Please use this identifier to cite or link to this item: http://ir.unikl.edu.my/jspui/handle/123456789/20195
metadata.conference.dc.title: Voltage & Current Magnitude Pattern Recognization by Using Fuzzy Logic for fault Types Classification
metadata.conference.dc.contributor.*: Dr Lilik Jamilatul Awalin
metadata.conference.dc.subject: fuzzy logic, fault type classification, Single Line to Ground Fault, fault resistance, distribution network
metadata.conference.dc.date.issued: 24-Aug-2018
metadata.conference.dc.description.abstract: This research introduces the appropriate input pattern of Fuzzy Logic design for fault type classification of Single Line to Ground Fault at distribution network. The proposed design is solely using Fuzzy Logic as the research technique with input data from PSCAD simulation. PSCAD software simulate the circuit configuration for fault disturbance at the distribution network. The research technique was 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 Fuzzy Logic design. The acquired results that represented in average accuracy shown that voltage sag and current swell can draw a satisfying accuracy in classifying the fault type.
metadata.conference.dc.description: UniKL BMI
metadata.conference.dc.identifier.uri: http://ir.unikl.edu.my/jspui/handle/123456789/20195
metadata.conference.dc.conference.name: PEOCO 2018
metadata.conference.dc.conference.year: 2018
Appears in Collections:Conference Papers



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