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Active Disturbance Rejection Control for Wind Turbine Fatigue Load

Author

Listed:
  • Xingkang Jin

    (School of Control and Computer Engineering, North China Electric Power University, 2 Beinong Road, Changping District, Beijing 102206, China)

  • Wen Tan

    (School of Control and Computer Engineering, North China Electric Power University, 2 Beinong Road, Changping District, Beijing 102206, China)

  • Yarong Zou

    (School of Control and Computer Engineering, North China Electric Power University, 2 Beinong Road, Changping District, Beijing 102206, China)

  • Zijian Wang

    (School of Control and Computer Engineering, North China Electric Power University, 2 Beinong Road, Changping District, Beijing 102206, China)

Abstract

With the participation of wind power in grid frequency modulation, the fatigue load of the wind turbine increases accordingly. A new control method that considers both fatigue load and output power of wind turbine (WT) is proposed in this paper. A linear active disturbance rejection control (LADRC) is designed and applied for the pitch angle in the wind turbine load reduction control. The particle swarm optimization (PSO) algorithm is used to optimize the parameters of the wind turbine controller, and the total variation of the wind turbine shaft torque and tower bending moment is added to construct a new objective function to further reduce the fatigue load of the wind turbine. The design-optimized controller is validated on a 5 MW wind turbine in SimWindFarm. The simulation results show that the LADRC controller can accurately track the reference power of the wind turbine, reduce the pitch angle fluctuation of the wind turbine, reduce the fatigue load of the wind turbine, and improve the service life of the wind turbine.

Suggested Citation

  • Xingkang Jin & Wen Tan & Yarong Zou & Zijian Wang, 2022. "Active Disturbance Rejection Control for Wind Turbine Fatigue Load," Energies, MDPI, vol. 15(17), pages 1-15, August.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:17:p:6178-:d:897548
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    References listed on IDEAS

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    1. Shiyao Qin & Yuyang Chang & Zhen Xie & Shaolin Li, 2021. "Improved Virtual Inertia of PMSG-Based Wind Turbines Based on Multi-Objective Model-Predictive Control," Energies, MDPI, vol. 14(12), pages 1-20, June.
    2. Zhang, Jin-hua & Liu, Yong-qian & Tian, De & Yan, Jie, 2015. "Optimal power dispatch in wind farm based on reduced blade damage and generator losses," Renewable and Sustainable Energy Reviews, Elsevier, vol. 44(C), pages 64-77.
    3. Yingming Liu & Yingwei Wang & Xiaodong Wang & Jiangsheng Zhu & Wai Hou Lio, 2019. "Active Power Dispatch for Supporting Grid Frequency Regulation in Wind Farms Considering Fatigue Load," Energies, MDPI, vol. 12(8), pages 1-23, April.
    4. Bofeng Xu & Yue Yuan & Haoming Liu & Peng Jiang & Ziqi Gao & Xiang Shen & Xin Cai, 2020. "A Pitch Angle Controller Based on Novel Fuzzy-PI Control for Wind Turbine Load Reduction," Energies, MDPI, vol. 13(22), pages 1-16, November.
    5. Camblong, H. & Nourdine, S. & Vechiu, I. & Tapia, G., 2012. "Control of wind turbines for fatigue loads reduction and contribution to the grid primary frequency regulation," Energy, Elsevier, vol. 48(1), pages 284-291.
    6. Srikanth Bashetty & Joaquin I. Guillamon & Shanmukha S. Mutnuri & Selahattin Ozcelik, 2020. "Design of a Robust Adaptive Controller for the Pitch and Torque Control of Wind Turbines," Energies, MDPI, vol. 13(5), pages 1-22, March.
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    Cited by:

    1. Wei Fan & Zhijian Hu & Veerapandiyan Veerasamy, 2022. "PSO-Based Model Predictive Control for Load Frequency Regulation with Wind Turbines," Energies, MDPI, vol. 15(21), pages 1-15, November.

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