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Fault Diagnosis and Fault Tolerant Control of Wind Turbines: An Overview

Author

Listed:
  • Afef Fekih

    (Electrical and Computer Engineering Department, University of Louisiana at Lafayette, P.O. Box 43890, Lafayette, LA 70504, USA)

  • Hamed Habibi

    (Automation and Robotics Research Group, Interdisciplinary Centre for Security, Reliability and Trust, University of Luxembourg, 29, Avenue JF Kennedy, L-1855 Luxembourg, Luxembourg)

  • Silvio Simani

    (Department of Engineering, University of Ferrara, Via Saragat 1E, 44122 Ferrara, FE, Italy)

Abstract

Wind turbines are playing an increasingly important role in renewable power generation. Their complex and large-scale structure, however, and operation in remote locations with harsh environmental conditions and highly variable stochastic loads make fault occurrence inevitable. Early detection and location of faults are vital for maintaining a high degree of availability and reducing maintenance costs. Hence, the deployment of algorithms capable of continuously monitoring and diagnosing potential faults and mitigating their effects before they evolve into failures is crucial. Fault diagnosis and fault tolerant control designs have been the subject of intensive research in the past decades. Significant progress has been made and several methods and control algorithms have been proposed in the literature. This paper provides an overview of the most recent fault diagnosis and fault tolerant control techniques for wind turbines. Following a brief discussion of the typical faults, the most commonly used model-based, data-driven and signal-based approaches are discussed. Passive and active fault tolerant control approaches are also highlighted and relevant publications are discussed. Future development tendencies in fault diagnosis and fault tolerant control of wind turbines are also briefly stated. The paper is written in a tutorial manner to provide a comprehensive overview of this research topic.

Suggested Citation

  • Afef Fekih & Hamed Habibi & Silvio Simani, 2022. "Fault Diagnosis and Fault Tolerant Control of Wind Turbines: An Overview," Energies, MDPI, vol. 15(19), pages 1-21, September.
  • Handle: RePEc:gam:jeners:v:15:y:2022:i:19:p:7186-:d:929260
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    References listed on IDEAS

