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A New Fault Diagnosis Algorithm for PMSG Wind Turbine Power Converters under Variable Wind Speed Conditions

Author

Listed:
  • Yingning Qiu

    (School of Energy and Power Engineering, Nanjing University of Science and Technology, No. 200, Xiao Ling Wei, Nanjing 210094, China)

  • Hongxin Jiang

    (School of Energy and Power Engineering, Nanjing University of Science and Technology, No. 200, Xiao Ling Wei, Nanjing 210094, China
    These authors contributed equally to this work.)

  • Yanhui Feng

    (School of Energy and Power Engineering, Nanjing University of Science and Technology, No. 200, Xiao Ling Wei, Nanjing 210094, China
    These authors contributed equally to this work.)

  • Mengnan Cao

    (School of Energy and Power Engineering, Nanjing University of Science and Technology, No. 200, Xiao Ling Wei, Nanjing 210094, China)

  • Yong Zhao

    (School of Energy and Power Engineering, Nanjing University of Science and Technology, No. 200, Xiao Ling Wei, Nanjing 210094, China)

  • Dan Li

    (School of Energy and Power Engineering, Nanjing University of Science and Technology, No. 200, Xiao Ling Wei, Nanjing 210094, China)

Abstract

Although Permanent Magnet Synchronous Generator (PMSG) wind turbines (WTs) mitigate gearbox impacts, they requires high reliability of generators and converters. Statistical analysis shows that the failure rate of direct-drive PMSG wind turbines’ generators and inverters are high. Intelligent fault diagnosis algorithms to detect inverters faults is a premise for the condition monitoring system aimed at improving wind turbines’ reliability and availability. The influences of random wind speed and diversified control strategies lead to challenges for developing intelligent fault diagnosis algorithms for converters. This paper studies open-circuit fault features of wind turbine converters in variable wind speed situations through systematic simulation and experiment. A new fault diagnosis algorithm named Wind Speed Based Normalized Current Trajectory is proposed and used to accurately detect and locate faulted IGBT in the circuit arms. It is compared to direct current monitoring and current vector trajectory pattern approaches. The results show that the proposed method has advantages in the accuracy of fault diagnosis and has superior anti-noise capability in variable wind speed situations. The impact of the control strategy is also identified. Experimental results demonstrate its applicability on practical WT condition monitoring system which is used to improve wind turbine reliability and reduce their maintenance cost.

Suggested Citation

  • Yingning Qiu & Hongxin Jiang & Yanhui Feng & Mengnan Cao & Yong Zhao & Dan Li, 2016. "A New Fault Diagnosis Algorithm for PMSG Wind Turbine Power Converters under Variable Wind Speed Conditions," Energies, MDPI, vol. 9(7), pages 1-15, July.
    • Handle: RePEc:gam:jeners:v:9:y:2016:i:7:p:548-:d:73994
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    References listed on IDEAS

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    1. Jain, Bhavna & Jain, Shailendra & Nema, R.K., 2015. "Control strategies of grid interfaced wind energy conversion system: An overview," Renewable and Sustainable Energy Reviews, Elsevier, vol. 47(C), pages 983-996.
    2. Zaijun Wu & Xiaobo Dou & Jiawei Chu & Minqiang Hu, 2013. "Operation and Control of a Direct-Driven PMSG-Based Wind Turbine System with an Auxiliary Parallel Grid-Side Converter," Energies, MDPI, vol. 6(7), pages 1-17, July.
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    Cited by:

    1. Kyunghwan Choi & Kyung-Soo Kim & Seok-Kyoon Kim, 2019. "Proportional-Type Sensor Fault Diagnosis Algorithm for DC/DC Boost Converters Based on Disturbance Observer," Energies, MDPI, vol. 12(8), pages 1-14, April.
    2. Miranda, Rodolfo Farías & Salgado-Herrera, Nadia Maria & Rodríguez-Hernández, Osvaldo & Rodríguez-Rodríguez, Juan Ramon & Robles, Miguel & Ruiz-Robles, Dante & Venegas-Rebollar, Vicente, 2022. "Distributed generation in low-voltage DC systems by wind energy in the Baja California Peninsula, Mexico," Energy, Elsevier, vol. 242(C).
    3. Shoudao Huang & Yang Zhang & Sijia Hu, 2016. "Stator Current Harmonic Reduction in a Novel Half Quasi-Z-Source Wind Power Generation System," Energies, MDPI, vol. 9(10), pages 1-15, September.
    4. Fausto Pedro García Márquez & Alberto Pliego Marugán & Jesús María Pinar Pérez & Stuart Hillmansen & Mayorkinos Papaelias, 2017. "Optimal Dynamic Analysis of Electrical/Electronic Components in Wind Turbines," Energies, MDPI, vol. 10(8), pages 1-19, July.
    5. Lei Yu & Youtong Zhang & Wenqing Huang & Khaled Teffah, 2017. "A Fast-Acting Diagnostic Algorithm of Insulated Gate Bipolar Transistor Open Circuit Faults for Power Inverters in Electric Vehicles," Energies, MDPI, vol. 10(4), pages 1-16, April.

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