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Power Quality Disturbance Recognition Using Wavelet-Based Neural Networks

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2 Author(s)
S. Kaewarsa ; School of Electrical Engineering, Rajamangala University of Technology Isan, Sakon Nakhon Campus, 199, Phangkhon Sub-District, Phangkhon District, Sakon Nakhon, 47160, Thailand ; K. Attakitmongcol

This paper proposes a wavelet-based neural network classifier for recognizing power quality disturbances is implemented and tested under various transient events. The discrete wavelet transform technique is integrated with multiple neural networks using a learning vector quantization network as a powerful classifier. Various transient events are tested, the results show that the classier can detect and classify different power quality disturbance types efficiency.

Published in:

TENCON 2005 - 2005 IEEE Region 10 Conference

Date of Conference:

21-24 Nov. 2005