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dc.contributor.authorKhaleghi, Ali
dc.contributor.authorSadegh, Mahmoud Oukati
dc.contributor.authorGhazizadeh-Ahsaee, Mahdi
dc.contributor.authorRabori, Alireza Mehdipour
dc.date.accessioned2018-10-24T05:56:10Z
dc.date.available2018-10-24T05:56:10Z
dc.date.issued2018
dc.identifier.citationAdvances in electrical and electronic engineering. 2018, vol. 16, no. 2, p. 155-166 : ill.cs
dc.identifier.issn1336-1376
dc.identifier.issn1804-3119
dc.identifier.urihttp://hdl.handle.net/10084/132770
dc.description.abstractA novel method to locate the zone of transient faults and to classify the fault type in Power Distribution Systems using wavelet transforms and Adaptive Neuro-Fuzzy Inference Systems (ANFIS) has been developed. It draws on advanced techniques of signal processing based on wavelet transforms, using data sampled from the main feeder current to extract important characteristics and dynamic features of the fault signal. In this method, algorithms designed for fault detection and classification based on features extracted from wavelet transforms were implemented. One of four different algorithms based on ANFIS, according to the type of fault, was then used to locate the fault zone. Studies and simulations in an EMTP-RV environment for the 25kV power distribution system of Canada were carried out by considering ten types of faults with different fault inception, fault resistance and fault locations. The simulation results showed high accuracy in classifying the type of fault and determining the fault area, so that the maximum observed error was less than 2%.cs
dc.format.extent1494840 bytes
dc.format.mimetypeapplication/pdf
dc.language.isoencs
dc.publisherVysoká škola báňská - Technická univerzita Ostravacs
dc.relation.ispartofseriesAdvances in electrical and electronic engineeringcs
dc.relation.urihttp://dx.doi.org/10.15598/aeee.v16i2.2563cs
dc.rights© Vysoká škola báňská - Technická univerzita Ostrava
dc.rightsAttribution-NoDerivatives 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by-nd/4.0/*
dc.subjectAdaptive Neuro-Fuzzy Inference System (ANFIS)cs
dc.subjectelectrical distribution systemscs
dc.subjectfault classificationcs
dc.subjectfault detectioncs
dc.subjectfault locationcs
dc.subjectwavelet transformscs
dc.titleTransient fault area location and fault classification for distribution systems based on wavelet transform and Adaptive Neuro-Fuzzy Inference System (ANFIS)cs
dc.typearticlecs
dc.identifier.doi10.15598/aeee.v16i2.2563
dc.rights.accessopenAccesscs
dc.type.versionpublishedVersioncs
dc.type.statusPeer-reviewedcs


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