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A Current Sensorless Control of Buck-Boost Converter for Maximum Power Point Tracking in Photovoltaic Applications

Author

Listed:
  • Nabil Obeidi

    (Laboratory of Electrical Engineering and Renewable Energies LGEER, Electrical Engineering Department, University of Hassiba Ben Bouali Chlef, Chlef 02000, Algeria)

  • Mostefa Kermadi

    (Power Electronics and Renewable Energy Research Laboratory (PEARL), Department of Electrical Engineering, University of Malaya, Kuala Lumpur 50603, Malaysia)

  • Bachir Belmadani

    (Laboratory of Electrical Engineering and Renewable Energies LGEER, Electrical Engineering Department, University of Hassiba Ben Bouali Chlef, Chlef 02000, Algeria)

  • Abdelkarim Allag

    (Electrical Engineering Department, University of Echahid Hamma Lakhdar El Oued, El-Oued 39000, Algeria)

  • Lazhar Achour

    (Electrical Engineering Department, University of Batna 2, Batna 05078, Algeria)

  • Saad Mekhilef

    (Power Electronics and Renewable Energy Research Laboratory (PEARL), Department of Electrical Engineering, University of Malaya, Kuala Lumpur 50603, Malaysia
    School of Science, Computing and Engineering Technologies, Swinburne University of Technology, Hawthorn, VIC 3122, Australia
    Department of Electrical Engineering, College of Engineering, Universiti Tenaga Nasional, Kajang 43000, Malaysia)

Abstract

In the present paper, a current sensorless (CSL) method for buck-boost converter control is proposed for maximum power point tracking (MPPT) photovoltaic applications. The proposed control scheme uses the mathematical model of the buck-boost converter to derive a predefined objective function for the MPPT control. The proposed scheme does not require any current sensor and relies only on the input voltage signal, which decreases the implementation cost. The proposed method is successfully implemented using a Matlab/Simulink/Stateflow environment, and its effectiveness is compared over the perturb and observe (P&O) method. An experimental rig, that includes a buck-boost converter, a PV simulator, and a resistive load, is used for the experimental validation. A rapid Arduino prototyping platform is used for the digital implementation, where the SAM3X8E microcontroller of the Arduino DUE board, which integrates an ARM Cortex-M3 MCU, is used as a target hardware for the proposed model-based controller developed under the Stateflow environment. Furthermore, the integrated pulse width modulation (PWM) macrocell is used to generate accurate PWM gate-drive signals for the buck-boost converter. Compared to the P&O, the presented simulation and experimental results show that the proposed method has reduced the computation burden and the sensor cost of implementation by 24.3%, and 27.95%, respectively.

Suggested Citation

  • Nabil Obeidi & Mostefa Kermadi & Bachir Belmadani & Abdelkarim Allag & Lazhar Achour & Saad Mekhilef, 2022. "A Current Sensorless Control of Buck-Boost Converter for Maximum Power Point Tracking in Photovoltaic Applications," Energies, MDPI, vol. 15(20), pages 1-21, October.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:20:p:7811-:d:949832
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    References listed on IDEAS

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    1. Achour, Lazhar & Bouharkat, Malek & Assas, Ouarda & Behar, Omar, 2017. "Hybrid model for estimating monthly global solar radiation for the Southern of Algeria: (Case study: Tamanrasset, Algeria)," Energy, Elsevier, vol. 135(C), pages 526-539.
    2. Yang Du & Ke Yan & Zixiao Ren & Weidong Xiao, 2018. "Designing Localized MPPT for PV Systems Using Fuzzy-Weighted Extreme Learning Machine," Energies, MDPI, vol. 11(10), pages 1-10, October.
    3. Ishaque, Kashif & Salam, Zainal & Shamsudin, Amir & Amjad, Muhammad, 2012. "A direct control based maximum power point tracking method for photovoltaic system under partial shading conditions using particle swarm optimization algorithm," Applied Energy, Elsevier, vol. 99(C), pages 414-422.
    4. Karami, Nabil & Moubayed, Nazih & Outbib, Rachid, 2017. "General review and classification of different MPPT Techniques," Renewable and Sustainable Energy Reviews, Elsevier, vol. 68(P1), pages 1-18.
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    Cited by:

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