A Novel Wind Power Prediction Technique Based on Radial Basis Function Neural Network

To ensure the stability of power system and wind farm operation, it is important for power system dispatch in to forecast wind power outputs exactly. The historical data are acquired from an operating wind farm. According to a well-developed Radial Basis Function (RBF) neural network, a wind power predictive model is established, using the historical data such as wind speed, environmental temperature, wind power and so on. Comparing with the actual power output of the wind, the forecasting results show that the proposed method can predict a comparatively accurate and lead to stable results. The proposed power prediction method can be used to make more reasonable dispatching plans.