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Pitch Actuator Fault-Tolerant Control of Wind Turbines via an L 1 Adaptive Sliding Mode Control ( SMC ) Scheme

Author

Listed:
  • Ali Fayazi

    (Department of Electrical Engineering, Vali-e-Asr University of Rafsanjan, Rafsanjan 7718897111, Iran)

  • Hossein Ghayoumi Zadeh

    (Department of Electrical Engineering, Vali-e-Asr University of Rafsanjan, Rafsanjan 7718897111, Iran)

  • Hossein Ahmadian

    (Department of Electrical Engineering, Amirkabir University of Technology, Tehran 1591634311, Iran)

  • Mahdi Ghane

    (Department of Computer Science, Electrical Engineering and Mathematical Sciences, Western Norway University of Applied Sciences, 5528 Haugesund, Norway)

  • Omid Rahmani Seryasat

    (Department of Electrical Engineering, Shams Gonbad Higher Education Institute, Gorgan 4971817615, Iran)

Abstract

Effective fault identification and management are critical for efficient wind turbine operation. This research presents a novel L 1 adaptive- SMC system designed to enhance fault tolerance in wind turbines, specifically addressing common issues such as pump wear, hydraulic leakage, and excessive air content in the oil. By combining SMC with L 1 adaptive control, the proposed technique effectively controls rotor speed and power, ensuring reliable performance under various conditions. The controller employs an adjustable gain and an integrated sliding surface to maintain robustness. We validate the controller’s performance in the FAST (Fatigue, Aerodynamics, Structures, and Turbulence) simulation environment using a 5-megawatt wind turbine under high wind speeds. Simulation results demonstrate that the proposed L 1 adaptive- SMC outperforms traditional adaptive- SMC and adaptive control schemes, particularly in the presence of faults, unknown disturbances, and turbulent wind fields. This research highlights the controller’s potential to significantly improve the reliability and efficiency of wind turbine operations.

Suggested Citation

  • Ali Fayazi & Hossein Ghayoumi Zadeh & Hossein Ahmadian & Mahdi Ghane & Omid Rahmani Seryasat, 2024. "Pitch Actuator Fault-Tolerant Control of Wind Turbines via an L 1 Adaptive Sliding Mode Control ( SMC ) Scheme," Energies, MDPI, vol. 17(16), pages 1-20, August.
    • Handle: RePEc:gam:jeners:v:17:y:2024:i:16:p:3963-:d:1453480
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    References listed on IDEAS

    as
    1. Gisela Pujol-Vazquez & Leonardo Acho & José Gibergans-Báguena, 2020. "Fault Detection Algorithm for Wind Turbines’ Pitch Actuator Systems," Energies, MDPI, vol. 13(11), pages 1-14, June.
    2. 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.
    3. Zuojun Liu & Cheng Xiao & Tieling Zhang & Xu Zhang, 2020. "Research on Fault Detection for Three Types of Wind Turbine Subsystems Using Machine Learning," Energies, MDPI, vol. 13(2), pages 1-21, January.
    4. Farahani, E.M. & Hosseinzadeh, N. & Ektesabi, M., 2012. "Comparison of fault-ride-through capability of dual and single-rotor wind turbines," Renewable Energy, Elsevier, vol. 48(C), pages 473-481.
    5. A. G. Olabi & Khaled Obaideen & Mohammad Ali Abdelkareem & Maryam Nooman AlMallahi & Nabila Shehata & Abdul Hai Alami & Ayman Mdallal & Asma Ali Murah Hassan & Enas Taha Sayed, 2023. "Wind Energy Contribution to the Sustainable Development Goals: Case Study on London Array," Sustainability, MDPI, vol. 15(5), pages 1-22, March.
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