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Analysis and design of an adaptive turbulence-based controller for wind turbines

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  • Dong, Liang
  • Lio, Wai Hou
  • Pirrung, Georg Raimund

Abstract

This work aims to explore methods to retain the robustness and performance of a wind turbine controller under different wind conditions. A method of optimizing the control parameters in response to different turbulence intensity is proposed, which is referred to as adaptive turbulence-based control (ATBC). Specifically, the power spectrum of the rotor effective wind speed has been derived and the analytical expression is explicitly considered in the control optimization. Also, a linear aero-servo-elastic (ASE) model is established, which captures the closed-loop dynamics of the rotor speed, pitch activity and tower fore-aft vibration mode. Subsequently, a computationally-efficient component damage prediction method is proposed that uses rainflow counting and inverse fast Fourier transform. Based on the proposed ASE model and damage prediction method, the controller optimization problem is established using a quadratic cost function to achieve the optimal trade-off between the rotor speed variation and the damage of turbine components. A model validation shows that the proposed scheme is able to predict the component fatigue load and the rotor speed variation in an efficient way. Finally, one design case is given to illustrate the procedure of ATBC and to demonstrate the feasibility of the proposed method in different operating wind conditions.

Suggested Citation

  • Dong, Liang & Lio, Wai Hou & Pirrung, Georg Raimund, 2021. "Analysis and design of an adaptive turbulence-based controller for wind turbines," Renewable Energy, Elsevier, vol. 178(C), pages 730-744.
    • Handle: RePEc:eee:renene:v:178:y:2021:i:c:p:730-744
    DOI: 10.1016/j.renene.2021.06.080
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    References listed on IDEAS

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    1. Jena, Debashisha & Rajendran, Saravanakumar, 2015. "A review of estimation of effective wind speed based control of wind turbines," Renewable and Sustainable Energy Reviews, Elsevier, vol. 43(C), pages 1046-1062.
    2. Göçmen, Tuhfe & Giebel, Gregor, 2016. "Estimation of turbulence intensity using rotor effective wind speed in Lillgrund and Horns Rev-I offshore wind farms," Renewable Energy, Elsevier, vol. 99(C), pages 524-532.
    3. Abdallah, I. & Natarajan, A. & Sørensen, J.D., 2016. "Influence of the control system on wind turbine loads during power production in extreme turbulence: Structural reliability," Renewable Energy, Elsevier, vol. 87(P1), pages 464-477.
    4. Xiao Chen & Martin A. Eder & Asm Shihavuddin & Dan Zheng, 2021. "A Human-Cyber-Physical System toward Intelligent Wind Turbine Operation and Maintenance," Sustainability, MDPI, vol. 13(2), pages 1-10, January.
    5. Lio, Wai Hou & Li, Ang & Meng, Fanzhong, 2021. "Real-time rotor effective wind speed estimation using Gaussian process regression and Kalman filtering," Renewable Energy, Elsevier, vol. 169(C), pages 670-686.
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