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Wind turbine load reduction based on 2DoF robust individual pitch control

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  • Tang, Shize
  • Tian, De
  • Wu, Xiaoxuan
  • Huang, Mingyue
  • Deng, Ying

Abstract

The individual pitch controller can mitigate asymmetric loads in wind turbines. However, wind turbine dynamics have strong nonlinearity and high uncertainty. In addition to target value tracking, suppression of wind disturbance is also a performance requirement of the individual pitch controller, while the traditional PI controller cannot take into account the tracking and disturbance rejection performance simultaneously. Therefore, the two-degree-of-freedom (2DoF) robust individual pitch controller is proposed to reduce loads in the above-rated region. Besides, parameter tuning is complicated in the design of the robust individual pitch controller. So the reference model method is proposed to preset the closed-loop system response. Firstly, the state-space model is established to describe the dynamics of the wind turbine. The multi-blade coordinate transformation is applied to transform the model into the fixed coordinate system. Subsequently, the μ-synthesis problem is solved by the D-K iterative algorithm to get the controller parameter. Finally, the control method is verified in GH Bladed. It is shown that rotor loads are suppressed without affecting the output power. Tower loads are also mitigated. Moreover, the relationship between the pitch actuator action and the load reduction capability is discussed by designing different bandwidths of the proposed method.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:renene:v:183:y:2022:i:c:p:28-40
    DOI: 10.1016/j.renene.2021.10.086
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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. Yarmohammadi, Mohammad J. & Sadeghzadeh, Arash & Taghizadeh, Mostafa, 2020. "Gain-scheduled control of wind turbine exploiting inexact wind speed measurement for full operating range," Renewable Energy, Elsevier, vol. 149(C), pages 890-901.
    3. Sungsu Park & Yoonsu Nam, 2012. "Two LQRI based Blade Pitch Controls for Wind Turbines," Energies, MDPI, vol. 5(6), pages 1-19, June.
    4. Jia, Chengzhen & Wang, Lingmei & Meng, Enlong & Chen, Liming & Liu, Yushan & Jia, Wenqiang & Bao, Yutao & Liu, Zhenguo, 2021. "Combining LIDAR and LADRC for intelligent pitch control of wind turbines," Renewable Energy, Elsevier, vol. 169(C), pages 1091-1105.
    5. Ossmann, Daniel & Seiler, Peter & Milliren, Christopher & Danker, Alan, 2021. "Field testing of multi-variable individual pitch control on a utility-scale wind turbine," Renewable Energy, Elsevier, vol. 170(C), pages 1245-1256.
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    Cited by:

    1. Kumarasamy Palanimuthu & Ganesh Mayilsamy & Ameerkhan Abdul Basheer & Seong-Ryong Lee & Dongran Song & Young Hoon Joo, 2022. "A Review of Recent Aerodynamic Power Extraction Challenges in Coordinated Pitch, Yaw, and Torque Control of Large-Scale Wind Turbine Systems," Energies, MDPI, vol. 15(21), pages 1-27, November.
    2. Huo, Zhihong & Xu, Chang, 2022. "Distributed cooperative automatic generation control and multi-event triggered mechanisms co-design for networked wind-integrated power systems," Renewable Energy, Elsevier, vol. 193(C), pages 41-56.

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