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  4. Differential protection schemes for classification of fault detection between external fault and internal winding fault in transformer using probabilistic neural network
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Differential protection schemes for classification of fault detection between external fault and internal winding fault in transformer using probabilistic neural network

Author(s)
Jettanasen, C.
Klomjit, J.
Positharn, C.
Bunjongjit, S.
Ngaopitakkul, A.
Date Issued
December 1, 2012
Type
Conference Paper
DOI
10.1109/iFUZZY.2012.6409691
Abstract
This paper proposes an algorithm based on a combination of discrete wavelet transform (DWT) and probabilistic neural network (PNN) for discriminating between external fault and internal winding fault in power transformer. The coefficients of the first scale from the DWT that can detect fault are investigated. The maximum coefficients details (cD1) from DWT in first scale at 1/4 cycle of phase A, B, C and zero sequence for post-fault differential current waveforms have been used as an input for the training process of the PNN in a decision algorithm. 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 detection with satisfactory accuracy. © 2012 IEEE.
Citation
2012 International Conference on Fuzzy Theory and Its Applications Ifuzzy 2012, 150-153, 2012
Subjects

Difference Relay

Fault

Probabilistic Neural ...

Transformer

Wavelet Transform

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