Fault Types Classification Accuracy Considering Four Different Methods

Abstract

This research introduces four different tools designed for fault type classifications at distribution network. The proposed designs are using Artificial Neural Network, Fuzzy Logic, conventional method and Support Vector Machine as the research techniques with input data obtained from PSCAD simulation. The circuit configuration for fault disturbance at the distribution network was simulated by PSCAD simulation program. The research techniques were applied with multiples input values of voltage and current that extracted from the PSCAD simulation. This research testifies the output result by using different fault resistance values; 0.01Ω, 10Ω, 30Ω, 50Ω and 70Ω. Voltage sag and current swell of phase a, b and c that were obtained from the PSCAD simulation have been used as the input variables for the four different research tools design. The acquired results that represented in average accuracy (%) shows that voltage sag and current swell can draw a satisfying accuracy in classifying the fault type.