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Nonlinear model predictive pitch control of aero-elastic wind turbine blades

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  • El-Baklish, Shaimaa K.
  • El-Badawy, Ayman A.
  • Frison, Gianluca
  • Diehl, Moritz

Abstract

This paper proposes a Nonlinear Model Predictive Controller (NMPC) for pitch control of Horizontal-Axis Wind Turbines (HAWTs) in Region 3 to avoid flutter aero-elastic instability. First, an aero-elastic HAWT rotor model was derived based on extended Hamilton’s principle using the coupled flap-wise and torsional motions of each blade. As for the aerodynamic loading, expressions for lift and pitching moment are obtained based on modifications of Theodorsen’s fixed wing strip theory for a rotating HAWT blade. The model is spatially discretized using the Assumed Modes Method with the first three flap-wise and two torsional mode shapes for the fixed cantilevered blade under free loading. This was applied to the 5-MW NREL (National Renewable Energy Laboratory) reference HAWT. The time-domain response under aerodynamic loading of the developed model was compared to FAST (Fatigue, Aerodynamics, Structure and Turbulence) aero-servo-elastic HAWT simulator. Then, an NMPC pitch controller was designed using the developed model for prediction. This was compared to another NMPC pitch controller which used a lumped-mass drive-train model as a prediction model and to the baseline gain-scheduled PI pitch controller.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:renene:v:161:y:2020:i:c:p:777-791
    DOI: 10.1016/j.renene.2020.07.094
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    References listed on IDEAS

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    1. 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.
    2. Zaragoza, Jordi & Pou, Josep & Arias, Antoni & Spiteri, Cyril & Robles, Eider & Ceballos, Salvador, 2011. "Study and experimental verification of control tuning strategies in a variable speed wind energy conversion system," Renewable Energy, Elsevier, vol. 36(5), pages 1421-1430.
    3. Odgaard, Peter Fogh & Larsen, Lars F.S. & Wisniewski, Rafael & Hovgaard, Tobias Gybel, 2016. "On using Pareto optimality to tune a linear model predictive controller for wind turbines," Renewable Energy, Elsevier, vol. 87(P2), pages 884-891.
    4. Duong, Minh Quan & Grimaccia, Francesco & Leva, Sonia & Mussetta, Marco & Ogliari, Emanuele, 2014. "Pitch angle control using hybrid controller for all operating regions of SCIG wind turbine system," Renewable Energy, Elsevier, vol. 70(C), pages 197-203.
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    Cited by:

    1. Song, Dongran & Tu, Yanping & Wang, Lei & Jin, Fangjun & Li, Ziqun & Huang, Chaoneng & Xia, E & Rizk-Allah, Rizk M. & Yang, Jian & Su, Mei & Hoon Joo, Young, 2022. "Coordinated optimization on energy capture and torque fluctuation of wind turbines via variable weight NMPC with fuzzy regulator," Applied Energy, Elsevier, vol. 312(C).
    2. Pustina, L. & Biral, F. & Serafini, J., 2022. "A novel Economic Nonlinear Model Predictive Controller for power maximisation on wind turbines," Renewable and Sustainable Energy Reviews, Elsevier, vol. 170(C).

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