Short-term wind speed forecasting in wind farm based on improved GMDH network

Based on traditional GMDH metwork and fuzzy logic theory,the wind speed forecasting in wind farm is analyzed and an improved GMDH neural network is proposed.This method introduces feedback loop to the traditional network and makes the neuron fuzzified.The low-level computational ability of GMDH and the high-level reasoning ability of fuzzy logic are combined in the improved network for predicting.Besides,exponential energy function is taken into network training as the objective error function,which improves the speed of network convergence.Comparing the forecasting result by the proposed method with those from BP neural network and traditional GMDH network,the accuracy of the improved method in short-term wind speed forecasting is proved effectively.