Centralized radial feeder protection in electric power distribution using artificial neural networks

Abstract

Abstract The paper deals with a new way of determining a fault location in an electric power distribution radial feeder using an artificial neural network (ANN) and presents a new centralized protection method based on ANN. The aim of the devised algorithm is to detect the presence of a fault in a radial feeder and to disconnect faulted laterals from the distribution network. The protection schemes that are currently in use cannot leave the whole feeder energized by disconnecting faulted laterals only without even short de-energization of the healthy part of the feeder. A simulation model is also made for training the ANN and for testing the results. Current values for faulty and healthy states are generated by the simulation model and are used as training and testing data for the algorithm. The purpose of the algorithm is to make a decision which feeder circuit breakers should trip. The simulation model and the ANN are modeled by using MATLAB tools. The results show that the tripping of circuit breakers initiated by the algorithm is correct for all states.