Journal Article FZJ-2025-03661

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High‐Throughput PV Module Diagnostics using a Compact NIR Spectrometer

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2025
Wiley-VCH Weinheim

Solar RRL 9(18), 202500323 () [10.1002/solr.202500323]

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Abstract: The degradation of backsheets and encapsulants in photovoltaic (PV) modules compromises their long-term performance and reliability. This study investigates the use of a compact near-infrared (NIR) spectrometer for high-throughput field diagnostics of PV materials. Operating in the 1550–1950 nm spectral range, the spectrometer detects key molecular absorption bands to characterize polymer compositions. Principal component analysis (PCA) applied to the spectral data significantly improved material differentiation compared to raw data, achieving classification reliability exceeding 95%. Field deployment at a 10 mw PV installation demonstrated the method's scalability, with 981 modules analyzed at a rate of one module every 3 s. Spatial mapping revealed that all analyzed backsheets featured polyethylene terephthalate (PET) cores, with approximately 65% incorporating fluoropolymer- and 35% PET-based outer layers. These findings demonstrate the scalability and efficiency of a portable NIR spectrometer for rapid, nondestructive diagnostics of PV modules. The ability to directly identify polymer compositions during high-throughput field measurements enables applications in predictive maintenance, reliability assessment, bill-of-materials verification, and efficient sorting and recycling of end-of-life modules.

Classification:

Contributing Institute(s):
  1. Helmholtz-Institut Erlangen-Nürnberg Erneuerbare Energien (IET-2)
Research Program(s):
  1. 1214 - Modules, stability, performance and specific applications (POF4-121) (POF4-121)

Appears in the scientific report 2025
Database coverage:
Medline ; Creative Commons Attribution CC BY 4.0 ; OpenAccess ; Clarivate Analytics Master Journal List ; Current Contents - Engineering, Computing and Technology ; Current Contents - Physical, Chemical and Earth Sciences ; DEAL Wiley ; Essential Science Indicators ; IF >= 5 ; JCR ; SCOPUS ; Science Citation Index Expanded ; Web of Science Core Collection
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Open Access

 Datensatz erzeugt am 2025-09-08, letzte Änderung am 2025-11-03


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