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Distinguishing between different types of multi‐layered PET‐based backsheets of PV modules with near‐infrared spectroscopy
- Source :
- Progress in photovoltaics 30(8), 859-868 (2022). doi:10.1002/pip.3465
- Publication Year :
- 2021
- Publisher :
- Wiley, 2021.
-
Abstract
- Degradation of backsheets (BSs) of commercial silicon PV modules is currently recognized as a source of reduced module performance and module failure. Monitoring of the BS state in the field is possible by using non-destructive and highly informative near-infrared absorption (NIRA) spectroscopy. Application of NIRA for the analysis of multi-layer polyethylene terephtalate (PET) based BSs, which dominate the PV module market, is challenging due to a large variety of possible BS configurations that show only small differences in NIRA spectra. In the present work, a spectroscopic tool for the structural identification of PET-based BSs is introduced. The method is based on a principal component analysis of a database of 250 representative NIRA spectra of BSs of different types. It allows a BS with an unknown structure to be assigned to one of 12 different types based solely on its NIRA spectrum. The identification was successfully validated on a test collection of 45 selected BSs and shown to be feasible for the field deployment. Further automation of NIRA measurements and spectral analysis are expected to elevate the proposed tool to the level of a non-intrusive high-throughput field analysis of the BS composition and state in operating PV module grids.
- Subjects :
- ddc:690
Materials science
Renewable Energy, Sustainability and the Environment
business.industry
Near-infrared spectroscopy
Principal component analysis
Optoelectronics
Electrical and Electronic Engineering
Condensed Matter Physics
business
Electronic, Optical and Magnetic Materials
Polyethylene terephtalate
Subjects
Details
- ISSN :
- 1099159X and 10627995
- Volume :
- 30
- Database :
- OpenAIRE
- Journal :
- Progress in Photovoltaics: Research and Applications
- Accession number :
- edsair.doi.dedup.....cda738c1df3c45edb7f005b09e231c96
- Full Text :
- https://doi.org/10.1002/pip.3465