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A robust LMI-based pitch controller for large wind turbines

Author

Listed:
  • Hassan, H.M.
  • ElShafei, A.L.
  • Farag, W.A.
  • Saad, M.S.

Abstract

This paper utilizes the linear matrix inequalities’ techniques (LMI) for designing a robust collective pitch controller (CPC) for large wind turbines. CPC operates during up rated wind speeds to regulate the generator speed in order to harvest the rated electrical power. The proposed design takes into account model uncertainties by designing a controller based on a polytopic model. The LMI-based approach allows additional constraints to be included in the design (e.g. H∞ problem, H2 problem, H∞/H2 trade-off criteria, and pole clustering). These constraints are exploited to include requirements for perfect regulation, efficient disturbance rejection, and permissible actuator usage. The proposed controller is combined with individual pitch controller (IPC) that reduces the periodic blade’s load by alleviating once per revolution (1P) frequency fatigue loads. FAST (Fatigue, Aero-dynamics, Structures, and Turbulence) software code developed at the US National Renewable Energy Laboratory (NREL) is used to verify the results.

Suggested Citation

  • Hassan, H.M. & ElShafei, A.L. & Farag, W.A. & Saad, M.S., 2012. "A robust LMI-based pitch controller for large wind turbines," Renewable Energy, Elsevier, vol. 44(C), pages 63-71.
    • Handle: RePEc:eee:renene:v:44:y:2012:i:c:p:63-71
    DOI: 10.1016/j.renene.2011.12.016
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    Citations

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    Cited by:

    1. Assareh, Ehsanolah & Biglari, Mojtaba, 2015. "A novel approach to capture the maximum power from variable speed wind turbines using PI controller, RBF neural network and GSA evolutionary algorithm," Renewable and Sustainable Energy Reviews, Elsevier, vol. 51(C), pages 1023-1037.
    2. Lasheen, Ahmed & Elshafei, Abdel Latif, 2016. "Wind-turbine collective-pitch control via a fuzzy predictive algorithm," Renewable Energy, Elsevier, vol. 87(P1), pages 298-306.
    3. Sampaio, Leonardo P. & de Brito, Moacyr A.G. & de A. e Melo, Guilherme & Canesin, Carlos A., 2016. "Grid-tie three-phase inverter with active power injection and reactive power compensation," Renewable Energy, Elsevier, vol. 85(C), pages 854-864.
    4. Tiwari, Ramji & Babu, N. Ramesh, 2016. "Recent developments of control strategies for wind energy conversion system," Renewable and Sustainable Energy Reviews, Elsevier, vol. 66(C), pages 268-285.
    5. Yuan, Yuan & Tang, J., 2017. "Adaptive pitch control of wind turbine for load mitigation under structural uncertainties," Renewable Energy, Elsevier, vol. 105(C), pages 483-494.
    6. Petrović, Vlaho & Jelavić, Mate & Baotić, Mato, 2015. "Advanced control algorithms for reduction of wind turbine structural loads," Renewable Energy, Elsevier, vol. 76(C), pages 418-431.
    7. Coral-Enriquez, Horacio & Cortés-Romero, John & Dorado-Rojas, Sergio A., 2019. "Rejection of varying-frequency periodic load disturbances in wind-turbines through active disturbance rejection-based control," Renewable Energy, Elsevier, vol. 141(C), pages 217-235.
    8. Lin, Zhongwei & Chen, Zhenyu & Wu, Qiuwei & Yang, Shuo & Meng, Hongmin, 2018. "Coordinated pitch & torque control of large-scale wind turbine based on Pareto efficiency analysis," Energy, Elsevier, vol. 147(C), pages 812-825.
    9. Lasheen, Ahmed & Saad, Mohamed S. & Emara, Hassan M. & Elshafei, Abdel Latif, 2017. "Continuous-time tube-based explicit model predictive control for collective pitching of wind turbines," Energy, Elsevier, vol. 118(C), pages 1222-1233.
    10. 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.
    11. Shrabani Sahu & Sasmita Behera, 2022. "A review on modern control applications in wind energy conversion system," Energy & Environment, , vol. 33(2), pages 223-262, March.
    12. Yolanda Vidal & Leonardo Acho & Ningsu Luo & Mauricio Zapateiro & Francesc Pozo, 2012. "Power Control Design for Variable-Speed Wind Turbines," Energies, MDPI, vol. 5(8), pages 1-18, August.
    13. Elnaggar, M. & Abdel Fattah, H.A. & Elshafei, A.L., 2014. "Maximum power tracking in WECS (Wind energy conversion systems) via numerical and stochastic approaches," Energy, Elsevier, vol. 74(C), pages 651-661.
    14. Baiomy, Nehal & Kikuuwe, Ryo, 2020. "An amplitude- and rate-saturated collective pitch controller for wind turbine systems," Renewable Energy, Elsevier, vol. 158(C), pages 400-409.
    15. Njiri, Jackson G. & Söffker, Dirk, 2016. "State-of-the-art in wind turbine control: Trends and challenges," Renewable and Sustainable Energy Reviews, Elsevier, vol. 60(C), pages 377-393.

    More about this item

    Keywords

    Pitch control; LMI; H∞ problem; H2 problem; Polytopic system; Pole clustering;
    All these keywords.

    JEL classification:

    • H2 - Public Economics - - Taxation, Subsidies, and Revenue

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