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Novel Method for Identifying Fault Location of Mixed Lines

Author

Listed:
  • Lei Wang

    (School of Electrical and Electronic Engineering, Hubei University of Technology, Wuhan 430068, China)

  • Hui Liu

    (School of Electrical and Electronic Engineering, Hubei University of Technology, Wuhan 430068, China)

  • Le Van Dai

    (Institute of Research and Development, Duy Tan University, Danang 550000, Vietnam
    Office of Science Research and Development, Lac Hong University, Bien Hoa 810000, Vietnam)

  • Yuwei Liu

    (School of Electrical and Electronic Engineering, Hubei University of Technology, Wuhan 430068, China)

Abstract

The identification and localization of a fault are a basic requirement for optimal operation of a modern power system. An effective fault identification method significantly reduces outage time, improves the electrical supply reliability, and enhances the speed of protection control. This paper proposes a novel method based on the theory of the two-terminal traveling wave range to identify the fault location in a voltage source converter based high voltage direct current (VSC-HVDC) system containing mixed cable and overhead line segments. It uses variational mode decomposition (VMD) and the Teager energy operator (TEO) as a new method to detect the traveling wave fault through a fault signal. The effectiveness of the proposed method is verified via time domain simulation of the hybrid VSC-HVDC transmission system using PSCAD/EMTDC and MATLAB software. Simulation results show that the proposed method demonstrates high fault location accuracy and excellent robustness with a slight effect on transient resistance and fault types, and that it performs better than the existing transient detection techniques, such as wavelet transform and ensemble empirical mode decomposition.

Suggested Citation

  • Lei Wang & Hui Liu & Le Van Dai & Yuwei Liu, 2018. "Novel Method for Identifying Fault Location of Mixed Lines," Energies, MDPI, vol. 11(6), pages 1-19, June.
    • Handle: RePEc:gam:jeners:v:11:y:2018:i:6:p:1529-:d:152113
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    Citations

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    Cited by:

    1. Ana-Maria Moldovan & Mircea Ion Buzdugan, 2023. "Prediction of Faults Location and Type in Electrical Cables Using Artificial Neural Network," Sustainability, MDPI, vol. 15(7), pages 1-19, April.
    2. Ricardo Granizo Arrabé & Carlos A. Platero & Fernando Álvarez Gómez & Emilio Rebollo López, 2018. "New Differential Protection Method for Multiterminal HVDC Cable Networks," Energies, MDPI, vol. 11(12), pages 1-16, December.
    3. Shuhao Liu & Kunlun Han & Hongzheng Li & Tengyue Zhang & Fengyuan Chen, 2023. "A Two-Terminal Directional Protection Method for HVDC Transmission Lines of Current Fault Component Based on Improved VMD-Hilbert Transform," Energies, MDPI, vol. 16(19), pages 1-21, October.
    4. Mani Ashouri & Filipe Faria da Silva & Claus Leth Bak, 2019. "A Harmonic Based Pilot Protection Scheme for VSC-MTDC Grids with PWM Converters," Energies, MDPI, vol. 12(6), pages 1-16, March.

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