To solve the problems of variable redundancy and model complexity in the prediction model based on the dynamic neural network

an ultra-short-term wind power prediction method is proposed by combining the neural network(NN)and the mean impact value(MIV). In this method

the external and internal contribution rates of the input variables to the output variables(wind power prediction value)are taken into account

and the input variable with the largest contribution to the output variables is selected. Then an optimized NN prediction model for ultra-short-term wind power prediction is developed. The experimental results show that the proposed model reduces the complexity of the prediction model

mitigates the influence of the measuring noise on the prediction accuracy

and obtains good wind power prediction results.