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Enhanced Performance in PMSG-Based Wind Turbine Systems: Experimental Validation of Adaptive Backstepping Control Design

Author

Listed:
  • Youness El Mourabit

    (National School of Applied Sciences, Abdelmalek Essaadi University, Tetouan 93000, Morocco)

  • Hassna Salime

    (LISTA Laboratory, Faculty of Science Dhar El Mahraz-USMBA, Fez 30000, Morocco)

  • Badre Bossoufi

    (LISTA Laboratory, Faculty of Science Dhar El Mahraz-USMBA, Fez 30000, Morocco)

  • Saad Motahhir

    (Engineering, Systems and Applications Laboratory, ENSA, USMBA, Fez 30000, Morocco)

  • Aziz Derouich

    (Industrial Technologies and Services Laboratory, Higher School of Technology, Sidi Mohamed Ben Abdellah University, Fez 30000, Morocco)

  • Saleh Mobayen

    (Graduate School of Intelligent Data Science, National Yunlin University of Science and Technology, 123 University Road, Section 3, Douliou, Yunlin 640301, Taiwan)

  • Anton Zhilenkov

    (Department of Cyber-Physical Systems, St. Petersburg State Marine Technical University, 190121 Saint-Petersburg, Russia)

Abstract

Ensuring the quality and stability of the electrical grid is of utmost importance during the phase of electrical energy production. As wind energy plays an increasingly significant role in a country’s energy composition, maintaining stability and optimal quality has emerged as a prerequisite for the generated electricity. This article aims to devise a dynamic nonlinear algorithm that can be implemented in the wind energy conversion system (WECS) featuring a direct-drive permanent magnet synchronous generator (PMSG). Notably, the adaptive backstepping control relies on the nonlinear model of the controlled system. It harnesses the principles of the Lyapunov stability theory to regulate various parameters and uphold the overall system’s stability. Employing simulation analysis through the Matlab–Simulink environment, the proposed control strategy is evaluated using a 1.5 MW wind turbine. The results showcase the robust capability of the suggested control algorithm: it effectively maintains the DC bus voltage and produces high-quality electrical energy with a total harmonic distortion (THD) below 0.38%. Moreover, the algorithm demonstrates added resilience. The practical viability of the adaptive control algorithm is validated through an experimental study on the dSPACE DS1104 prototyping platform. This study underscores the algorithm’s proficiency in achieving all control objectives under diverse wind scenarios.

Suggested Citation

  • Youness El Mourabit & Hassna Salime & Badre Bossoufi & Saad Motahhir & Aziz Derouich & Saleh Mobayen & Anton Zhilenkov, 2023. "Enhanced Performance in PMSG-Based Wind Turbine Systems: Experimental Validation of Adaptive Backstepping Control Design," Energies, MDPI, vol. 16(22), pages 1-28, November.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:22:p:7481-:d:1275813
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    References listed on IDEAS

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    1. Jafarian, M. & Ranjbar, A.M., 2010. "Fuzzy modeling techniques and artificial neural networks to estimate annual energy output of a wind turbine," Renewable Energy, Elsevier, vol. 35(9), pages 2008-2014.
    2. Yang, Bo & Yu, Tao & Shu, Hongchun & Zhang, Yuming & Chen, Jian & Sang, Yiyan & Jiang, Lin, 2018. "Passivity-based sliding-mode control design for optimal power extraction of a PMSG based variable speed wind turbine," Renewable Energy, Elsevier, vol. 119(C), pages 577-589.
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