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Prediction of fault location in overhead transmission line and underground distribution cable using probabilistic neural network
Author(s)
Chiradeja, P.
Date Issued
January 1, 2013
Type
Article
Abstract
This 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.
Citation
International Review of Electrical Engineering, 8(2), 762-768, 2013