NEURAL NETWORK MODELING OF RELAY PROTECTION WITH A TIME DELAY

Abstract

Modern electric power facilities – stations and high-voltage substations – have become digital objects with the active use of high-speed local networks directly involved in the technological process. Management, analysis and control of information exchange in the digital substation of the power system require the development of new means and approaches. For these purposes, machine learning methods can be used, in particular the apparatus of artificial neural networks (ANN). The paper shows the possibilities of using direct propagation ANNs (multilayer perceptrons) for modeling and identifying anomalies in the operation modes of relay protection with a time delay. The results of training and testing of the ANN are presented on the example of analyzing the operation of the over current protection in the “sliding time window” mode in a three-phase electrical network. The proposed neuroalgorithm and configuration of the ANN can be used to control the modes and accuracy of relay and cybernetic defenses.