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Accelerated Particle Swarm Optimization for Photovoltaic Maximum Power Point Tracking under Partial Shading Conditions

Author

Listed:
  • Muhannad Alshareef

    (Power Electronics, Machine and Power System Group, Aston University, Birmingham B4 7ET, UK)

  • Zhengyu Lin

    (Power Electronics, Machine and Power System Group, Aston University, Birmingham B4 7ET, UK)

  • Mingyao Ma

    (School of Electrical Engineering and Automation, Hefei University of Technology, Hefei 230009, China)

  • Wenping Cao

    (Power Electronics, Machine and Power System Group, Aston University, Birmingham B4 7ET, UK)

Abstract

This paper presents an accelerated particle swarm optimization (PSO)-based maximum power point tracking (MPPT) algorithm to track global maximum power point (MPP) of photovoltaic (PV) generation under partial shading conditions. Conventional PSO-based MPPT algorithms have common weaknesses of a long convergence time to reach the global MPP and oscillations during the searching. The proposed algorithm includes a standard PSO and a perturb-and-observe algorithm as the accelerator. It has been experimentally tested and compared with conventional MPPT algorithms. Experimental results show that the proposed MPPT method is effective in terms of high reliability, fast dynamic response, and high accuracy in tracking the global MPP.

Suggested Citation

  • Muhannad Alshareef & Zhengyu Lin & Mingyao Ma & Wenping Cao, 2019. "Accelerated Particle Swarm Optimization for Photovoltaic Maximum Power Point Tracking under Partial Shading Conditions," Energies, MDPI, vol. 12(4), pages 1-18, February.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:4:p:623-:d:206300
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    Citations

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    Cited by:

    1. Mohamed Derbeli & Cristian Napole & Oscar Barambones & Jesus Sanchez & Isidro Calvo & Pablo Fernández-Bustamante, 2021. "Maximum Power Point Tracking Techniques for Photovoltaic Panel: A Review and Experimental Applications," Energies, MDPI, vol. 14(22), pages 1-31, November.
    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. Chanuri Charin & Dahaman Ishak & Muhammad Ammirrul Atiqi Mohd Zainuri & Baharuddin Ismail & Turki Alsuwian & Adam R. H. Alhawari, 2022. "Modified Levy-based Particle Swarm Optimization (MLPSO) with Boost Converter for Local and Global Point Tracking," Energies, MDPI, vol. 15(19), pages 1-30, October.
    4. Grzegorz Trzmiel & Jaroslaw Jajczyk & Ewa Kardas-Cinal & Norbert Chamier-Gliszczynski & Waldemar Wozniak & Konrad Lewczuk, 2021. "The Condition of Photovoltaic Modules under Random Operation Parameters," Energies, MDPI, vol. 14(24), pages 1-18, December.
    5. Nihat Pamuk, 2023. "Performance Analysis of Different Optimization Algorithms for MPPT Control Techniques under Complex Partial Shading Conditions in PV Systems," Energies, MDPI, vol. 16(8), pages 1-25, April.
    6. Kuei-Hsiang Chao & Muhammad Nursyam Rizal, 2021. "A Hybrid MPPT Controller Based on the Genetic Algorithm and Ant Colony Optimization for Photovoltaic Systems under Partially Shaded Conditions," Energies, MDPI, vol. 14(10), pages 1-17, May.
    7. Imran Pervez & Charalampos Antoniadis & Yehia Massoud, 2022. "Advanced Limited Search Strategy for Enhancing the Performance of MPPT Algorithms," Energies, MDPI, vol. 15(15), pages 1-19, August.
    8. Manoharan Premkumar & Umashankar Subramaniam & Thanikanti Sudhakar Babu & Rajvikram Madurai Elavarasan & Lucian Mihet-Popa, 2020. "Evaluation of Mathematical Model to Characterize the Performance of Conventional and Hybrid PV Array Topologies under Static and Dynamic Shading Patterns," Energies, MDPI, vol. 13(12), pages 1-37, June.
    9. Saud Alotaibi & Ahmed Darwish, 2021. "Modular Multilevel Converters for Large-Scale Grid-Connected Photovoltaic Systems: A Review," Energies, MDPI, vol. 14(19), pages 1-30, September.
    10. Mariam A. Sameh & Mostafa I. Marei & M. A. Badr & Mahmoud A. Attia, 2021. "An Optimized PV Control System Based on the Emperor Penguin Optimizer," Energies, MDPI, vol. 14(3), pages 1-16, February.
    11. Fateh Mehazzem & Maina André & Rudy Calif, 2022. "Efficient Output Photovoltaic Power Prediction Based on MPPT Fuzzy Logic Technique and Solar Spatio-Temporal Forecasting Approach in a Tropical Insular Region," Energies, MDPI, vol. 15(22), pages 1-21, November.
    12. Ehab Mohamed Ali & Ahmed K. Abdelsalam & Karim H. Youssef & Ahmed A. Hossam-Eldin, 2021. "An Enhanced Cuckoo Search Algorithm Fitting for Photovoltaic Systems’ Global Maximum Power Point Tracking under Partial Shading Conditions," Energies, MDPI, vol. 14(21), pages 1-21, November.

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