Influence of Lamination Conditions of EVA Encapsulation on Photovoltaic Module Durability.

Encapsulation is a well-known impact factor on the durability of Photovoltaics (PV) modules. Currently there is a lack of understanding on the relationship between lamination process and module durability. In this paper, the effects of different lamination parameters on the encapsulant stability due to stress testing have been investigated from both on-site production quality and long-term stability viewpoints. Rather than focusing on single stability factors, this paper evaluates lamination stability using a number of indicators including EVA (ethylene-vinyl acetate copolymer) curing level, voids generation, chemical stability, optical stability, and adhesion strength. The influences of EVA curing level on the stability of other properties are also discussed. It is shown that laminates stability increases with increasing curing level to an upper limit, beyond which leading to the formation of voids, reduced transmittance stability, discoloration, and unstable interfaces. A minimum gel content is identified but an upper limit should not be surpassed. The best range of gel content for the materials tested here is 84-90%. Samples with gel content below 70% show low chemical and optical stability, weak adhesion strength, and EVA flowing. Laminates with gel content over 92% are more likely to become yellow and are less stable in adhesion.

Extensive validation of CM SAF surface radiation products over Europe.

This work presents a validation of three satellite-based radiation products over an extensive network of 313 pyranometers across Europe, from 2005 to 2015. The products used have been developed by the Satellite Application Facility on Climate Monitoring (CM SAF) and are one geostationary climate dataset (SARAH-JRC), one polar-orbiting climate dataset (CLARA-A2) and one geostationary operational product. Further, the ERA-Interim reanalysis is also included in the comparison. The main objective is to determine the quality level of the daily means of CM SAF datasets, identifying their limitations, as well as analyzing the different factors that can interfere in the adequate validation of the products. The quality of the pyranometer was the most critical source of uncertainty identified. In this respect, the use of records from Second Class pyranometers and silicon-based photodiodes increased the absolute error and the bias, as well as the dispersion of both metrics, preventing an adequate validation of the daily means. The best spatial estimates for the three datasets were obtained in Central Europe with a Mean Absolute Deviation (MAD) within 8-13 W/m2, whereas the MAD always increased at high-latitudes, snow-covered surfaces, high mountain ranges and coastal areas. Overall, the SARAH-JRC's accuracy was demonstrated over a dense network of stations making it the most consistent dataset for climate monitoring applications. The operational dataset was comparable to SARAH-JRC in Central Europe, but lacked of the temporal stability of climate datasets, while CLARA-A2 did not achieve the same level of accuracy despite predictions obtained showed high uniformity with a small negative bias. The ERA-Interim reanalysis shows the by-far largest deviations from the surface reference measurements.