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Dual multivariable model-free adaptive individual pitch control for load reduction in wind turbines with actuator faults

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  • Li, Jianshen
  • Wang, Shuangxin

Abstract

Thanks to the great advances in the installations of large wind turbines, individual pitch control (IPC) has gained mounting interest among researchers. The actuator faults, however, have become a hindrance with the individual pitch process introducing more actuator actions and the pitch system operating in complex conditions. The traditional fault-tolerant control strategies of the IPC, which are mainly based on the system modeling information, and require the process of fault diagnosis, isolation or parameter estimation. The subsequent model errors and unmodeled dynamics have somehow limited the application of the strategies. Therefore, this paper proposes a passive fault-tolerant individual pitch control scheme independent of the above process, and based on the scheme, a dual multivariable model-free adaptive control strategy with differential characteristic is constructed. The benchmark 5 MW wind turbine model provided by FAST is employed to evaluate the performance. The results show that, compared with the traditional individual pitch control strategy, the proposed scheme can achieve almost identical load control and even better power control under fault-free conditions. Once the fault occurs, the proposed scheme can quickly compensate for the faulty actuator dynamics, and finally achieve almost the same performance in power and load control as under the nominal conditions.

Suggested Citation

  • Li, Jianshen & Wang, Shuangxin, 2021. "Dual multivariable model-free adaptive individual pitch control for load reduction in wind turbines with actuator faults," Renewable Energy, Elsevier, vol. 174(C), pages 293-304.
  • Handle: RePEc:eee:renene:v:174:y:2021:i:c:p:293-304
    DOI: 10.1016/j.renene.2021.04.080
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    References listed on IDEAS

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    1. Yuan, Yuan & Chen, Xu & Tang, J., 2020. "Multivariable robust blade pitch control design to reject periodic loads on wind turbines," Renewable Energy, Elsevier, vol. 146(C), pages 329-341.
    2. 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.
    3. Lasheen, Ahmed & Elshafei, Abdel Latif, 2016. "Wind-turbine collective-pitch control via a fuzzy predictive algorithm," Renewable Energy, Elsevier, vol. 87(P1), pages 298-306.
    4. Lasheen, Ahmed & Saad, Mohamed S. & Emara, Hassan M. & Elshafei, Abdel Latif, 2019. "Tube-based explicit model predictive output-feedback controller for collective pitching of wind turbines," Renewable Energy, Elsevier, vol. 131(C), pages 549-562.
    5. Li, Jianshen & Wang, Shuangxin & Li, Yaguang, 2020. "A model-free adaptive controller with tracking error differential for collective pitching of wind turbines," Renewable Energy, Elsevier, vol. 161(C), pages 435-447.
    6. Zuo, Haoran & Bi, Kaiming & Hao, Hong, 2020. "A state-of-the-art review on the vibration mitigation of wind turbines," Renewable and Sustainable Energy Reviews, Elsevier, vol. 121(C).
    7. Cho, Seongpil & Gao, Zhen & Moan, Torgeir, 2018. "Model-based fault detection, fault isolation and fault-tolerant control of a blade pitch system in floating wind turbines," Renewable Energy, Elsevier, vol. 120(C), pages 306-321.
    8. Abdelbaky, Mohamed Abdelkarim & Liu, Xiangjie & Jiang, Di, 2020. "Design and implementation of partial offline fuzzy model-predictive pitch controller for large-scale wind-turbines," Renewable Energy, Elsevier, vol. 145(C), pages 981-996.
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    Cited by:

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    2. Jordi Cusidó & Arnau López & Mattia Beretta, 2021. "Fault-Tolerant Control of a Wind Turbine Generator Based on Fuzzy Logic and Using Ensemble Learning," Energies, MDPI, vol. 14(16), pages 1-20, August.
    3. Liu, Yanhua & Patton, Ron J. & Shi, Shuo, 2023. "Actuator fault tolerant offshore wind turbine load mitigation control," Renewable Energy, Elsevier, vol. 205(C), pages 432-446.
    4. Shi Liu & Yi Yang & Chengyuan Wang & Yuangang Tu & Zhenqing Liu, 2021. "Proposal of a Novel Mooring System Using Three-Bifurcated Mooring Lines for Spar-Type Off-Shore Wind Turbines," Energies, MDPI, vol. 14(24), pages 1-33, December.

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