Abstract
The growth of photovoltaic (PV) solar energy harvesting is expected to be massive over the next 10 years, which will be one of the most trending and highlighted topics in the near future, due to the developments of the industrial sectors such renewable energy, agriculture, manufacturing and construction. As PV systems continue to be installed, maintenance and monitoring to preserve peak performance in renewable energy production is essential. In most cases modules are exposed to environmental factors that act as inhibitors over time such temperature fluctuations, ultraviolet (UV) radiation, humidity and moisture, where these factors are a burden on the performance of PV modules. In this work, we carried out near-infrared (NIR) spectroscopy measurements on modules of a utility-scale PV system. The modules (26) were randomly chosen from a PV plant located in central Italy, which has been operational for approximately 13 years. The results demonstrate the capacity to distinguish between backsheets and encapsulants materials for modules with unknown bill of materials (BOMs) by the use of principal component analysis (PCA) as a multivariate data analysis (MVDA). We identified three types of backsheets and one type of encapsulant for the 26 PV modules investigated. Additionally, the aspect of this work to detect and monitoring ageing, as well as differences between unexposed (references) and exposed modules for a specific BOM. Based on PCA results we got two trends: (1) some data related toexposed modules overlapped with the unexposed modules, indicating minimal degradation or similarity in the BOM even after field exposure, moreover (2) other exposed modules showed variation from the reference modules, hinting that the material is degrading or is influenced by environmental factors.