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Self-triggered H-infinity pitch control for wind turbines considering stochastic wind speed

Author

Listed:
  • Zhang, Qiliang
  • Hou, Manxi
  • Zhao, Ya
  • Wang, Han
  • Hu, Bin
  • Liu, Ji
  • Lu, Qiang

Abstract

Stochastic wind speed can lead to output power fluctuation of wind turbines. To maintain the output power of the wind turbine within the admissible range of rated output power under stochastic wind speed, this paper investigates the H∞ pitch control of wind turbines using self-triggered mechanism. Firstly, a Markov-based wind turbine model is proposed to describe the dynamic characteristics of wind turbines under stochastic wind speed. The Markov-based wind turbine model describes the high-frequency wind speed through external disturbances, while it models the low-frequency wind speed using a Markov process. Then, the self-triggered mechanism is integrated into the design process of H∞ pitch controller. An algorithm is proposed to calculate the controller update interval and the feedback gain matrix. The derived self-triggered H∞ pitch control ensures that the output power of the wind turbine remains within the admissible range of rated output power, while decreasing the frequency of communications between the system and the controller. Finally, the simulation results based on a 5MW wind turbine show that compared with the existing results, the self-triggered H∞ pitch control can effectively reduce power fluctuations and blade loads while decreasing the update frequency of controller.

Suggested Citation

  • Zhang, Qiliang & Hou, Manxi & Zhao, Ya & Wang, Han & Hu, Bin & Liu, Ji & Lu, Qiang, 2026. "Self-triggered H-infinity pitch control for wind turbines considering stochastic wind speed," Renewable Energy, Elsevier, vol. 256(PA).
    • Handle: RePEc:eee:renene:v:256:y:2026:i:pa:s0960148125014314
    DOI: 10.1016/j.renene.2025.123769
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    References listed on IDEAS

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    1. Yang, Jin & Zhong, Qishui & Ghias, Amer M.Y.M. & Dong, Zhao Yang & Shi, Kaibo & Yu, Yongbin, 2023. "Distributed fault-tolerant PI load frequency control for power system under stochastic event-triggered scheme," Applied Energy, Elsevier, vol. 351(C).
    2. Zhang, Shuyuan & Wang, Ying & Liu, Yingming & Wang, Xiaodong & Bai, Wenchao & Cao, Tian, 2024. "Improved control strategy and designed control parameters of pitch system for wind turbine considering blade load reduction," Renewable Energy, Elsevier, vol. 232(C).
    3. Tang, Shize & Tian, De & Wu, Xiaoxuan & Huang, Mingyue & Deng, Ying, 2022. "Wind turbine load reduction based on 2DoF robust individual pitch control," Renewable Energy, Elsevier, vol. 183(C), pages 28-40.
    4. Shangguan, Xing-Chen & He, Yong & Zhang, Chuan-Ke & Jiang, Lin & Wu, Min, 2022. "Load frequency control of time-delayed power system based on event-triggered communication scheme," Applied Energy, Elsevier, vol. 308(C).
    5. El-Baklish, Shaimaa K. & El-Badawy, Ayman A. & Frison, Gianluca & Diehl, Moritz, 2020. "Nonlinear model predictive pitch control of aero-elastic wind turbine blades," Renewable Energy, Elsevier, vol. 161(C), pages 777-791.
    6. Hao, Wenxing & Li, Chun & Wu, Fuzhong, 2024. "Adaptive blade pitch control method based on an aerodynamic blade oscillator model for vertical axis wind turbines," Renewable Energy, Elsevier, vol. 223(C).
    7. Ibáñez, Bernabé & Inthamoussou, F.A. & De Battista, Hernán, 2020. "Wind turbine load analysis of a full range LPV controller," Renewable Energy, Elsevier, vol. 145(C), pages 2741-2753.
    8. Xie, Jingjie & Dong, Hongyang & Zhao, Xiaowei, 2023. "Data-driven torque and pitch control of wind turbines via reinforcement learning," Renewable Energy, Elsevier, vol. 215(C).
    Full references (including those not matched with items on IDEAS)

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