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Design of a Robust Adaptive Controller for the Pitch and Torque Control of Wind Turbines

Author

Listed:
  • Srikanth Bashetty

    (Frank H. Dotterweich College of Engineering, Texas A&M University Kingsville, Kingsville, TX 78363, USA)

  • Joaquin I. Guillamon

    (Frank H. Dotterweich College of Engineering, Texas A&M University Kingsville, Kingsville, TX 78363, USA)

  • Shanmukha S. Mutnuri

    (Frank H. Dotterweich College of Engineering, Texas A&M University Kingsville, Kingsville, TX 78363, USA)

  • Selahattin Ozcelik

    (Frank H. Dotterweich College of Engineering, Texas A&M University Kingsville, Kingsville, TX 78363, USA)

Abstract

In this paper, robust adaptive control is designed for pitch and torque control of the wind turbines operating under turbulent wind conditions. The dynamics of the wind turbine are formulated by considering the five degrees of freedom system (rotor angle, gearbox angle, generator angle, flap-wise deflection of the rotor blade, and axial displacement of the nacelle). The controller is designed to maintain the rotor speed, maximize the aerodynamic efficiency of the wind turbine, and reduce the loads due to high wind speeds. Gaussian probability distribution function is used for approximating the wind speed, which is given as the disturbance input to the plant. The adaptive control algorithm is implemented to 2 MW and 5 MW wind turbines to test the robustness of the controller for varying parameters. The simulation is carried out using MATLAB/Simulink for three cases, namely pitch control, torque control, and the combined case. A case study is done to validate the proposed adaptive control using real wind speed data. In all the cases, the results indicate that the rotor speed follows the reference speed and show that the designed controller gives a satisfactory performance under varying operating conditions and parameter variations.

Suggested Citation

  • Srikanth Bashetty & Joaquin I. Guillamon & Shanmukha S. Mutnuri & Selahattin Ozcelik, 2020. "Design of a Robust Adaptive Controller for the Pitch and Torque Control of Wind Turbines," Energies, MDPI, vol. 13(5), pages 1-22, March.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:5:p:1195-:d:328752
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    References listed on IDEAS

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    1. Yancai Xiao & Yi Hong & Xiuhai Chen & Wenjian Huo, 2016. "Switching Control of Wind Turbine Sub-Controllers Based on an Active Disturbance Rejection Technique," Energies, MDPI, vol. 9(10), pages 1-19, October.
    2. 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.
    3. Aksoy, Hafzullah & Fuat Toprak, Z & Aytek, Ali & Erdem Ünal, N, 2004. "Stochastic generation of hourly mean wind speed data," Renewable Energy, Elsevier, vol. 29(14), pages 2111-2131.
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    Cited by:

    1. Amira Elkodama & Amr Ismaiel & A. Abdellatif & S. Shaaban & Shigeo Yoshida & Mostafa A. Rushdi, 2023. "Control Methods for Horizontal Axis Wind Turbines (HAWT): State-of-the-Art Review," Energies, MDPI, vol. 16(17), pages 1-32, September.
    2. Srikanth Bashetty & Selahattin Ozcelik, 2021. "Review on Dynamics of Offshore Floating Wind Turbine Platforms," Energies, MDPI, vol. 14(19), pages 1-30, September.
    3. José Antonio Cortajarena & Oscar Barambones & Patxi Alkorta & Jon Cortajarena, 2021. "Grid Frequency and Amplitude Control Using DFIG Wind Turbines in a Smart Grid," Mathematics, MDPI, vol. 9(2), pages 1-18, January.
    4. Md Rasel Sarkar & Sabariah Julai & Chong Wen Tong & Moslem Uddin & M.F. Romlie & GM Shafiullah, 2020. "Hybrid Pitch Angle Controller Approaches for Stable Wind Turbine Power under Variable Wind Speed," Energies, MDPI, vol. 13(14), pages 1-19, July.
    5. Xingkang Jin & Wen Tan & Yarong Zou & Zijian Wang, 2022. "Active Disturbance Rejection Control for Wind Turbine Fatigue Load," Energies, MDPI, vol. 15(17), pages 1-15, August.

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