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Implementation of the Bio-Inspired Metaheuristic Firefly Algorithm (FA) Applied to Maximum Power Point Tracking of Photovoltaic Systems

Author

Listed:
  • Rodrigo Bairros Watanabe

    (University Center Dynamics of the Cataratas (UDC), Foz do Iguaçu 85867-000, PR, Brazil)

  • Oswaldo Hideo Ando Junior

    (Smart Grid Laboratory (LREI), Center for Alternative and Renewable Research (CEAR), Federal University of Paraiba (UFPB), João Pessoa 58051-900, PB, Brazil
    Academic Unit of Cabo de Santo Agostinho (UACSA), Federal Rural University of Pernambuco (UFRPE), Cabo de Santo Agostinho 54518-430, PE, Brazil)

  • Paulo Gabriel Martins Leandro

    (Smart Grid Laboratory (LREI), Center for Alternative and Renewable Research (CEAR), Federal University of Paraiba (UFPB), João Pessoa 58051-900, PB, Brazil)

  • Fabiano Salvadori

    (Smart Grid Laboratory (LREI), Center for Alternative and Renewable Research (CEAR), Federal University of Paraiba (UFPB), João Pessoa 58051-900, PB, Brazil)

  • Marlon Felipe Beck

    (University Center Dynamics of the Cataratas (UDC), Foz do Iguaçu 85867-000, PR, Brazil)

  • Katiane Pereira

    (University Center Dynamics of the Cataratas (UDC), Foz do Iguaçu 85867-000, PR, Brazil)

  • Marcelo Henrique Manzque Brandt

    (University Center Dynamics of the Cataratas (UDC), Foz do Iguaçu 85867-000, PR, Brazil)

  • Fernando Marcos de Oliveira

    (University Center Dynamics of the Cataratas (UDC), Foz do Iguaçu 85867-000, PR, Brazil)

Abstract

In this paper, an algorithm for the maximum extraction of energy generated by photovoltaic (PV) systems was presented. The tracking of the global maximum point of the system is complex due to the non-linearity of the current-voltage (I-V) characteristic curve of the photovoltaic modules, as they vary according to the temperature and solar irradiation in the module. To obtain the best energy efficiency in these systems, it is important that the generation is delivering the maximum power available through the arrangement. In order to solve such problems, in this work an efficient MPPT-FA method was proposed, which showed good traceability when compared to traditional methods. Most traditional MPPT techniques are not able to find the global maximum point to extract the maximum power provided by the PV system. Finally, the Firefly Metaheuristic MPPT method proved to be robust against several partial shading scenarios. Simulations were presented to demonstrate the effectiveness of the proposal when compared to the traditional MPPT-PO method.

Suggested Citation

  • Rodrigo Bairros Watanabe & Oswaldo Hideo Ando Junior & Paulo Gabriel Martins Leandro & Fabiano Salvadori & Marlon Felipe Beck & Katiane Pereira & Marcelo Henrique Manzque Brandt & Fernando Marcos de O, 2022. "Implementation of the Bio-Inspired Metaheuristic Firefly Algorithm (FA) Applied to Maximum Power Point Tracking of Photovoltaic Systems," Energies, MDPI, vol. 15(15), pages 1-15, July.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:15:p:5338-:d:869523
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    Citations

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    Cited by:

    1. Yonggang Wang & Shengnan Dai & Pinchi Liu & Xinyu Zhao, 2023. "A Hybrid Particle Swarm Optimization with Butterfly Optimization Algorithm Based Maximum Power Point Tracking for Photovoltaic Array under Partial Shading Conditions," Sustainability, MDPI, vol. 15(16), pages 1-21, August.
    2. Amit Kumar Sharma & Rupendra Kumar Pachauri & Sushabhan Choudhury & Ahmad Faiz Minai & Majed A. Alotaibi & Hasmat Malik & Fausto Pedro García Márquez, 2023. "Role of Metaheuristic Approaches for Implementation of Integrated MPPT-PV Systems: A Comprehensive Study," Mathematics, MDPI, vol. 11(2), pages 1-48, January.
    3. Naveed Ahmed Malik & Naveed Ishtiaq Chaudhary & Muhammad Asif Zahoor Raja, 2023. "Firefly Optimization Heuristics for Sustainable Estimation in Power System Harmonics," Sustainability, MDPI, vol. 15(6), pages 1-20, March.

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