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Interturn Short Fault Detection and Location of Permanent Magnet Wind Generator Based on Negative Sequence Current Residuals

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  • Tonghua Wu

    (NARI Group Corporation, Nanjing 211106, China
    State Key Laboratory of Smart Grid Protection and Control, Nanjing 211106, China
    College of Energy and Electrical Engineering, Hohai University, Nanjing 210098, China)

  • Shouguo Cai

    (College of Energy and Electrical Engineering, Hohai University, Nanjing 210098, China)

  • Wei Dai

    (NARI Group Corporation, Nanjing 211106, China
    State Key Laboratory of Smart Grid Protection and Control, Nanjing 211106, China)

  • Ying Zhu

    (College of Energy and Electrical Engineering, Hohai University, Nanjing 210098, China)

  • Xiaobao Liu

    (NARI Group Corporation, Nanjing 211106, China)

  • Xindong Li

    (NARI Group Corporation, Nanjing 211106, China)

Abstract

This article proposes a model-based method for the detection and phase location of interturn short fault (ISF) in the permanent magnet synchronous generator (PMSG). The simplified mathematical model of PMSG with ISF on dq -axis is established to analyze the fault signature. The current residuals are accurately estimated through Luenberger observer based on the expanded mathematical model of PMSG. In current residuals, the second harmonics are extracted using negative sequence park transform and angular integral filtering to construct the fault detection index. In addition, the unbalance characteristics of three-phase current after ISF can reflect the location of the fault phase, based on which the location indexes are defined. Simulation results for various operating and fault severity conditions primarily validate the effectiveness and robustness of diagnosis method in this paper.

Suggested Citation

  • Tonghua Wu & Shouguo Cai & Wei Dai & Ying Zhu & Xiaobao Liu & Xindong Li, 2022. "Interturn Short Fault Detection and Location of Permanent Magnet Wind Generator Based on Negative Sequence Current Residuals," Energies, MDPI, vol. 15(24), pages 1-18, December.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:24:p:9441-:d:1002313
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    References listed on IDEAS

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    1. Yao, Jun & Liu, Ruikuo & Zhou, Te & Hu, Weihao & Chen, Zhe, 2017. "Coordinated control strategy for hybrid wind farms with DFIG-based and PMSG-based wind farms during network unbalance," Renewable Energy, Elsevier, vol. 105(C), pages 748-763.
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