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Early Detection of Health Condition Degradation of Circuit Breaker Based on Electrical Quantity Monitoring

Author

Listed:
  • Lisheng Li

    (State Grid Shandong Electric Power Research Institute, Jinan 250003, China)

  • Bin Wang

    (State Key Laboratory of Control and Simulation of Power Systems and Generation Equipment, Department of Electrical Engineering, Tsinghua University, Haidian District, Beijing 100084, China)

  • Yang Liu

    (State Grid Shandong Electric Power Research Institute, Jinan 250003, China)

  • Haidong Yu

    (State Grid Shandong Electric Power Research Institute, Jinan 250003, China)

  • Shidong Zhang

    (State Grid Shandong Electric Power Research Institute, Jinan 250003, China)

  • Min Huang

    (State Grid Shandong Electric Power Research Institute, Jinan 250003, China)

Abstract

Circuit breakers on the filter bank branches in converter stations are vulnerable to contact wear and mechanical deterioration caused by frequent operations, which can lead to circuit breaker breakdowns and explosions. It is imperative to conduct research on the early detection of abnormal states in circuit breakers. Existing electrical quantity-based detection methods are constrained by a priori assumptions, and their measurement methods are susceptible to interference, leading to misjudgments. To address this issue, this paper examines the influence of changes in critical breakdown field strength and contact spacing on circuit breaker operation states. It also proposes a technical scheme that employs breakdown current values to comprehensively characterize circuit breaker operation states, replacing the use of critical breakdown field strength and contact spacing. An early detection method for abnormal circuit breaker states based on a sequence of breakdown current ratios at different times is proposed, and its effectiveness is verified through simulation and field recording data.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:14:p:5581-:d:1201473
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    References listed on IDEAS

    as
    1. 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.
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