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Distinguishing between different types of multi‐layered PET‐based backsheets of PV modules with near‐infrared spectroscopy
Author(s) -
Stroyuk Oleksandr,
BuerhopLutz Claudia,
Vetter Andreas,
Hepp Johannes,
Hauch Jens,
Peters Ian Marius,
Brabec Christoph J.
Publication year - 2022
Publication title -
progress in photovoltaics: research and applications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.286
H-Index - 131
eISSN - 1099-159X
pISSN - 1062-7995
DOI - 10.1002/pip.3465
Subject(s) - computer science , identification (biology) , process engineering , principal component analysis , absorption (acoustics) , biological system , materials science , artificial intelligence , engineering , botany , biology , composite material
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.