Prediction of fault location in overhead transmission line and underground distribution cable using probabilistic neural network

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dc.contributor.authorChiradeja, P.
dc.contributor.authorNgaopitakkul, A.
dc.date.accessioned2026-08-06T10:06:13Z
dc.date.available2026-08-06T10:06:13Z
dc.date.issued2013-01-01
dc.description.abstractThis paper proposes an algorithm based on a combination of discrete wavelet transform (DWT) and probabilistic neural network (PNN) for locating fault on transmission and distribution system. Simulations and the training process for the PNN are performed using Electromagnetic Transients Program (EMTP) and MATLAB. The mother wavelet daubechies4 (db4) is employed to decompose high frequency component from fault signals. The first peak time in first scale of each bus, that can detect fault, is used as input pattern for the training pattern. Various cases studies based on Thailand electricity transmission and distribution systems have been investigated so that the algorithm can be implemented. The results show that the proposed algorithm is capable of performing the fault location with satisfactory accuracy. © 2013 Praise Worthy Prize S.r.l. - All rights reserved.
dc.identifier.citationInternational Review of Electrical Engineering, 8(2), 762-768, 2013
dc.identifier.issn18276660
dc.identifier.other2-s2.0-84878221942
dc.identifier.urihttps://dspace.kmitl.ac.th/handle/123456789/4760
dc.sourceInternational Review of Electrical Engineering
dc.subjectFault location
dc.subjectProbabilistic neural network
dc.subjectTransmission and distribution
dc.subjectWavelet transform
dc.titlePrediction of fault location in overhead transmission line and underground distribution cable using probabilistic neural network
dc.typeArticle

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