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Wavelet-Based Intelligent System for Recognition of Power Quality Disturbance Signals

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Advances in Neural Networks - ISNN 2006 (ISNN 2006)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3972))

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Abstract

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 new approach for the recognition of power quality disturbances using wavelet transform and neural networks. The proposed method employs the wavelet 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 power quality signal types efficiency.

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References

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Author information

Authors and Affiliations

  1. School of Electrical Engineering, Suranaree University of Technology, 111, Muang District, Nakhon Ratchasima, 30000, Thailand

    Suriya Kaewarsa & Kitti Attakitmongcol

  2. School of Electrical Engineering, Rajamangala University of Technology Isan, Sakon Nakhon Campus, Phangkhon District, Sakon Nakhon, 47160, Thailand

    Wichai Krongkitsiri

Authors
  1. Suriya Kaewarsa
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  2. Kitti Attakitmongcol
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  3. Wichai Krongkitsiri
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Editor information

Editors and Affiliations

  1. Department of Mechanical and Automation Engineering, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong, China

    Jun Wang

  2. Computational Intelligence Laboratory, School of Computer Science and Engineering, University of Electronic Science and Technology of China, 610054, Chengdu, P.R. China

    Zhang Yi

  3. Department of Electrical Engineering, University of Louisville, 40292, Louisville, KY, U.S.A

    Jacek M. Zurada

  4. Laboratory for Computational Biology, Shanghai Center for Systems Biomedicine, 800 Dong Chuan Rd., 200240, Shanghai, China

    Bao-Liang Lu

  5. School of Electrical and Electronic Engineering, University of Manchester, UK

    Hujun Yin

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© 2006 Springer-Verlag Berlin Heidelberg

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Cite this paper

Kaewarsa, S., Attakitmongcol, K., Krongkitsiri, W. (2006). Wavelet-Based Intelligent System for Recognition of Power Quality Disturbance Signals. In: Wang, J., Yi, Z., Zurada, J.M., Lu, BL., Yin, H. (eds) Advances in Neural Networks - ISNN 2006. ISNN 2006. Lecture Notes in Computer Science, vol 3972. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11760023_199

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  • DOI: https://doi.org/10.1007/11760023_199

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-34437-7

  • Online ISBN: 978-3-540-34438-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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