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A novel and efficient global maximum power tracking method for photovoltaic systems under complicated partial shading with repeatable irradiance conditions

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  • Wang, Shun-Chung

Abstract

Partial shading conditions (PSC) significantly hinder the conversion efficiency of photovoltaic (PV) generation systems (PVGS), posing challenges for global maximum power point (GMPP) tracking (GMPPT). This paper proposes a novel and efficient two-stage GMPPT method to address the challenges, introducing multiple techniques to improve tracking performance under complicated and repeatable irradiance environments. In the first stage, a Lambert W-function (LWF)-based modeling and estimation mechanism are developed to identify the candidate shaded region (SR) containing the GMPP and its corresponding voltage operating point (VOP) using fewer samplings. In the second phase, the variable step size incremental conductance (VSSINC) method, starting from the VOP found in the first stage, takes over subsequent tracking to refine convergence on the GMPP. A PV system formed by a 5-series 1-parallel (5S1P) module string is utilized as a study case. The devised method demonstrates significant advancements compared to the four presented benchmark methods. Simulations across 2002 shading patterns (SP) achieve maximum improvement rates of 98.4 % in average tracking power error (ATPE), 8.1 % in total tracking success rate (TTSR), and 66.9 % in average tracking time (ATT). Experimental results under three random SPs show improvements of 93.1 % in average tracking power loss (ATPL), 5.31 % in average tracking accuracy (ATA), and 86.6 % in ATT, all of which outperform the counterparts. These results highlight the significant improvement in TTSR, robustness to changes in SP, and efficiency derived from the proposed accurate LWF-based system modeling and estimation for the critical VOPs. This study also provides a new solution for maximizing the power extraction from PVGS and paving the way for the broader application and advancement in solar technology.

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  • Wang, Shun-Chung, 2025. "A novel and efficient global maximum power tracking method for photovoltaic systems under complicated partial shading with repeatable irradiance conditions," Applied Energy, Elsevier, vol. 383(C).
    • Handle: RePEc:eee:appene:v:383:y:2025:i:c:s0306261925001369
    DOI: 10.1016/j.apenergy.2025.125406
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    1. Pei Ye, Song & Hua Liu, Yi & Chung Wang, Shun & Yu Pai, Hung, 2022. "A novel global maximum power point tracking algorithm based on Nelder-Mead simplex technique for complex partial shading conditions," Applied Energy, Elsevier, vol. 321(C).
    2. Sahoo, Buddhadeva & Samantaray, Subhransu Ranjan & Rout, Pravat Kumar, 2024. "Enhanced supervisory control scheme for hybrid microgrid operation with virtual power plants," Applied Energy, Elsevier, vol. 372(C).
    3. Słowik, Adam & Cpałka, Krzysztof & Xue, Yu & Hapka, Aneta, 2024. "An efficient approach to parameter extraction of photovoltaic cell models using a new population-based algorithm," Applied Energy, Elsevier, vol. 364(C).
    4. Ma, Chao & Deng, Zexing & Xu, Ximeng & Pang, Xiulan & Li, Xiaofeng & Wu, Runze & Tian, Zhuojun, 2024. "Space optimization of utility-scale photovoltaic power plants considering the impact of inter-row shading," Applied Energy, Elsevier, vol. 370(C).
    5. Azaioud, Hakim & Farnam, Arash & Knockaert, Jos & Vandevelde, Lieven & Desmet, Jan, 2024. "Efficiency optimisation and converterless PV integration by applying a dynamic voltage on an LVDC backbone," Applied Energy, Elsevier, vol. 356(C).
    6. 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.
    7. Rizzo, Santi Agatino & Scelba, Giacomo, 2015. "ANN based MPPT method for rapidly variable shading conditions," Applied Energy, Elsevier, vol. 145(C), pages 124-132.
    8. Wang, Zhenlong & Wang, Yifan & Zhang, Xinrui & Yang, Dong & Ma, Duanyu & Ramakrishna, Seeram & Yuan, Weizheng & Ye, Tao, 2024. "Flexible photovoltaic micro-power system enabled with a customized MPPT," Applied Energy, Elsevier, vol. 367(C).
    9. Liu, Yang & Sun, Kangwen & Xu, Ziyuan & Lv, Mingyun, 2022. "Energy efficiency assessment of photovoltaic array on the stratospheric airship under partial shading conditions," Applied Energy, Elsevier, vol. 325(C).
    10. Samuel R. Fahim & Hany M. Hasanien & Rania A. Turky & Shady H. E. Abdel Aleem & Martin Ćalasan, 2022. "A Comprehensive Review of Photovoltaic Modules Models and Algorithms Used in Parameter Extraction," Energies, MDPI, vol. 15(23), pages 1-56, November.
    11. Salam, Zainal & Ahmed, Jubaer & Merugu, Benny S., 2013. "The application of soft computing methods for MPPT of PV system: A technological and status review," Applied Energy, Elsevier, vol. 107(C), pages 135-148.
    12. 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.
    13. Lappalainen, Kari & Valkealahti, Seppo, 2021. "Experimental study of the maximum power point characteristics of partially shaded photovoltaic strings," Applied Energy, Elsevier, vol. 301(C).
    14. Bustani Hadi Wijaya & Ramadhani Kurniawan Subroto & Kuo Lung Lian & Nanang Hariyanto, 2020. "A Maximum Power Point Tracking Method Based on a Modified Grasshopper Algorithm Combined with Incremental Conductance," Energies, MDPI, vol. 13(17), pages 1-19, August.
    15. Celikel, Resat & Yilmaz, Musa & Gundogdu, Ahmet, 2022. "A voltage scanning-based MPPT method for PV power systems under complex partial shading conditions," Renewable Energy, Elsevier, vol. 184(C), pages 361-373.
    16. Ahmed, Jubaer & Salam, Zainal, 2014. "A Maximum Power Point Tracking (MPPT) for PV system using Cuckoo Search with partial shading capability," Applied Energy, Elsevier, vol. 119(C), pages 118-130.
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