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Improvement of PMSG-Based Wind Energy Conversion System Using Developed Sliding Mode Control

Author

Listed:
  • Btissam Majout

    (LIMAS Laboratory, Faculty of Sciences Dhar El Mahraz, Sidi Mohammed Ben Abdellah University, Fez 30000, Morocco)

  • Badre Bossoufi

    (LIMAS Laboratory, Faculty of Sciences Dhar El Mahraz, Sidi Mohammed Ben Abdellah University, Fez 30000, Morocco)

  • Manale Bouderbala

    (LIMAS Laboratory, Faculty of Sciences Dhar El Mahraz, Sidi Mohammed Ben Abdellah University, Fez 30000, Morocco)

  • Mehedi Masud

    (Department of Computer Science, College of Computers and Information Technology, Taif University, P.O. Box 11099, Taif 21944, Saudi Arabia)

  • Jehad F. Al-Amri

    (Department of Information Technology, College of Computers and Information Technology, Taif University, P.O. Box 11099, Taif 21944, Saudi Arabia)

  • Mohammed Taoussi

    (LIMAS Laboratory, Faculty of Sciences Dhar El Mahraz, Sidi Mohammed Ben Abdellah University, Fez 30000, Morocco)

  • Mohammed El Mahfoud

    (LIMAS Laboratory, Faculty of Sciences Dhar El Mahraz, Sidi Mohammed Ben Abdellah University, Fez 30000, Morocco)

  • Saad Motahhir

    (Engineering, Systems and Applications Laboratory, ENSA, Sidi Mohammed Ben Abdellah University, Fez 30000, Morocco)

  • Mohammed Karim

    (LIMAS Laboratory, Faculty of Sciences Dhar El Mahraz, Sidi Mohammed Ben Abdellah University, Fez 30000, Morocco)

Abstract

In recent years, regulating a wind energy conversion system (WECS) under fluctuating wind speed and enhancing the quality of the electricity provided to the grid has become a hard challenge for many academics. The current research provides a better control strategy to decrease the occurrence of chattering phenomena. Combined with the Maximum Power Point Tracking (MPPT) strategy and a pitch angle control, the control is possible to increase the performance and the efficiency of the Permanent Magnet Synchronous Generator (PMSG) based Wind Energy Conversion System. This study attempts initially to regulate the generator and the grid side converter to track the wind speed reference established by the MPPT algorithm. And secondly, to relieve the chattering problem associated with the conventional sliding mode control (CSMC), the proposed sliding mode control (PSMC) is based on a novel smooth continuous switching control. Besides, the suggested sliding mode control stability is confirmed using Lyapunov’s stability function. The complete system was evaluated in the MATLAB/Simulink (MathWorks, Natick, MA, USA) environment using a 2 MW PMSG’s power, under random fluctuations in the wind speed to show the suggested approach’s efficiency and robustness, which was then compared to the CSMC and other common approaches available in the literature. The simulation results reveal that the recommended sliding mode control approach delivers good speed, accuracy, stability, and output current’s ripple.

Suggested Citation

  • Btissam Majout & Badre Bossoufi & Manale Bouderbala & Mehedi Masud & Jehad F. Al-Amri & Mohammed Taoussi & Mohammed El Mahfoud & Saad Motahhir & Mohammed Karim, 2022. "Improvement of PMSG-Based Wind Energy Conversion System Using Developed Sliding Mode Control," Energies, MDPI, vol. 15(5), pages 1-17, February.
  • Handle: RePEc:gam:jeners:v:15:y:2022:i:5:p:1625-:d:755665
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    References listed on IDEAS

    as
    1. Yin, Xiu-xing & Lin, Yong-gang & Li, Wei & Gu, Ya-jing & Liu, Hong-wei & Lei, Peng-fei, 2015. "A novel fuzzy integral sliding mode current control strategy for maximizing wind power extraction and eliminating voltage harmonics," Energy, Elsevier, vol. 85(C), pages 677-686.
    2. Jaramillo-Lopez, Fernando & Kenne, Godpromesse & Lamnabhi-Lagarrigue, Francoise, 2016. "A novel online training neural network-based algorithm for wind speed estimation and adaptive control of PMSG wind turbine system for maximum power extraction," Renewable Energy, Elsevier, vol. 86(C), pages 38-48.
    3. Mohamed Zribi & Muthana Alrifai & Mohamed Rayan, 2017. "Sliding Mode Control of a Variable- Speed Wind Energy Conversion System Using a Squirrel Cage Induction Generator," Energies, MDPI, vol. 10(5), pages 1-21, May.
    4. Pan, Lin & Shao, Chengpeng, 2020. "Wind energy conversion systems analysis of PMSG on offshore wind turbine using improved SMC and Extended State Observer," Renewable Energy, Elsevier, vol. 161(C), pages 149-161.
    5. Bossoufi, Badre & Karim, Mohammed & Lagrioui, Ahmed & Taoussi, Mohammed & Derouich, Aziz, 2015. "Observer backstepping control of DFIG-Generators for wind turbines variable-speed: FPGA-based implementation," Renewable Energy, Elsevier, vol. 81(C), pages 903-917.
    6. González, L.G. & Figueres, E. & Garcerá, G. & Carranza, O., 2010. "Maximum-power-point tracking with reduced mechanical stress applied to wind-energy-conversion-systems," Applied Energy, Elsevier, vol. 87(7), pages 2304-2312, July.
    7. Yang, Bo & Yu, Tao & Shu, Hongchun & Dong, Jun & Jiang, Lin, 2018. "Robust sliding-mode control of wind energy conversion systems for optimal power extraction via nonlinear perturbation observers," Applied Energy, Elsevier, vol. 210(C), pages 711-723.
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    Cited by:

    1. Lu Liu & Yun Zeng, 2023. "Intelligent ISSA-Based Non-Singular Terminal Sliding-Mode Control of DC–DC Boost Converter Feeding a Constant Power Load System," Energies, MDPI, vol. 16(13), pages 1-23, June.
    2. Hamza Assia & Houari Merabet Boulouiha & William David Chicaiza & Juan Manuel Escaño & Abderrahmane Kacimi & José Luis Martínez-Ramos & Mouloud Denai, 2023. "Wind Turbine Active Fault Tolerant Control Based on Backstepping Active Disturbance Rejection Control and a Neurofuzzy Detector," Energies, MDPI, vol. 16(14), pages 1-22, July.
    3. Btissam Majout & Houda El Alami & Hassna Salime & Nada Zine Laabidine & Youness El Mourabit & Saad Motahhir & Manale Bouderbala & Mohammed Karim & Badre Bossoufi, 2022. "A Review on Popular Control Applications in Wind Energy Conversion System Based on Permanent Magnet Generator PMSG," Energies, MDPI, vol. 15(17), pages 1-41, August.
    4. Anto Anbarasu Yesudhas & Young Hoon Joo & Seong Ryong Lee, 2022. "Reference Model Adaptive Control Scheme on PMVG-Based WECS for MPPT under a Real Wind Speed," Energies, MDPI, vol. 15(9), pages 1-17, April.

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