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Active load control of large wind turbines using state-space methods and disturbance accommodating control

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  • Novaes Menezes, Eduardo José
  • Araújo, Alex Maurício
  • Rohatgi, Janardan Singh
  • González del Foyo, Pedro Manuel

Abstract

The control of wind turbine loads is fundamental to reduce wind energy cost. Wind turbines are complex dynamic systems subjected to random wind loads and harsh operational vibrations. Active load control reduces wind turbine mechanical vibrations, provoking an increase in wind turbine components lifetimes and the design of lighter and more flexible parts, reducing wind turbine global cost. The pitch control system plays a decisive role in shaping the wind turbine dynamics. By using the appropriate control methods, it can be used to reduce the dynamic response in most of wind turbine components, given the fully-coupled system dynamics. In this paper, it is demonstrated the development of an active load control of the wind turbine tower loads using the pitch control system. State-space control is carried out to consider the coupled wind turbine dynamics and the disturbance accommodating control (DAC) is used to cancel the effect of wind disturbances in the dynamics of the overall system. The active load control is performed without damaging the aerodynamic power control.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:energy:v:150:y:2018:i:c:p:310-319
    DOI: 10.1016/j.energy.2018.02.143
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    References listed on IDEAS

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    Cited by:

    1. Moodi, Hoda & Bustan, Danyal, 2019. "Wind turbine control using T-S systems with nonlinear consequent parts," Energy, Elsevier, vol. 172(C), pages 922-931.
    2. 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.
    3. Nejra Beganovic & Jackson G. Njiri & Dirk Söffker, 2018. "Reduction of Structural Loads in Wind Turbines Based on an Adapted Control Strategy Concerning Online Fatigue Damage Evaluation Models," Energies, MDPI, vol. 11(12), pages 1-15, December.
    4. Jingchun Chu & Ling Yuan & Yang Hu & Chenyang Pan & Lei Pan, 2019. "Comparative Analysis of Identification Methods for Mechanical Dynamics of Large-Scale Wind Turbine," Energies, MDPI, vol. 12(18), pages 1-24, September.
    5. Dai, Juchuan & Li, Mimi & Zhang, Fan & Zeng, Huifan, 2024. "Field load testing of wind turbines based on the relational model of strain vs load," Renewable Energy, Elsevier, vol. 221(C).
    6. Raja M. Imran & D. M. Akbar Hussain & Bhawani Shanker Chowdhry, 2018. "Parameterized Disturbance Observer Based Controller to Reduce Cyclic Loads of Wind Turbine," Energies, MDPI, vol. 11(5), pages 1-13, May.
    7. Gao, Xiaoxia & Zhang, Shaohai & Li, Luqing & Xu, Shinai & Chen, Yao & Zhu, Xiaoxun & Sun, Haiying & Wang, Yu & Lu, Hao, 2022. "Quantification of 3D spatiotemporal inhomogeneity for wake characteristics with validations from field measurement and wind tunnel test," Energy, Elsevier, vol. 254(PA).

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