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Modeling and maximum power point tracking (MPPT) method for PV array under partial shade conditions

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  • Qi, Jun
  • Zhang, Youbing
  • Chen, Yi

Abstract

Influenced by partial shade, PV module aging or fault, there are multiple peaks on PV array's output power–voltage (P–V) characteristic curve. Conventional maximum power point tracking (MPPT) methods are effective for single peak P–V characteristic under uniform solar irradiation, but they may fail in global MPP tracking under multi-peak P–V characteristics. Existing methods in literature for this problem are still unsatisfactory in terms of effectiveness, complexity and speed. In this paper, we first analyze the mathematical model of PV array that is suitable for simulation of complex partial shade situation. Then an adaptive MPPT (AMPPT) method is proposed, which can find real global maximum power point (MPP) for different partial shade conditions. When output characteristic of PV array varies, AMPPT will adjust tracking strategies to search for global peak area (GPA). Then it is easy for conventional MPPT to track the global MPP in GPA. Simulation and experimental results verify that the proposed AMPPT method is able to find real global MPP accurately, quickly and smoothly for complex multi-peak P–V characteristics. Comparison analysis results demonstrate that AMPPT is more effective for most shade types.

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  • Qi, Jun & Zhang, Youbing & Chen, Yi, 2014. "Modeling and maximum power point tracking (MPPT) method for PV array under partial shade conditions," Renewable Energy, Elsevier, vol. 66(C), pages 337-345.
    • Handle: RePEc:eee:renene:v:66:y:2014:i:c:p:337-345
    DOI: 10.1016/j.renene.2013.12.018
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    7. Hashemzadeh, Seyed Majid, 2019. "A new model-based technique for fast and accurate tracking of global maximum power point in photovoltaic arrays under partial shading conditions," Renewable Energy, Elsevier, vol. 139(C), pages 1061-1076.
    8. Sampath Kumar Vankadara & Shamik Chatterjee & Praveen Kumar Balachandran, 2022. "An accurate analytical modeling of solar photovoltaic system considering Rs and Rsh under partial shaded condition," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 13(5), pages 2472-2481, October.
    9. Polo, J. & Fernandez-Neira, W.G. & Alonso-García, M.C., 2017. "On the use of reference modules as irradiance sensor for monitoring and modelling rooftop PV systems," Renewable Energy, Elsevier, vol. 106(C), pages 186-191.
    10. Ramli, Makbul A.M. & Twaha, Ssennoga & Ishaque, Kashif & Al-Turki, Yusuf A., 2017. "A review on maximum power point tracking for photovoltaic systems with and without shading conditions," Renewable and Sustainable Energy Reviews, Elsevier, vol. 67(C), pages 144-159.
    11. Jena, Debashisha & Ramana, Vanjari Venkata, 2015. "Modeling of photovoltaic system for uniform and non-uniform irradiance: A critical review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 52(C), pages 400-417.
    12. Paula Andrea Ortiz Valencia & Carlos Andres Ramos-Paja, 2015. "Sliding-Mode Controller for Maximum Power Point Tracking in Grid-Connected Photovoltaic Systems," Energies, MDPI, vol. 8(11), pages 1-25, November.
    13. Tabanjat, Abdulkader & Becherif, Mohamed & Hissel, Daniel, 2015. "Reconfiguration solution for shaded PV panels using switching control," Renewable Energy, Elsevier, vol. 82(C), pages 4-13.
    14. 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).
    15. Guerrero-Rodríguez, N.F. & Rey-Boué, Alexis B. & Herrero-de Lucas, Luis C. & Martinez-Rodrigo, Fernando, 2015. "Control and synchronization algorithms for a grid-connected photovoltaic system under harmonic distortions, frequency variations and unbalances," Renewable Energy, Elsevier, vol. 80(C), pages 380-395.
    16. Dhimish, Mahmoud & Holmes, Violeta & Dales, Mark, 2017. "Parallel fault detection algorithm for grid-connected photovoltaic plants," Renewable Energy, Elsevier, vol. 113(C), pages 94-111.
    17. Başoğlu, Mustafa Engin & Çakır, Bekir, 2016. "A novel voltage-current characteristic based global maximum power point tracking algorithm in photovoltaic systems," Energy, Elsevier, vol. 112(C), pages 153-163.
    18. 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.
    19. 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.
    20. Zhang, Xiaoshun & Li, Shengnan & He, Tingyi & Yang, Bo & Yu, Tao & Li, Haofei & Jiang, Lin & Sun, Liming, 2019. "Memetic reinforcement learning based maximum power point tracking design for PV systems under partial shading condition," Energy, Elsevier, vol. 174(C), pages 1079-1090.

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