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Thermo-mechanical behavior assessment of smart wire connected and busbarPV modules during production, transportation, and subsequent field loading stages

Author

Listed:
  • Li, Guiqiang
  • Akram, M.W.
  • Jin, Yi
  • Chen, Xiao
  • Zhu, Changan
  • Ahmad, Ashfaq
  • Arshad, R.H.
  • Zhao, Xudong

Abstract

Thermo-mechanical loads induce stresses in photovoltaic (PV) modules, leading to crack formation. In this context, the understanding of module's thermo-mechanical behavior is important. To investigate the thermo-mechanical behavior of smart wire connected technology (SWCT) and busbarPV modules throughout their entire life, the present study is conducted that probes the stress distribution and deformation during production, transportation, and subsequent mechanical and thermal loading stages in a consecutive step-by-step manner using finite element modellingapproach. Pre-stresses and non-linearitiesare considered in simulation models. Stresses and displacements experienced by different parts/layers are examined, and crack sensitive regions are identified. In addition, the SWCTand busbarmodules are compared, and it is found that SWCTinterconnection is relatively a less stress inducing process and less susceptible to thermal and dynamic affects. During production stage, stresses of 39.3 MPaand 40.4 MPaare generated in SWCTcells and copper wires respectively; while, stresses of 60 MPaand 87 MPaare generated in busbarcells and busbarrespectively. Similarly, lower stresses are induced in SWCTPV modules during subsequent stages. The comparison results show advantages of SWCTmodule in terms of mechanical stability which can lead to improve the performance and reliability of PV modules.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:energy:v:168:y:2019:i:c:p:931-945
    DOI: 10.1016/j.energy.2018.12.002
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    References listed on IDEAS

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    1. Zarmai, Musa T. & Ekere, N.N. & Oduoza, C.F. & Amalu, Emeka H., 2015. "A review of interconnection technologies for improved crystalline silicon solar cell photovoltaic module assembly," Applied Energy, Elsevier, vol. 154(C), pages 173-182.
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    Cited by:

    1. 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).
    2. Zhang, Jinxia & Chen, Xinyi & Wei, Haikun & Zhang, Kanjian, 2024. "A lightweight network for photovoltaic cell defect detection in electroluminescence images based on neural architecture search and knowledge distillation," Applied Energy, Elsevier, vol. 355(C).
    3. 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).
    4. Nivelle, Philippe & Tsanakas, John A. & Poortmans, Jef & Daenen, Michaël, 2021. "Stress and strain within photovoltaic modules using the finite element method: A critical review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 145(C).
    5. Akram, M. Waqar & Li, Guiqiang & Jin, Yi & Chen, Xiao & Zhu, Changan & Zhao, Xudong & Khaliq, Abdul & Faheem, M. & Ahmad, Ashfaq, 2019. "CNN based automatic detection of photovoltaic cell defects in electroluminescence images," Energy, Elsevier, vol. 189(C).
    6. 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).
    7. Georgios Goudelis & Pavlos I. Lazaridis & Mahmoud Dhimish, 2022. "A Review of Models for Photovoltaic Crack and Hotspot Prediction," Energies, MDPI, vol. 15(12), pages 1-24, June.

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