One New Research on Method of Intelligent Substation Network Traffic Prediction

Abstract

With the gradual implementation of intelligent network transformation substation, the industry began to pay attention from the smart substation network flow forecasting techniques. Intelligent substation network traffic anomaly event directly affects the operation of the protection device reliability, speed and agility. The paper first combination of gray theory and artificial neural network algorithm, create and analyze a gray neural network model, Then through additional momentum variable learning rate method right to update the value of gray neural network strategy to improve, Proposes an model is based on improved gray neural network intelligent substation network traffic prediction, finally the use of smart substation station level switches network traffic data, for example, to the original frequency of data collection as the basis for simulation, experiments show that the model predicts high accuracy, fast convergence, improved intelligent substation network traffic prediction accuracy and rapidity, to protect the safe operation of the power grid.