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Analysis and synthesis of sliding mode control for large scale variable speed wind turbine for power optimization

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  • Mérida, Jován
  • Aguilar, Luis T.
  • Dávila, Jorge

Abstract

The problem of designing a nonlinear feedback control scheme for variable speed wind turbines, without wind speed measurements, in below rated wind conditions was addressed. The objective is to operate the wind turbines in order to have maximum wind power extraction while also the mechanical loads are reduced. Two control strategies were proposed seeking a better performance. The first strategy uses a tracking controller that ensures the optimal angular velocity for the rotor. The second strategy uses a Maximum Power Point Tracking (MPPT) algorithm while a non-homogeneous quasi-continuous high-order sliding mode controller is applied to ensure the power tracking. Two algorithms were developed to solve the tracking control problem for the first strategy. The first one is a sliding mode output feedback torque controller combined with a wind speed estimator. The second algorithm is a quasi-continuous high-order sliding mode controller to ensure the speed tracking. The proposed controllers are compared with existing control strategies and their performance is validated using a FAST model based on the Controls Advanced Research Turbine (CART). The controllers show a good performance in terms of energy extraction and load reduction.

Suggested Citation

  • Mérida, Jován & Aguilar, Luis T. & Dávila, Jorge, 2014. "Analysis and synthesis of sliding mode control for large scale variable speed wind turbine for power optimization," Renewable Energy, Elsevier, vol. 71(C), pages 715-728.
    • Handle: RePEc:eee:renene:v:71:y:2014:i:c:p:715-728
    DOI: 10.1016/j.renene.2014.06.030
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    References listed on IDEAS

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    1. Abdullah, M.A. & Yatim, A.H.M. & Tan, C.W. & Saidur, R., 2012. "A review of maximum power point tracking algorithms for wind energy systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(5), pages 3220-3227.
    2. Boukhezzar, B. & Lupu, L. & Siguerdidjane, H. & Hand, M., 2007. "Multivariable control strategy for variable speed, variable pitch wind turbines," Renewable Energy, Elsevier, vol. 32(8), pages 1273-1287.
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    2. Yanwei Jing & Hexu Sun & Lei Zhang & Tieling Zhang, 2017. "Variable Speed Control of Wind Turbines Based on the Quasi-Continuous High-Order Sliding Mode Method," Energies, MDPI, vol. 10(10), pages 1-21, October.
    3. Yin, Xiuxing & Zhao, Xiaowei & Lin, Jin & Karcanias, Aris, 2020. "Reliability aware multi-objective predictive control for wind farm based on machine learning and heuristic optimizations," Energy, Elsevier, vol. 202(C).
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    9. Mousavi, Yashar & Bevan, Geraint & Kucukdemiral, Ibrahim Beklan & Fekih, Afef, 2022. "Sliding mode control of wind energy conversion systems: Trends and applications," Renewable and Sustainable Energy Reviews, Elsevier, vol. 167(C).
    10. Zhikun Luo & Zhifeng Sun & Fengli Ma & Yihan Qin & Shihao Ma, 2020. "Power Optimization for Wind Turbines Based on Stacking Model and Pitch Angle Adjustment," Energies, MDPI, vol. 13(16), pages 1-15, August.
    11. Wang, Feng & Chen, Jincheng & Xu, Bing & Stelson, Kim A., 2019. "Improving the reliability and energy production of large wind turbine with a digital hydrostatic drivetrain," Applied Energy, Elsevier, vol. 251(C), pages 1-1.
    12. Abolvafaei, Mahnaz & Ganjefar, Soheil, 2020. "Maximum power extraction from wind energy system using homotopy singular perturbation and fast terminal sliding mode method," Renewable Energy, Elsevier, vol. 148(C), pages 611-626.
    13. Hongfu Zhang & Jiahao Wen & Farshad Golnary & Lei Zhou, 2022. "Output Power Control and Load Mitigation of a Horizontal Axis Wind Turbine with a Fully Coupled Aeroelastic Model: Novel Sliding Mode Perspective," Mathematics, MDPI, vol. 10(15), pages 1-40, August.
    14. Golnary, Farshad & Moradi, Hamed, 2018. "Design and comparison of quasi continuous sliding mode control with feedback linearization for a large scale wind turbine with wind speed estimation," Renewable Energy, Elsevier, vol. 127(C), pages 495-508.

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