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A review of maximum power point tracking methods of PV power system at uniform and partial shading

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  • Liu, Liqun
  • Meng, Xiaoli
  • Liu, Chunxia

Abstract

The maximum power point tracking (MPPT) methods for the photovoltaic (PV) power system have been considered by the experts in the whole world. A review of different MPPT methods is discussed in this paper. Firstly, the main methods at uniform radiation that will be deliberated are Hill-Climbing (HC), Incremental Conductance (IncCond), Perturbation and Observation (P&O), Fuzzy-Logic (FL), and Neural Network (NN). However, these existing methods have several drawbacks such as slow tracking speed, low tracking efficiency, which fail to extract maximum power at complex partial shading. Then, the more recent MPPT methods at partial shading are discussed to find the best MPPT control strategy, such as the particle swarm optimization (PSO) algorithm, Cuckoo Search (CS) method, and Fibonacci line search scheme, etc. The advantages and shortcomings of abovementioned MPPT methods are compared to find the optimal MPPT during partial shading conditions. It is imagined that this article will be a source of valuable information for PV professionals to keep abreast with the latest progress in the PV power area, as well as for new researchers to get started on MPPT.

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  • Liu, Liqun & Meng, Xiaoli & Liu, Chunxia, 2016. "A review of maximum power point tracking methods of PV power system at uniform and partial shading," Renewable and Sustainable Energy Reviews, Elsevier, vol. 53(C), pages 1500-1507.
    • Handle: RePEc:eee:rensus:v:53:y:2016:i:c:p:1500-1507
    DOI: 10.1016/j.rser.2015.09.065
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    6. Yu-Pei Huang & Cheng-En Ye & Xiang Chen, 2018. "A Modified Firefly Algorithm with Rapid Response Maximum Power Point Tracking for Photovoltaic Systems under Partial Shading Conditions," Energies, MDPI, vol. 11(9), pages 1-33, August.
    7. Camilo, Jones C. & Guedes, Tatiana & Fernandes, Darlan A. & Melo, J.D. & Costa, F.F. & Sguarezi Filho, Alfeu J., 2019. "A maximum power point tracking for photovoltaic systems based on Monod equation," Renewable Energy, Elsevier, vol. 130(C), pages 428-438.
    8. Osmani, Khaled & Haddad, Ahmad & Lemenand, Thierry & Castanier, Bruno & Ramadan, Mohamad, 2021. "An investigation on maximum power extraction algorithms from PV systems with corresponding DC-DC converters," Energy, Elsevier, vol. 224(C).
    9. Amjad Ali & Kashif Irshad & Mohammad Farhan Khan & Md Moinul Hossain & Ibrahim N. A. Al-Duais & Muhammad Zeeshan Malik, 2021. "Artificial Intelligence and Bio-Inspired Soft Computing-Based Maximum Power Plant Tracking for a Solar Photovoltaic System under Non-Uniform Solar Irradiance Shading Conditions—A Review," Sustainability, MDPI, vol. 13(19), pages 1-26, September.
    10. Sheik Mohammed, S. & Devaraj, D. & Imthias Ahamed, T.P., 2016. "A novel hybrid Maximum Power Point Tracking Technique using Perturb & Observe algorithm and Learning Automata for solar PV system," Energy, Elsevier, vol. 112(C), pages 1096-1106.
    11. Başoğlu, Mustafa Engin & Çakır, Bekir, 2016. "Comparisons of MPPT performances of isolated and non-isolated DC–DC converters by using a new approach," Renewable and Sustainable Energy Reviews, Elsevier, vol. 60(C), pages 1100-1113.
    12. Fang, Xiaolun & Yang, Qiang, 2024. "Dynamic reconfiguration of photovoltaic array for minimizing mismatch loss," Renewable and Sustainable Energy Reviews, Elsevier, vol. 191(C).
    13. Belhachat, Faiza & Larbes, Cherif, 2017. "Global maximum power point tracking based on ANFIS approach for PV array configurations under partial shading conditions," Renewable and Sustainable Energy Reviews, Elsevier, vol. 77(C), pages 875-889.
    14. Çelik, Özgür & Teke, Ahmet & Tan, Adnan, 2018. "Overview of micro-inverters as a challenging technology in photovoltaic applications," Renewable and Sustainable Energy Reviews, Elsevier, vol. 82(P3), pages 3191-3206.
    15. Bradai, R. & Boukenoui, R. & Kheldoun, A. & Salhi, H. & Ghanes, M. & Barbot, J-P. & Mellit, A., 2017. "Experimental assessment of new fast MPPT algorithm for PV systems under non-uniform irradiance conditions," Applied Energy, Elsevier, vol. 199(C), pages 416-429.
    16. Amjad Ali & K. Almutairi & Muhammad Zeeshan Malik & Kashif Irshad & Vineet Tirth & Salem Algarni & Md. Hasan Zahir & Saiful Islam & Md Shafiullah & Neeraj Kumar Shukla, 2020. "Review of Online and Soft Computing Maximum Power Point Tracking Techniques under Non-Uniform Solar Irradiation Conditions," Energies, MDPI, vol. 13(12), pages 1-37, June.
    17. Mao, Mingxuan & Zhang, Li & Duan, Pan & Duan, Qichang & Yang, Ming, 2018. "Grid-connected modular PV-Converter system with shuffled frog leaping algorithm based DMPPT controller," Energy, Elsevier, vol. 143(C), pages 181-190.
    18. Abdelbasset Krama & Laid Zellouma & Boualaga Rabhi & Shady S. Refaat & Mansour Bouzidi, 2018. "Real-Time Implementation of High Performance Control Scheme for Grid-Tied PV System for Power Quality Enhancement Based on MPPC-SVM Optimized by PSO Algorithm," Energies, MDPI, vol. 11(12), pages 1-26, December.
    19. Li, Qiyu & Zhao, Shengdun & Wang, Mengqi & Zou, Zhongyue & Wang, Bin & Chen, Qixu, 2017. "An improved perturbation and observation maximum power point tracking algorithm based on a PV module four-parameter model for higher efficiency," Applied Energy, Elsevier, vol. 195(C), pages 523-537.

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