Abstract
Non-traditional photovoltaic (PV) modules, such as solar shingles, facades and skins, are expected to increase in market share as the solar industry matures and moves to fill building integrated photovoltaics niches. The advent of building integration and the application of photovoltaics to multiple surfaces come with fabrication challenges and inherent geometrical, optical and thermal constraints. In this paper, we investigate the curved lamination process and the integration of a dichroic polymeric film within the laminate for the particular case of a large-scale optical collector called a ”PVMirror”. PVMirror is a concentrating solar power (CSP)/PV hybrid design that combines the high efficiency of PV and storage capability of CSP using a dichroic film. The film does not degrade upon lamination and exhibits good adhesion to encapsulants. Multiple lamination approaches, such as tuning the thickness of the encapsulant, are shown to significantly reduce the impact of the lamination process on the shape error of PVMirror modules, which could also be applied to the fabrication of other non-traditional PV modules.
Original language | English (US) |
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Article number | 110072 |
Journal | Solar Energy Materials and Solar Cells |
Volume | 201 |
DOIs | |
State | Published - Oct 2019 |
Keywords
- Curved surfaces
- Hartmann test
- Lamination
- Non-traditional PV
- Optical film
- Shape error
ASJC Scopus subject areas
- Electronic, Optical and Magnetic Materials
- Renewable Energy, Sustainability and the Environment
- Surfaces, Coatings and Films
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Dive into the research topics of 'Optical characterization of curved silicon PV modules with dichroic polymeric films'. Together they form a unique fingerprint.Datasets
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Data for: Lamination of Silicon Solar Cells on Curved Surfaces and Incorporation of Polymeric Optical Films
Taylor, W. S. (Contributor), Bertoni, M. (Contributor), Meng, X. (Contributor), Stuckelberger, M. (Contributor), Holman, Z. (Contributor), Fisher, K. C. (Contributor) & Reinhart, L. O. (Contributor), Mendeley Data, Aug 7 2019
DOI: 10.17632/wsw4yz7z7r.1, https://data.mendeley.com/datasets/wsw4yz7z7r
Dataset