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Design Procedure to Convert a Maximum Power Point Tracking Algorithm into a Loop Control System

Author

Listed:
  • Moacyr A. G. de Brito

    (Faculty of Engineering, Architecture and Urbanism and Geography, Federal University of Mato Grosso do Sul—UFMS, Campo Grande 79070-900, MS, Brazil)

  • Victor A. Prado

    (Faculty of Engineering, Architecture and Urbanism and Geography, Federal University of Mato Grosso do Sul—UFMS, Campo Grande 79070-900, MS, Brazil)

  • Edson A. Batista

    (Faculty of Engineering, Architecture and Urbanism and Geography, Federal University of Mato Grosso do Sul—UFMS, Campo Grande 79070-900, MS, Brazil)

  • Marcos G. Alves

    (Ningbo Institute of Technology, School of Computing and Data Engineering, Zhejiang University, Ningbo 315100, China)

  • Carlos A. Canesin

    (Faculty of Engineering, São Paulo State University—UNESP, Ilha Solteira 15385-000, SP, Brazil)

Abstract

This paper presents a novel complete design procedure to convert a maximum power point tracking (MPPT) algorithm into a control system. The MPPT algorithm can be tuned by employing any control system design. In this paper, we adopted Bode diagrams using the criteria of module and phase as the power electronics specialists are habituated with such concepts. The MPPT control transfer functions were derived using the average state equations and small-signal analysis. The control loops were derived for power and voltage control loops. The design procedure was applied to the well-known perturb and observe (P&O) and incremental conductance (IC) algorithms, returning the P&O based on PI and IC based on PI algorithms. Such algorithms were evaluated through simulation and experimental results. Additionally, we showed that the proposed design methodology can optimize energy harvesting, allowing algorithms to have outstanding tracking factors (above 99%) and adaptability characteristics.

Suggested Citation

  • Moacyr A. G. de Brito & Victor A. Prado & Edson A. Batista & Marcos G. Alves & Carlos A. Canesin, 2021. "Design Procedure to Convert a Maximum Power Point Tracking Algorithm into a Loop Control System," Energies, MDPI, vol. 14(15), pages 1-17, July.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:15:p:4550-:d:602654
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    References listed on IDEAS

    as
    1. Daraban, Stefan & Petreus, Dorin & Morel, Cristina, 2014. "A novel MPPT (maximum power point tracking) algorithm based on a modified genetic algorithm specialized on tracking the global maximum power point in photovoltaic systems affected by partial shading," Energy, Elsevier, vol. 74(C), pages 374-388.
    2. Tafticht, T. & Agbossou, K. & Doumbia, M.L. & Chériti, A., 2008. "An improved maximum power point tracking method for photovoltaic systems," Renewable Energy, Elsevier, vol. 33(7), pages 1508-1516.
    3. Li, Xingshuo & Wen, Huiqing & Hu, Yihua & Jiang, Lin, 2019. "A novel beta parameter based fuzzy-logic controller for photovoltaic MPPT application," Renewable Energy, Elsevier, vol. 130(C), pages 416-427.
    4. Hyeon-Seok Lee & Jae-Jung Yun, 2019. "Advanced MPPT Algorithm for Distributed Photovoltaic Systems," Energies, MDPI, vol. 12(18), pages 1-17, September.
    5. Kofinas, P. & Doltsinis, S. & Dounis, A.I. & Vouros, G.A., 2017. "A reinforcement learning approach for MPPT control method of photovoltaic sources," Renewable Energy, Elsevier, vol. 108(C), pages 461-473.
    6. Sivakumar, P. & Abdul Kader, Abdullah & Kaliavaradhan, Yogeshraj & Arutchelvi, M., 2015. "Analysis and enhancement of PV efficiency with incremental conductance MPPT technique under non-linear loading conditions," Renewable Energy, Elsevier, vol. 81(C), pages 543-550.
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