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    1. Eryilmaz, Serkan & Kan, Cihangir, 2020. "Reliability based modeling and analysis for a wind power system integrated by two wind farms considering wind speed dependence," Reliability Engineering and System Safety, Elsevier, vol. 203(C).
    2. Mousavi, Yashar & Bevan, Geraint & Kucukdemiral, Ibrahim Beklan & Fekih, Afef, 2022. "Sliding mode control of wind energy conversion systems: Trends and applications," Renewable and Sustainable Energy Reviews, Elsevier, vol. 167(C).
    3. Li, He & Teixeira, Angelo P. & Guedes Soares, C., 2020. "A two-stage Failure Mode and Effect Analysis of offshore wind turbines," Renewable Energy, Elsevier, vol. 162(C), pages 1438-1461.
    4. Shi, Fengming & Patton, Ron, 2015. "An active fault tolerant control approach to an offshore wind turbine model," Renewable Energy, Elsevier, vol. 75(C), pages 788-798.
    5. Bhardwaj, U. & Teixeira, A.P. & Soares, C. Guedes, 2019. "Reliability prediction of an offshore wind turbine gearbox," Renewable Energy, Elsevier, vol. 141(C), pages 693-706.
    6. Langseth, Helge & Portinale, Luigi, 2007. "Bayesian networks in reliability," Reliability Engineering and System Safety, Elsevier, vol. 92(1), pages 92-108.
    7. Waseem El Sayed & Mostafa Abd El Geliel & Ahmed Lotfy, 2020. "Fault Diagnosis of PMSG Stator Inter-Turn Fault Using Extended Kalman Filter and Unscented Kalman Filter," Energies, MDPI, vol. 13(11), pages 1-24, June.
    8. Habibi, Hamed & Howard, Ian & Simani, Silvio, 2019. "Reliability improvement of wind turbine power generation using model-based fault detection and fault tolerant control: A review," Renewable Energy, Elsevier, vol. 135(C), pages 877-896.
    9. Castro-Santos, Laura & Martins, Elson & Guedes Soares, C., 2016. "Cost assessment methodology for combined wind and wave floating offshore renewable energy systems," Renewable Energy, Elsevier, vol. 97(C), pages 866-880.
    10. Alkaff, Abdullah & Qomarudin, Mochamad Nur & Bilfaqih, Yusuf, 2020. "Network reliability analysis: Matrix-exponential approach," Reliability Engineering and System Safety, Elsevier, vol. 204(C).
    11. Yeter, B. & Garbatov, Y. & Guedes Soares, C., 2020. "Risk-based maintenance planning of offshore wind turbine farms," Reliability Engineering and System Safety, Elsevier, vol. 202(C).
    12. Kang, Jichuan & Sun, Liping & Guedes Soares, C., 2019. "Fault Tree Analysis of floating offshore wind turbines," Renewable Energy, Elsevier, vol. 133(C), pages 1455-1467.
    13. Peng Guo & Jian Fu & XiYun Yang, 2018. "Condition Monitoring and Fault Diagnosis of Wind Turbines Gearbox Bearing Temperature Based on Kolmogorov-Smirnov Test and Convolutional Neural Network Model," Energies, MDPI, vol. 11(9), pages 1-16, August.
    14. Reder, Maik & Yürüşen, Nurseda Y. & Melero, Julio J., 2018. "Data-driven learning framework for associating weather conditions and wind turbine failures," Reliability Engineering and System Safety, Elsevier, vol. 169(C), pages 554-569.
    15. Afef Fekih & Saleh Mobayen & Chih-Chiang Chen, 2021. "Adaptive Robust Fault-Tolerant Control Design for Wind Turbines Subject to Pitch Actuator Faults," Energies, MDPI, vol. 14(6), pages 1-13, March.
    16. Seyed Mojtaba Tabatabaeipour & Peter F. Odgaard & Thomas Bak & Jakob Stoustrup, 2012. "Fault Detection of Wind Turbines with Uncertain Parameters: A Set-Membership Approach," Energies, MDPI, vol. 5(7), pages 1-25, July.
    17. Shanzhi Li & Abdel Aitouche & Nicolai Christov & Jian Zhang, 2022. "Fault-Tolerant Control of Wind Turbine System Using Linear Parameter-Varying Model," Mathematical Problems in Engineering, Hindawi, vol. 2022, pages 1-10, July.
    18. Yang, Bo & Yu, Tao & Shu, Hongchun & Zhang, Yuming & Chen, Jian & Sang, Yiyan & Jiang, Lin, 2018. "Passivity-based sliding-mode control design for optimal power extraction of a PMSG based variable speed wind turbine," Renewable Energy, Elsevier, vol. 119(C), pages 577-589.
    19. Cho, Seongpil & Choi, Minjoo & Gao, Zhen & Moan, Torgeir, 2021. "Fault detection and diagnosis of a blade pitch system in a floating wind turbine based on Kalman filters and artificial neural networks," Renewable Energy, Elsevier, vol. 169(C), pages 1-13.
    20. Kong, Ziqian & Tang, Baoping & Deng, Lei & Liu, Wenyi & Han, Yan, 2020. "Condition monitoring of wind turbines based on spatio-temporal fusion of SCADA data by convolutional neural networks and gated recurrent units," Renewable Energy, Elsevier, vol. 146(C), pages 760-768.
    21. Teng, Wei & Ding, Xian & Cheng, Hao & Han, Chen & Liu, Yibing & Mu, Haihua, 2019. "Compound faults diagnosis and analysis for a wind turbine gearbox via a novel vibration model and empirical wavelet transform," Renewable Energy, Elsevier, vol. 136(C), pages 393-402.
    22. García Márquez, Fausto Pedro & Tobias, Andrew Mark & Pinar Pérez, Jesús María & Papaelias, Mayorkinos, 2012. "Condition monitoring of wind turbines: Techniques and methods," Renewable Energy, Elsevier, vol. 46(C), pages 169-178.
    23. Azizi, Askar & Nourisola, Hamid & Shoja-Majidabad, Sajjad, 2019. "Fault tolerant control of wind turbines with an adaptive output feedback sliding mode controller," Renewable Energy, Elsevier, vol. 135(C), pages 55-65.
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    Cited by:

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