A Method for Fault Section Identification of Distribution Networks Based on Validation of Fault Indicators Using Artificial Neural Network

A fault section in Korean distribution networks is generally determined as a between switch with indicator (FI) and without an FI. However, the existing method cannot be applied to distributed generations (DGs) due false FIs that are generated by currents flowing from load side of location. To identify make applicable, this paper proposes determine utilizing artificial neural network (ANN) model for validating FIs, which difficult using mathematical equations. The proposed ANN built training relationship measured A, B, C, N phase acquired numerous simulations on sample system, guarantees 100% FI validations test data. can accurately distinguish genuine Fis ability model, thereby enabling conventional FI-based DG-connected any changes equipment communication infrastructure. verify performance method, various case studies considering real conditions conducted under MATLAB.