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A Simple-to-Implement Fault Diagnosis Method for Open Switch Fault in Wind System PMSG Drives without Threshold Setting

Author

Listed:
  • Tan Yanghong

    (College of electrical and information engineering, Hunan University, Changsha 410082, China)

  • Zhang Haixia

    (College of electrical and information engineering, Hunan University, Changsha 410082, China)

  • Zhou Ye

    (NARI Group Corporation/State Grid Electric Power Research Institute, Nanjing 210003, China)

Abstract

The conversion system is a major contributor to failure rates. These faults lead to time and cost consuming. Fault diagnosis capabilities pay as a solver to achieve a steady system. This paper presents a full analysis of permanent magnet synchronous generator wind system (PMSGWS) and proposes a special RMS voltage-based fault diagnosis method. The full analysis presents a comprehensive knowledge of faulty behaviors especially under arm current flowing or cutting off. Due to enough knowledge of faulty behaviors, the implementation of the detection method without threshold setting is contributed by the special RMS voltage. Its sample period is set longer than the time of the maximum pulse width ratio (MPR) and shorter than the fault show time of lower tube voltage. Due to this, the detection speed and robustness are achieved. By these simple settings for the fault diagnosis method, the faulty switch is detected in less than 1/4 of the period. Simulation and experimental results confirm the validity and feasibility of the new proposed fault detection method.

Suggested Citation

  • Tan Yanghong & Zhang Haixia & Zhou Ye, 2018. "A Simple-to-Implement Fault Diagnosis Method for Open Switch Fault in Wind System PMSG Drives without Threshold Setting," Energies, MDPI, vol. 11(10), pages 1-18, September.
    • Handle: RePEc:gam:jeners:v:11:y:2018:i:10:p:2571-:d:172207
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    References listed on IDEAS

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    1. Yang, Zhimin & Chai, Yi, 2016. "A survey of fault diagnosis for onshore grid-connected converter in wind energy conversion systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 66(C), pages 345-359.
    2. Igba, Joel & Alemzadeh, Kazem & Durugbo, Christopher & Eiriksson, Egill Thor, 2016. "Analysing RMS and peak values of vibration signals for condition monitoring of wind turbine gearboxes," Renewable Energy, Elsevier, vol. 91(C), pages 90-106.
    3. Hongqian Wei & Youtong Zhang & Lei Yu & Mengzhu Zhang & Khaled Teffah, 2018. "A New Diagnostic Algorithm for Multiple IGBTs Open Circuit Faults by the Phase Currents for Power Inverter in Electric Vehicles," Energies, MDPI, vol. 11(6), pages 1-14, June.
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    Cited by:

    1. Michał Gwóźdź & Michał Krystkowiak & Łukasz Ciepliński & Ryszard Strzelecki, 2020. "A Wind Energy Conversion System Based on a Generator with Modulated Magnetic Flux," Energies, MDPI, vol. 13(12), pages 1-18, June.
    2. Youjie Ma & Long Tao & Xuesong Zhou & Wei Li & Xueqi Shi, 2019. "Analysis and Control of Wind Power Grid Integration Based on a Permanent Magnet Synchronous Generator Using a Fuzzy Logic System with Linear Extended State Observer," Energies, MDPI, vol. 12(15), pages 1-19, July.
    3. Youjie Ma & Faqing Zhao & Xuesong Zhou & Mao Liu & Bao Yang, 2019. "DC Side Bus Voltage Control of Wind Power Grid-Connected Inverter Based on Second-Order Linear Active Disturbance Rejection Control," Energies, MDPI, vol. 12(22), pages 1-20, November.
    4. Youjie Ma & Luyong Yang & Xuesong Zhou & Xia Yang & Yongliang Zhou & Bo Zhang, 2020. "Linear Active Disturbance Rejection Control for DC Bus Voltage Under Low-Voltage Ride-Through at the Grid-Side of Energy Storage System," Energies, MDPI, vol. 13(5), pages 1-22, March.

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