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A New Cross-Correlation Algorithm Based on Distance for Improving Localization Accuracy of Partial Discharge in Cables Lines

Author

Listed:
  • Xianjie Rao

    (College of Electrical Engineering, Sichuan University, Chengdu 610065, China)

  • Kai Zhou

    (College of Electrical Engineering, Sichuan University, Chengdu 610065, China)

  • Yuan Li

    (College of Electrical Engineering, Sichuan University, Chengdu 610065, China)

  • Guangya Zhu

    (College of Electrical Engineering, Sichuan University, Chengdu 610065, China)

  • Pengfei Meng

    (College of Electrical Engineering, Sichuan University, Chengdu 610065, China)

Abstract

Locating the partial discharge (PD) source is one of the most effective means to locate local defects in power cable lines. The sampling rate and the frequency-dependent characteristic of phase velocity have an obvious influence on localization accuracy based on the times of arrival (TOA) evaluation algorithm. In this paper, we present a cross-correlation algorithm based on propagation distance to locate the PD source in cable lines. First, we introduce the basic principle of the cross-correlation function of propagation distance. Then we verify the proposed method through a computer simulation model and investigate the influences of propagation distance, sampling rate, and noise on localization accuracy. Finally, we perform PD location experiments on two 250 m 10 kV XLPE power cables using the oscillation wave test system. The simulation and experiment results indicate that compared with traditional TOA evaluation methods, the proposed method has superior locating precision.

Suggested Citation

  • Xianjie Rao & Kai Zhou & Yuan Li & Guangya Zhu & Pengfei Meng, 2020. "A New Cross-Correlation Algorithm Based on Distance for Improving Localization Accuracy of Partial Discharge in Cables Lines," Energies, MDPI, vol. 13(17), pages 1-13, September.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:17:p:4549-:d:407922
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    References listed on IDEAS

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    1. Muhammad Shafiq & Ivar Kiitam & Kimmo Kauhaniemi & Paul Taklaja & Lauri Kütt & Ivo Palu, 2020. "Performance Comparison of PD Data Acquisition Techniques for Condition Monitoring of Medium Voltage Cables," Energies, MDPI, vol. 13(16), pages 1-14, August.
    2. Kai Zhou & Mingzhi Li & Yuan Li & Min Xie & Yonglu Huang, 2019. "An Improved Denoising Method for Partial Discharge Signals Contaminated by White Noise Based on Adaptive Short-Time Singular Value Decomposition," Energies, MDPI, vol. 12(18), pages 1-16, September.
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    Cited by:

    1. Michał Borecki, 2020. "A Proposed New Approach for the Assessment of Selected Operating Conditions of the High Voltage Cable Line," Energies, MDPI, vol. 13(20), pages 1-15, October.

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