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Robust Finite Control-Set Model Predictive Control for Power Quality Enhancement of a Wind System Based on the DFIG Generator

Author

Listed:
  • Houda El Alami

    (Faculty of Sciences Dhar El Mahraz, Sidi Mohammed Ben Abdellah University, Fez 30070, Morocco)

  • Badre Bossoufi

    (Faculty of Sciences Dhar El Mahraz, Sidi Mohammed Ben Abdellah University, Fez 30070, Morocco)

  • Mohammed El Mahfoud

    (Faculty of Sciences Dhar El Mahraz, Sidi Mohammed Ben Abdellah University, Fez 30070, Morocco)

  • Manale Bouderbala

    (Faculty of Sciences Dhar El Mahraz, Sidi Mohammed Ben Abdellah University, Fez 30070, Morocco)

  • Btissam Majout

    (Faculty of Sciences Dhar El Mahraz, Sidi Mohammed Ben Abdellah University, Fez 30070, Morocco)

  • Paweł Skruch

    (Department of Automatic Control and Robotics, AGH University of Science and Technology, 30-059 Kraków, Poland)

  • Saleh Mobayen

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

Abstract

For many academics, it has proven difficult to operate a wind energy conversion system (WECS) under changeable wind speed while also enhancing the quality of the electricity delivered to the grid. In order to increase the effectiveness and performance of the DFIG-based Wind Energy Conversion System, this research suggests an updated model predictive control technique. This study intends to regulate the generator in two ways: first, to follow the reference wind speed with high precision using the rotor side and grid side converters; second, to reduce system error. The suggested approach optimizes a value function with current magnitude errors based on the discrete mathematical model to forecast the converter’s switching state. In this system, the converter switching states are used directly as control inputs. Thus, the converter may be immediately subjected to improved control action. The key advantage of the suggested strategy over current FCS-MPC methods is error reduction. The originality of this research is in the proposal of a cost function that allows for both successful results and computation time minimization. To achieve this, the system is first presented, followed by a description of the predictive control, and then this method is applied to the rotor side control and grid side control. To demonstrate the efficacy and robustness of the suggested technique, a random wind profile was used to examine the system’s performance with a unitary power factor. This was done in order to compare the results with other controls that have been reported in the literature. The simulation results, which were conducted using a 1.5 kW DFIG in the MATLAB/Simulink environment, demonstrate that the FCS-MPC technique is highly effective in terms of speed, accuracy, stability, and output current ripple.

Suggested Citation

  • Houda El Alami & Badre Bossoufi & Mohammed El Mahfoud & Manale Bouderbala & Btissam Majout & Paweł Skruch & Saleh Mobayen, 2023. "Robust Finite Control-Set Model Predictive Control for Power Quality Enhancement of a Wind System Based on the DFIG Generator," Energies, MDPI, vol. 16(3), pages 1-15, February.
  • Handle: RePEc:gam:jeners:v:16:y:2023:i:3:p:1422-:d:1053508
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    References listed on IDEAS

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    1. 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.
    2. Hansen, Anca D. & Michalke, Gabriele, 2007. "Fault ride-through capability of DFIG wind turbines," Renewable Energy, Elsevier, vol. 32(9), pages 1594-1610.
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