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Hierarchical Fault-Tolerant Control using Model Predictive Control for Wind Turbine Pitch Actuator Faults

Author

Listed:
  • Donggil Kim

    (Department of Robot Engineering, Kyungil University, Gyeongsan 38428, Korea)

  • Dongik Lee

    (School of Electronics Engineering, Kyungpook National University, Daegu 41566, Korea)

Abstract

Wind energy is one of the fastest growing energy sources in the world. It is expected that by the end of 2022 the installed capacity will exceed 250 GW thanks to the supply of large scale wind turbines in Europe. However, there are still challenging problems with wind turbines. In particular, off-shore and large-scale wind turbines are required to tackle the issue of maintainability and availability because they are installed in harsh off-shore environments, which may also prevent engineers from accessing the site for immediate repair works. Fault-tolerant control techniques have been widely exploited to overcome this issue. This paper proposes a novel fault-tolerant control strategy for wind turbines. The proposed strategy has a hierarchical structure, consisting of a pitch controller and a wind turbine controller, with parameter estimations using the adaptive fading Kalman filter technique. The pitch controller compensates any fault with a pitching actuator, while the wind turbine controller computes the optimal reference command for pitching behavior so that the effect of the fault with a pitch actuator can be minimized. The performance of the proposed approach is demonstrated through a set of simulations with a wind turbine benchmark model.

Suggested Citation

  • Donggil Kim & Dongik Lee, 2019. "Hierarchical Fault-Tolerant Control using Model Predictive Control for Wind Turbine Pitch Actuator Faults," Energies, MDPI, vol. 12(16), pages 1-13, August.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:16:p:3097-:d:256930
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    References listed on IDEAS

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    1. Yun-Tao Shi & Xiang Xiang & Li Wang & Yuan Zhang & De-Hui Sun, 2018. "Stochastic Model Predictive Fault Tolerant Control Based on Conditional Value at Risk for Wind Energy Conversion System," Energies, MDPI, vol. 11(1), pages 1-20, January.
    2. Kaldellis, John K. & Zafirakis, D., 2011. "The wind energy (r)evolution: A short review of a long history," Renewable Energy, Elsevier, vol. 36(7), pages 1887-1901.
    3. Njiri, Jackson G. & Söffker, Dirk, 2016. "State-of-the-art in wind turbine control: Trends and challenges," Renewable and Sustainable Energy Reviews, Elsevier, vol. 60(C), pages 377-393.
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