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Degradation of Bifacial & Monofacial, Double Glass & Glass-backsheet, Photovoltaic Modules with Multiple Packaging Combinations

Liu, Jiqi
http://orcid.org/0000-0003-2016-4160
http://rave.ohiolink.edu/etdc/view?acc_num=case1654890007036549

Abstract Details

2022, Doctor of Philosophy, Case Western Reserve University, Materials Science and Engineering.
The annual installed capacity of solar energy has grown rapidly in recent years and reached 773.3 GW at the end of 2020, providing 3.1% of global electricity demand. The levelized cost of electricity (LCOE) of solar energy has been continuously decreasing since 2009 and reached $0.037/kWh in 2020. Improving the reliability of photovoltaic (PV) modules and reducing their degradation rates are critical for further decreasing the LCOE and maintaining market competitiveness. The degradation of PV modules depends on their interaction with exposure conditions and is strongly influenced by their packaging materials and combinations. In recent years, modules using polyolefin elastomer (POE), double glass (DG) module architecture, or transparent backsheet have been gaining market share and have become strong competitors to conventional monofacial ethylene-vinyl acetate (EVA) glass-backsheet (GB) modules. However, the reliability performance data of these emerging packaging strategies were lacking. This work used statistical analysis to compare the degradation behaviors of sixteen module variants under two indoor accelerated exposures and 1.6 years of outdoor exposure. The two indoor accelerated exposures included modified damp heat (80 ℃, 85% relative humidity) and modified damp heat with full-spectrum light, for up to 2,520 hours. The EVA+GB modules with opaque rear encapsulant exhibited a significantly greater power loss, and the dominant degradation mechanism was identified as interconnection corrosion. The outdoor exposure location was in the Dfa climate zone (continental, no dry season, hot summer). Significant differences in the average power loss were identified between three module variants and the other two. The dominant power loss factor for most module variants was uniform current power loss, followed by power loss due to increased series resistance. This work developed a cross-correlation algorithm to quantify the similarity of degradation behaviors under different exposures, considering the power loss rates and the similarity in trends for various electrical features over time. Enabled by extensive characterization data collected, various neural network models were explored to predict the change in electrical features based on images. Recurrent neural network (RNN) models outperformed convolution neural network (CNN) models, emphasizing the importance of utilizing measurements for the same sample taken at different exposure times to improve prediction accuracy.
Roger H. French (Committee Chair)
Alp Sehirlioglu (Committee Member)
Laura S. Bruckman (Committee Member)
Yinghui Wu (Committee Member)
Jennifer L. Braid (Committee Member)
Xuanji Yu (Committee Member)
192 p.
Materials Science; Packaging

Recommended Citations

Citations

  • Liu, J. (2022). Degradation of Bifacial & Monofacial, Double Glass & Glass-backsheet, Photovoltaic Modules with Multiple Packaging Combinations [Doctoral dissertation, Case Western Reserve University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=case1654890007036549

    APA Style (7th edition)

  • Liu, Jiqi. Degradation of Bifacial & Monofacial, Double Glass & Glass-backsheet, Photovoltaic Modules with Multiple Packaging Combinations. 2022. Case Western Reserve University, Doctoral dissertation. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=case1654890007036549.

    MLA Style (8th edition)

  • Liu, Jiqi. "Degradation of Bifacial & Monofacial, Double Glass & Glass-backsheet, Photovoltaic Modules with Multiple Packaging Combinations." Doctoral dissertation, Case Western Reserve University, 2022. http://rave.ohiolink.edu/etdc/view?acc_num=case1654890007036549

    Chicago Manual of Style (17th edition)

case1654890007036549
116
© 2022, all rights reserved.
This open access ETD is published by Case Western Reserve University School of Graduate Studies and OhioLINK.
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