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Nondestructive characterization of solar PV cells defects by means of electroluminescence, infrared thermography, I–V curves and visual tests: Experimental study and comparison

Author

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  • Gallardo-Saavedra, Sara
  • Hernández-Callejo, Luis
  • Alonso-García, María del Carmen
  • Santos, José Domingo
  • Morales-Aragonés, José Ignacio
  • Alonso-Gómez, Víctor
  • Moretón-Fernández, Ángel
  • González-Rebollo, Miguel Ángel
  • Martínez-Sacristán, Oscar

Abstract

Photovoltaic (PV) modules are the core of every PV system, representing the power generation and their operation will affect the overall plant performance. It is one of the elements within a PV site with the higher failure appearance, being essential their proper operation to produce reliable, efficient and safety energy. Quantitative analysis and characterization of manufacturing, soldering and breaking PV defects is performed by a combination of electroluminescence (EL), infrared thermography (IRT), electrical current voltage (I–V) curves and visual inspection. Equivalent-circuit model characterization and microscope inspection are also performed as additional techniques when they contribute to the defects characterization. A 60-cells polycrystalline module has been ad hoc manufactured for this research, with different defective and non-defective cells. All cells are accessible from the backside of the module and the module includes similar kinds of defects in the same bypass string. This paper characterizes different defects of PV modules to control, mitigate or eliminate their influence and being able to do a quality assessment of a whole PV module, relating the individual cells performance with the combination of defective and non-defective cells within the module strings, with the objective of determining their interaction and mismatch effects, apart from their discrete performance.

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  • Gallardo-Saavedra, Sara & Hernández-Callejo, Luis & Alonso-García, María del Carmen & Santos, José Domingo & Morales-Aragonés, José Ignacio & Alonso-Gómez, Víctor & Moretón-Fernández, Ángel & González, 2020. "Nondestructive characterization of solar PV cells defects by means of electroluminescence, infrared thermography, I–V curves and visual tests: Experimental study and comparison," Energy, Elsevier, vol. 205(C).
    • Handle: RePEc:eee:energy:v:205:y:2020:i:c:s0360544220310379
    DOI: 10.1016/j.energy.2020.117930
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    1. 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).
    2. Davis, Kristopher O. & Rodgers, Marianne P. & Scardera, Giuseppe & Brooker, R. Paul & Seigneur, Hubert & Mohajeri, Nahid & Dhere, Neelkanth G. & Wohlgemuth, John & Schneller, Eric & Shiradkar, Narendr, 2016. "Manufacturing metrology for c-Si module reliability and durability Part II: Cell manufacturing," Renewable and Sustainable Energy Reviews, Elsevier, vol. 59(C), pages 225-252.
    3. Du, Bolun & Yang, Ruizhen & He, Yunze & Wang, Feng & Huang, Shoudao, 2017. "Nondestructive inspection, testing and evaluation for Si-based, thin film and multi-junction solar cells: An overview," Renewable and Sustainable Energy Reviews, Elsevier, vol. 78(C), pages 1117-1151.
    4. Dong Ji & Cai Zhang & Mingsong Lv & Ye Ma & Nan Guan, 2017. "Photovoltaic Array Fault Detection by Automatic Reconfiguration," Energies, MDPI, vol. 10(5), pages 1-13, May.
    5. Chine, W. & Mellit, A. & Pavan, A. Massi & Kalogirou, S.A., 2014. "Fault detection method for grid-connected photovoltaic plants," Renewable Energy, Elsevier, vol. 66(C), pages 99-110.
    6. Tsanakas, John A. & Ha, Long & Buerhop, Claudia, 2016. "Faults and infrared thermographic diagnosis in operating c-Si photovoltaic modules: A review of research and future challenges," Renewable and Sustainable Energy Reviews, Elsevier, vol. 62(C), pages 695-709.
    7. Gallardo-Saavedra, Sara & Hernández-Callejo, Luis & Duque-Pérez, Oscar, 2019. "Quantitative failure rates and modes analysis in photovoltaic plants," Energy, Elsevier, vol. 183(C), pages 825-836.
    8. Li, Guiqiang & Akram, M.W. & Jin, Yi & Chen, Xiao & Zhu, Changan & Ahmad, Ashfaq & Arshad, R.H. & Zhao, Xudong, 2019. "Thermo-mechanical behavior assessment of smart wire connected and busbarPV modules during production, transportation, and subsequent field loading stages," Energy, Elsevier, vol. 168(C), pages 931-945.
    9. Schneller, Eric J. & Brooker, R. Paul & Shiradkar, Narendra S. & Rodgers, Marianne P. & Dhere, Neelkanth G. & Davis, Kristopher O. & Seigneur, Hubert P. & Mohajeri, Nahid & Wohlgemuth, John & Scardera, 2016. "Manufacturing metrology for c-Si module reliability and durability Part III: Module manufacturing," Renewable and Sustainable Energy Reviews, Elsevier, vol. 59(C), pages 992-1016.
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    Cited by:

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    2. Waqar Akram, M. & Li, Guiqiang & Jin, Yi & Chen, Xiao, 2022. "Failures of Photovoltaic modules and their Detection: A Review," Applied Energy, Elsevier, vol. 313(C).
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    6. 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).
    7. Kellil, N. & Aissat, A. & Mellit, A., 2023. "Fault diagnosis of photovoltaic modules using deep neural networks and infrared images under Algerian climatic conditions," Energy, Elsevier, vol. 263(PC).
    8. Zhao, Xiaolong & Song, Chonghui & Zhang, Haifeng & Sun, Xianrui & Zhao, Jing, 2023. "HRNet-based automatic identification of photovoltaic module defects using electroluminescence images," Energy, Elsevier, vol. 267(C).

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