Short-term wind power forecast based on the Radial Basis Function neural network

Accurate wind power outputs forecasting plays an important role in power system dispatching,power system stability,and wind farm operation.Based on historical data from an operating wind farm such as wind speed,environmental temperature,wind power and so on,a short-term wind power forecasting model based on the well-developed Radial Basis Function(RBF) neural network is presented for hour-ahead forecasting,and the predicted error is about 12%.The forecasting results are compared with actual wind power outputs,and this shows that the presented method can lead to acceptable and stable forecasting results.