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A New Model Predictive Control Method for Buck-Boost Inverter-Based Photovoltaic Systems

Author

Listed:
  • Saeed Danyali

    (Department of Electrical Engineering, Ilam University, Ilam 6931647574, Iran)

  • Omid Aghaei

    (Department of Electrical Engineering, Ilam University, Ilam 6931647574, Iran)

  • Mohammadamin Shirkhani

    (Department of Electrical Engineering, Ilam University, Ilam 6931647574, Iran)

  • Rahmat Aazami

    (Department of Electrical Engineering, Ilam University, Ilam 6931647574, Iran)

  • Jafar Tavoosi

    (Department of Electrical Engineering, Ilam University, Ilam 6931647574, Iran)

  • Ardashir Mohammadzadeh

    (Multidisciplinary Center for Infrastructure Engineering, Shenyang University of Technology, Shenyang 110870, China)

  • Amir Mosavi

    (Faculty of Civil Engineering, Technische Universität Dresden, 01067 Dresden, Germany
    John von Neumann Faculty of Informatics, Obuda University, 1034 Budapest, Hungary
    Institute of Information Engineering, Automation and Mathematics, Slovak University of Technology in Bratislava, 81107 Bratislava, Slovakia)

Abstract

This study designed a system consisting of a photovoltaic system and a DC-DC boost converter with buck-boost inverter. A multi-error method, based on model predictive control (MPC), is presented for control of the buck-boost inverter. Incremental conductivity and predictive control methods have also been used to track the maximum power of the photovoltaic system. Due to the fact that inverters are in the category of systems with fast dynamics, in this method, by first determining the system state space and its discrete time model, a switching algorithm is proposed to reduce the larger error for the converter. By using this control method, in addition to reducing the total harmonic distortion (THD), the inverter voltage reaches the set reference value at a high speed. To evaluate the performance of the proposed method, the dynamic performance of the converter at the reference voltage given to the system was investigated. The results of system performance in SIMULINK environment were simulated and analyzed by MATLAB software. According to the simulation results, we can point out the advantage of this system in following the reference signal with high speed and accuracy.

Suggested Citation

  • Saeed Danyali & Omid Aghaei & Mohammadamin Shirkhani & Rahmat Aazami & Jafar Tavoosi & Ardashir Mohammadzadeh & Amir Mosavi, 2022. "A New Model Predictive Control Method for Buck-Boost Inverter-Based Photovoltaic Systems," Sustainability, MDPI, vol. 14(18), pages 1-14, September.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:18:p:11731-:d:918523
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    References listed on IDEAS

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    1. Alessandro Palmieri & Alessandro Rosini & Renato Procopio & Andrea Bonfiglio, 2020. "An MPC-Sliding Mode Cascaded Control Architecture for PV Grid-Feeding Inverters," Energies, MDPI, vol. 13(9), pages 1-17, May.
    2. Haidar Islam & Saad Mekhilef & Noraisyah Binti Mohamed Shah & Tey Kok Soon & Mehdi Seyedmahmousian & Ben Horan & Alex Stojcevski, 2018. "Performance Evaluation of Maximum Power Point Tracking Approaches and Photovoltaic Systems," Energies, MDPI, vol. 11(2), pages 1-24, February.
    3. Haifeng Huang & Mohammadamin Shirkhani & Jafar Tavoosi & Omar Mahmoud, 2022. "A New Intelligent Dynamic Control Method for a Class of Stochastic Nonlinear Systems," Mathematics, MDPI, vol. 10(9), pages 1-15, April.
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    Cited by:

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    4. Humam Al-Baidhani & Abdullah Sahib & Marian K. Kazimierczuk, 2023. "State Feedback with Integral Control Circuit Design of DC-DC Buck-Boost Converter," Mathematics, MDPI, vol. 11(9), pages 1-18, May.
    5. Arun Kumar Udayakumar & Raghavendra Rajan Vijaya Raghavan & Mohamad Abou Houran & Rajvikram Madurai Elavarasan & Anushkannan Nedumaran Kalavathy & Eklas Hossain, 2023. "Three-Port Bi-Directional DC–DC Converter with Solar PV System Fed BLDC Motor Drive Using FPGA," Energies, MDPI, vol. 16(2), pages 1-21, January.
    6. Weijun Hu & Jiale Quan & Xianlong Ma & Mostafa M. Salah & Ahmed Shaker, 2023. "Analytical Design of Optimal Model Predictive Control and Its Application in Small-Scale Helicopters," Mathematics, MDPI, vol. 11(8), pages 1-15, April.

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