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A Fault Location Method in Distribution Networks Including DG
Finding and designing new methods for determining type and exact location of faults in power system has been a major subject for power system protection. One of the main capabilities that can improve the efficiency of new protection relays in distribution systems is exact fault locating. In this paper, a new approach for determining the exact fault type and location in distribution systems including distributed generation using MLP neural networks is presented. In the suggested method, after determining the fault type, by normalizing the fault current of the main source, the corresponding trained neural network has been activated and the exact location of occurred fault has been derived. The presented method has been implemented on a sample distribution network, simulated by DIgSILENT Power Factory 13.2, and its performance has been tested. The simulation results show high performance and accuracy of the method and substantiate that it can be used in modern heuristic protection schemes in distribution systems.
Distributed Generation, Distribution System, Fault Location, Neural Network
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