2020 4th International Symposium on Multidisciplinary Studies and Innovative Technologies (ISMSIT) · 2020 · 14 citations · 9 references
ComputingComputer ScienceElectrical EngineeringArtificial IntelligenceComputer NetworksMachine LearningDiagnosticsElectrical System DiagnosticsElectrical TechnologyFault DetectionNeural NetworksTransmission LinesFault Localization AlgorithmsFault LocationMachine Learning For Fault DetectionNeural Network ModelingShort Circuit DetectionShort-circuit Fault DetectionTransmission Line ModelingVoltage
In this study, an alternative approach based on artificial neural network (ANN) is presented in order to determine the location of short circuit faults that may occur in a 230 kV 100 km transmission line. The study is modeled with ANN algorithm using the feed forward standard back propagation technique. After processing the current and voltage information of the three phases taken from the line beginning, they are divided into specific 5 frequency groups and used as an input to ANN. The energy transmission line is modeled using MATLAB / Simulink. Tests are made by changing the values of the fault location and fault resistance in order to show the accuracy and the results are presented in tables.
9