction. Firstly, The authors compare the observed wind speed in one wind farm with the forecasted wind speed using the 3 km × 3 km Weather Research and Forecast (WRF) model. Then the revised is conducted based on Kalman filter theory. In the revised process, the special and temporal impact of observed wind speed on target wind farm is considered and the reasonable predictive factor matrix is built to lower the systematic and random error. The wind speed data at heights of 10, 30, 50, and 70 m are processed using this revised approach, respectively. It turns out that the correlation coefficient between the wind speed forecast and observation has been raised from 0.48 and 0.47 (no revision) to 0.88 and 0.89 (after revision). The RMSE of wind speed has been decreasing from 3.98 and 4.20 to 1.72 and 1.60 m/s. The accuracy of wind speed forecast has been improved.