Abstract
The presented work focuses on the influence of different stress combinations (in climate-specific ageing tests) on polymer material degradation and electrical power loss of PV modules and how these data can be linked using advanced statistical methods. The statistical analysis is divided into three parts: in the first part, the direct effects of the climatic stresses on the electrical performance are assessed. The second part aims to correlate the electrical degradation behaviour with changes in the encapsulation material, and the third part does the same for the backsheet material of the modules. Time series of electrical data are extracted from IV curves and correlated with changes in material parameters obtained from fluorescence spectroscopy of the encapsulant as well as infrared spectroscopy and colour measurements of the backsheet. The data set analyzed consists of measurements that were taken throughout accelerated ageing experiments simulating stressors typically found for arid, tropical, moderate, and alpine climate zones. Significant correlations were found between the material changes - as indicated by the spectral measurements - and the electrical power loss of the test modules in the course of climate-specific ageing. The results of the analysis provide valuable input for possible measures of preventive maintenance based on condition monitoring of single modules. The methodology developed in this paper allows for an estimation of the power output for modules with identical design and bill of materials using simple, non-destructive measurement methods. The results from accelerated lab tests and the correlations determined from them can be used to predict the electrical power output of installed PV modules. As a result, deviations in module performance can be detected at an early stage and preventive maintenance measures in PV systems can be carried out.
Original language | English |
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Article number | 112485 |
Number of pages | 15 |
Journal | Solar Energy Materials and Solar Cells |
Volume | 260 |
DOIs | |
Publication status | Published - 15 Sept 2023 |
Research Field
- Energy Conversion and Hydrogen Technologies
Keywords
- Photovoltaic modules
- Degradation Models
- Statistical Data Analysis