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Recognition of Power Quality Events by Using Multiwavelet-Based Neural Network

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3 Author(s)
Kaewarsa, S. ; Rajamangala Univ. of Technol. Isan, Sakon Nakhon ; Attakitmongcol, K. ; Kulworawanichpong, T.

Recognition of power quality events by analyzing the voltage and current waveform disturbances is a very important task for the power system monitoring. This paper presents a novel approach for the recognition of power quality disturbances using multiwavelet transform and neural networks. The proposed method employs the multiwavelet transform using multiresolution signal decomposition techniques working together with multiple neural networks using a learning vector quantization network as a powerful classifier. Various transient events are tested, such as voltage sag, swell, interruption, notching, impulsive transient, and harmonic distortion show that the classifier can detect and classify different.

Published in:

Computer and Information Science, 2007. ICIS 2007. 6th IEEE/ACIS International Conference on

Date of Conference:

11-13 July 2007

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