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Research on VFTO Identification of GIS Based on Wavelet Transform and Singular Value Decomposition

Author

Listed:
  • Gang Xiao

    (School of Automation, Wuhan University of Technology, Wuhan 430070, China
    Wuhan Digital Engineering Institute, Wuhan 430074, China)

  • Quansen Rong

    (School of Automation, Wuhan University of Technology, Wuhan 430070, China)

  • Miaoran Yang

    (School of Automation, Wuhan University of Technology, Wuhan 430070, China)

  • Peng Xiao

    (School of Automation, Wuhan University of Technology, Wuhan 430070, China)

  • Qihong Chen

    (School of Automation, Wuhan University of Technology, Wuhan 430070, China)

  • Junzhe Fan

    (School of Automation, Wuhan University of Technology, Wuhan 430070, China)

  • Haoran Guo

    (School of Automation, Wuhan University of Technology, Wuhan 430070, China)

  • Haonan Wang

    (School of Automation, Wuhan University of Technology, Wuhan 430070, China)

Abstract

The accurate identification of Very Fast Transient Overvoltage (VFTO) is the key of overvoltage control in modern smart grids. In order to accurately identify VFTO generated by the operation of a disconnector in Gas Insulated Substation (GIS), a VFTO identification method based on Wavelet Transform (WT) and Singular Value Decomposition (SVD) is proposed. The simulation model of VFTO is established in ATP-EMTP software first, and then wavelet decomposition is used in MATLAB software for VFTO simulation of the waveform from the ATP-EMTP software. Then, the feature matrix is composed of the coefficients of each frequency layer of the wavelet. The SVD is used to decompose the feature matrix, and finally the characteristic parameters of the VFTO are obtained. The simulation results in Matlab software indicate that the characteristic parameters of VFTO have an obvious difference compared with those of power frequency AC voltage, especially in the load-side, which verifies the effectiveness of the VFTO identification method based on WT and SVD proposed in this paper.

Suggested Citation

  • Gang Xiao & Quansen Rong & Miaoran Yang & Peng Xiao & Qihong Chen & Junzhe Fan & Haoran Guo & Haonan Wang, 2022. "Research on VFTO Identification of GIS Based on Wavelet Transform and Singular Value Decomposition," Energies, MDPI, vol. 15(9), pages 1-13, May.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:9:p:3367-:d:808991
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    Cited by:

    1. Lisheng Li & Bin Wang & Yang Liu & Haidong Yu & Shidong Zhang & Min Huang, 2023. "Early Detection of Health Condition Degradation of Circuit Breaker Based on Electrical Quantity Monitoring," Energies, MDPI, vol. 16(14), pages 1-15, July.

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