The resources, exergetic and environmental footprint of the silicon photovoltaic circular economy: Assessment and opportunities

被引:38
|
作者
Bartie, N. J. [1 ]
Cobos-Becerra, Y. L. [2 ]
Froehling, M. [3 ]
Schlatmann, R. [2 ]
Reuter, M. A. [1 ,4 ]
机构
[1] Helmholtz Zentrum Dresden Rossendorf, Helmholtz Inst Freiberg Resource Technol, Chemnitzer Str 40, D-09599 Freiberg, Germany
[2] Helmholtz Zentrum Berlin, PVcomB, Schwarzschildstr 3, D-12489 Berlin, Germany
[3] Tech Univ Munich, Professorship Circular Econ, Essigberg 3-2, D-94315 Straubing, Germany
[4] SMS Grp, Eduard Schloemann Str 4, D-40237 Dusseldorf, Germany
关键词
Silicon photovoltaics; Circular Economy; Digital twin simulation; Neural networks; Exergy; LIFE-CYCLE ASSESSMENT; ENERGY PAYBACK TIME; GRADE SILICON; SOLAR; EFFICIENCY; RECOVERY; DESIGN; PANELS;
D O I
10.1016/j.resconrec.2021.105516
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
The photovoltaic industry has shown vigorous growth over the last decade and will continue on its trajectory to reach terawatt-level deployment by 2022-2023 and an estimated 4.5 TW by 2050. Presently, its elaboration is driven primarily by cost reduction. Growth will, however, be fuelled by the consumption of various resources, bringing with it unavoidable losses and environmental, economic, and societal impacts. Additionally, strong deployment growth will be trailed by waste growth, which needs to be managed, to support Sustainable Development and Circular Economy (CE). A rigorous approach to quantifying the resource efficiency, circularity and sustainability of complex PV life cycles, and exploring opportunities for partially sustaining industry growth through the recovery of high-quality secondary resources is needed. We create a high-detail digital twin of a Silicon PV life cycle using process simulation. The scalable, predictive simulation model accounts for the system's non-linearities by incorporating the physical and thermochemical principles that govern processes down to the unit operation level. Neural network-based surrogate functions are subsequently used to analyse the system's response to variations in end-of-life and kerf recycling in terms of primary resource and power consumption, PV power generation capacity, and CO2 emission. Applying the second law of thermodynamics, opportunities for improving the sustainability of unit operations, the larger processes they are the building blocks of, and the system as a whole are pinpointed, and the technical limits of circularity highlighted. We show the significant effects changes in technology can have on the conclusions drawn from such analyses.
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页数:24
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