DocumentCode :
2878738
Title :
Classification of power distribution system fault currents using wavelets associated to artificial neural networks
Author :
Assef, Yasmine ; Chaari, Oinis ; Meunier, Michel
Author_Institution :
Service Electrotechnique et Electron. Ind., Ecole Superieure d´´Electr., Gif-sur-Yvette, France
fYear :
1996
fDate :
18-21 Jun 1996
Firstpage :
421
Lastpage :
424
Abstract :
In a power distribution system with a resonant neutral grounding, traditional protection algorithms based on a steady state analysis are no longer adapted. Hence a good use of transients becomes essential. This paper deals with the possibility of using wavelet transform as a preprocess for artificial neural networks (ANN) in the algorithm of power system relays. The ANN decides, after training, if the measured signal is faulty or sound. The inputs of the ANN are the arguments of wavelet coefficients obtained after applying a recursive wavelet transform on faulty signals generated with EMTP (ElectroMagnetic Transient Program). A comparison between the wavelets and fast Fourier transform has been made
Keywords :
distribution networks; earthing; fault currents; fault location; neural nets; power system analysis computing; wavelet transforms; EMTP; ElectroMagnetic Transient Program; artificial neural networks; fast Fourier transform; faulty signals; power distribution system fault currents; power system relays; protection algorithms; recursive wavelet transform; resonant neutral grounding; steady state analysis; wavelet coefficients; wavelet transform; wavelets; Algorithm design and analysis; Artificial neural networks; EMTP; Fault currents; Grounding; Power distribution; Power system protection; Resonance; Steady-state; Wavelet transforms;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Time-Frequency and Time-Scale Analysis, 1996., Proceedings of the IEEE-SP International Symposium on
Conference_Location :
Paris
Print_ISBN :
0-7803-3512-0
Type :
conf
DOI :
10.1109/TFSA.1996.550082
Filename :
550082
Link To Document :
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