Intelligent Substation Communication Network Traffic Predicting Based on Improved Elman Neural Network

Abstract

Due to the introduction of a large number of auxiliary monitoring equipment in smart substation, higher requirements are put forward for the performance of substation communication network. At present, there is a lack of effective methods for monitoring and predicting the traffic of substation communication network. In this paper, a communication Network traffic predicting method based on improved Elman neural network has been proposed, according to the characteristics of network communication in intelligent substation. An improved PSO algorithm is proposed to optimize the learning process of Elman neural network. The experimental results show that this method has better convergence and stability than the standard Elman network model, and can obtain higher prediction accuracy. The method proposed in this paper can effectively predict the traffic of substation communication network.