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Mitigating Potential-Induced Degradation (PID) Using SiO 2 ARC Layer

Author

Listed:
  • Mahmoud Dhimish

    (Department of Engineering and Technology, University of Huddersfield, Huddersfield HD1 3DH, UK)

  • Yihua Hu

    (Department of Electronic Engineering, University of York, York YO10 5DD, UK)

  • Nigel Schofield

    (Department of Engineering and Technology, University of Huddersfield, Huddersfield HD1 3DH, UK)

  • Romênia G. Vieira

    (Department of Engineering and Technology, Semi-Arid Federal University, Mossoró 59626-105, Brazil)

Abstract

Potential-induced degradation (PID) of photovoltaic (PV) cells is one of the most severe types of degradation, where the output power losses in solar cells may even exceed 30%. In this article, we present the development of a suitable anti-reflection coating (ARC) structure of solar cells to mitigate the PID effect using a SiO 2 ARC layer. Our PID testing experiments show that the proposed ARC layer can improve the durability and reliability of the solar cell, where the maximum drop in efficiency was equal to 0.69% after 96 h of PID testing using an applied voltage of 1000 V and temperature setting at 85 °C. In addition, we observed that the maximum losses in the current density are equal to 0.8 mA/cm 2 , compared with 4.5 mA/cm 2 current density loss without using the SiO 2 ARC layer.

Suggested Citation

  • Mahmoud Dhimish & Yihua Hu & Nigel Schofield & Romênia G. Vieira, 2020. "Mitigating Potential-Induced Degradation (PID) Using SiO 2 ARC Layer," Energies, MDPI, vol. 13(19), pages 1-12, October.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:19:p:5139-:d:423112
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    References listed on IDEAS

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    1. Romênia G. Vieira & Fábio M. U. de Araújo & Mahmoud Dhimish & Maria I. S. Guerra, 2020. "A Comprehensive Review on Bypass Diode Application on Photovoltaic Modules," Energies, MDPI, vol. 13(10), pages 1-21, May.
    2. Šlamberger, Jan & Schwark, Michael & Van Aken, Bas B. & Virtič, Peter, 2018. "Comparison of potential-induced degradation (PID) of n-type and p-type silicon solar cells," Energy, Elsevier, vol. 161(C), pages 266-276.
    3. Hussain, Muhammed & Dhimish, Mahmoud & Titarenko, Sofya & Mather, Peter, 2020. "Artificial neural network based photovoltaic fault detection algorithm integrating two bi-directional input parameters," Renewable Energy, Elsevier, vol. 155(C), pages 1272-1292.
    4. Wang, Ao & Xuan, Yimin, 2018. "A detailed study on loss processes in solar cells," Energy, Elsevier, vol. 144(C), pages 490-500.
    5. Islam, M.A. & Hasanuzzaman, M. & Rahim, Nasrudin Abd, 2018. "A comparative investigation on in-situ and laboratory standard test of the potential induced degradation of crystalline silicon photovoltaic modules," Renewable Energy, Elsevier, vol. 127(C), pages 102-113.
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    Cited by:

    1. Dhimish, Mahmoud & Ahmad, Ameer & Tyrrell, Andy M., 2022. "Inequalities in photovoltaics modules reliability: From packaging to PV installation site," Renewable Energy, Elsevier, vol. 192(C), pages 805-814.

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