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Hybrid maximum power point tracking algorithm with improved dynamic performance

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  • Bahrami, Milad
  • Gavagsaz-Ghoachani, Roghayeh
  • Zandi, Majid
  • Phattanasak, Matheepot
  • Maranzanaa, Gaël
  • Nahid-Mobarakeh, Babak
  • Pierfederici, Serge
  • Meibody-Tabar, Farid

Abstract

In light of the low efficiency of photovoltaic (PV) panels and varying environmental conditions, it is necessary to develop methods for maximum power extraction of PV panels in any environmental conditions. Here, a new hybrid method is proposed for maximum power point tracking (MPPT). The fuzzy logic control-based method is very fast and accurate but difficult to implement. In addition, this method depends on PV arrays. The three-point weight method is another MPPT method that does not compromise on the maximum power point under fast transient conditions. The advantages of both methods are utilized in the proposed method. Furthermore, the overall complexity is decreased by simplifying the fuzzy logic part. The three methods were experimentally validated and, in addition, were numerically simulated in Matlab.

Suggested Citation

  • Bahrami, Milad & Gavagsaz-Ghoachani, Roghayeh & Zandi, Majid & Phattanasak, Matheepot & Maranzanaa, Gaël & Nahid-Mobarakeh, Babak & Pierfederici, Serge & Meibody-Tabar, Farid, 2019. "Hybrid maximum power point tracking algorithm with improved dynamic performance," Renewable Energy, Elsevier, vol. 130(C), pages 982-991.
    • Handle: RePEc:eee:renene:v:130:y:2019:i:c:p:982-991
    DOI: 10.1016/j.renene.2018.07.020
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    2. Rezk, Hegazy & AL-Oran, Mazen & Gomaa, Mohamed R. & Tolba, Mohamed A. & Fathy, Ahmed & Abdelkareem, Mohammad Ali & Olabi, A.G. & El-Sayed, Abou Hashema M., 2019. "A novel statistical performance evaluation of most modern optimization-based global MPPT techniques for partially shaded PV system," Renewable and Sustainable Energy Reviews, Elsevier, vol. 115(C).
    3. Bahrami, Milad & Martin, Jean-Philippe & Maranzana, Gaël & Pierfederici, Serge & Weber, Mathieu & Didierjean, Sophie, 2022. "Fuel cell management system: An approach to increase its durability," Applied Energy, Elsevier, vol. 306(PB).
    4. Milad Bahrami & Jean-Philippe Martin & Gaël Maranzana & Serge Pierfederici & Mathieu Weber & Farid Meibody-Tabar & Majid Zandi, 2020. "Multi-Stack Lifetime Improvement through Adapted Power Electronic Architecture in a Fuel Cell Hybrid System," Mathematics, MDPI, vol. 8(5), pages 1-28, May.
    5. Baldwin Cortés & Roberto Tapia & Juan J. Flores, 2021. "System-Independent Irradiance Sensorless ANN-Based MPPT for Photovoltaic Systems in Electric Vehicles," Energies, MDPI, vol. 14(16), pages 1-18, August.
    6. Abdelilah Chalh & Aboubakr El Hammoumi & Saad Motahhir & Abdelaziz El Ghzizal & Umashankar Subramaniam & Aziz Derouich, 2020. "Trusted Simulation Using Proteus Model for a PV System: Test Case of an Improved HC MPPT Algorithm," Energies, MDPI, vol. 13(8), pages 1-12, April.
    7. Bizon, Nicu & Pierfederici, Serge & Bahrami, Milad & Thounthong, Phatiphat, 2022. "Power equalizer for a series fuel cell architecture based on load tracking control," Renewable and Sustainable Energy Reviews, Elsevier, vol. 166(C).
    8. Eduardo Manuel Godinho Rodrigues & Radu Godina & Mousa Marzband & Edris Pouresmaeil, 2018. "Simulation and Comparison of Mathematical Models of PV Cells with Growing Levels of Complexity," Energies, MDPI, vol. 11(11), pages 1-21, October.

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