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Independent Pitch Adaptive Control of Large Wind Turbines Using State Feedback and Disturbance Accommodating Control

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  • Yingming Liu

    (School of Electrical Engineering, Shenyang University of Technology, Liao Shen West Road 111, Shenyang 110027, China)

  • Yi Wang

    (School of Electrical Engineering, Shenyang University of Technology, Liao Shen West Road 111, Shenyang 110027, China)

  • Xiaodong Wang

    (School of Electrical Engineering, Shenyang University of Technology, Liao Shen West Road 111, Shenyang 110027, China)

Abstract

Wind turbines experience significant unbalanced loads during operation, exacerbated by external disturbances that challenge the stability of the pitch control system and affect output power. This paper proposes an independent pitch adaptive control strategy integrating state feedback and disturbance accommodating control (DAC). Initially, nonlinear wind turbine dynamics are globally linearized, and DAC is applied to mitigate the impact of wind disturbances dynamically. Subsequently, the entire range of wind speeds is segmented, and controllers are individually designed to optimize gain settings according to specific control objectives at each wind speed interval. Scheduling parameters such as collective pitch angle and tower fore-aft displacement are identified and trained using Radial Basis Function Neural Networks (RBFNN). Finally, based on the output gain values determined by RBFNN, the full-state feedback controller group is adaptively adjusted, and the optimal controller is selected for the final output. Simulations conducted on the NREL 5MW reference wind turbine model using FAST and Simulink demonstrate that compared to the ROSCO controller, the proposed strategy ensures smoother output power and effectively reduces blade and tower loads, thereby extending the turbine’s operational lifespan.

Suggested Citation

  • Yingming Liu & Yi Wang & Xiaodong Wang, 2024. "Independent Pitch Adaptive Control of Large Wind Turbines Using State Feedback and Disturbance Accommodating Control," Energies, MDPI, vol. 17(18), pages 1-17, September.
    • Handle: RePEc:gam:jeners:v:17:y:2024:i:18:p:4619-:d:1478426
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    References listed on IDEAS

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    1. Xingqi Hu & Wen Tan & Guolian Hou, 2023. "PIDD2 Control of Large Wind Turbines’ Pitch Angle," Energies, MDPI, vol. 16(13), pages 1-22, July.
    2. Abhinandan Routray & Nitin Sivakumar & Sung-ho Hur & Deok-je Bang, 2023. "A Comparative Study of Optimal Individual Pitch Control Methods," Sustainability, MDPI, vol. 15(14), pages 1-25, July.
    3. Adrian Gambier, 2021. "Pitch Control of Three Bladed Large Wind Energy Converters—A Review," Energies, MDPI, vol. 14(23), pages 1-24, December.
    4. Novaes Menezes, Eduardo José & Araújo, Alex Maurício & Rohatgi, Janardan Singh & González del Foyo, Pedro Manuel, 2018. "Active load control of large wind turbines using state-space methods and disturbance accommodating control," Energy, Elsevier, vol. 150(C), pages 310-319.
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