In order to improve the precision of forecasting wind power

a short-term wind power forecasting method based on Elman neural network and measured wind speed power data is proposed. The wind power curve of wind turbine can be fitted with the measured data of wind speed and power

which can be applied to short-term wind power forecast. The forecasting method based on Elman neural network is built

and GA is applied to optimize the key parameters of Elman neural network. Finally

the wind power prediction is carried out combining the forecasting wind speed and the fitting wind speed power curve. The proposed model is validated by applying this modeling process to the measured data.