Solar‐NIRT: Identification of PV‐module backsheets in the field with natural sunlight

Abstract

AbstractReliable and durable solar power plants require PV modules with high‐grade polymer encapsulants and backsheets (BSs). For performance analyses of PV installations fast, reliable and non‐destructive methods for determining composition and degradation state of polymer components need to be developed. Here, we show that the structure of some common polymer BSs can be determined in the field in real time by analyzing near‐infrared transmission (NIRT) spectra collected under illumination with natural sunlight. The potential of this “Solar‐NIRT” method was probed by field measurements on a multi‐MW PV power plant where four major BS types were identified by multispectral cross‐sectional Raman imaging. Additionally, degradation of a particular BS type was found to result in distinct changes in NIRT spectra allowing the degraded BSs to be classified as a separate type. Principal component analysis (PCA) applied to a collection of 62 Solar‐NIRT spectra allowed to create a map of five clusters, each corresponding to a particular BS type. The feasibility of using the PCA cluster map for the identification of unknown samples was shown on a test set of 13 different BSs. The Solar‐NIRT is relatively fast, non‐invasive, selective, can be upgraded to a non‐contact regime making it a promising tool for high‐throughput characterization.