Wind Speed Forecast Based on Improved Elman Neural Network
Yang Hu · East China Electric Power · 2012
Wind speed forecast is of significance for the operation of grid-connected wind power generation systems.In order to improve the forecast precision,a method based on improved Elman neural network is proposed,where back propagation method is used to confirm the value of Feedback gainγ.The forecast model is established by using improved Elman neural network and BP neural network respectively,and applied to simulate and forecast the real historical wind speed data.The actual data of wind plant has verified the simulation results.