PV Defects Identification through a Synergistic Set of Non-Destructive Testing (NDT) Techniques

Abstract

A synergistic set of NDT techniques, including I–V analysis, UVF imaging, IR thermography, and EL imaging, supports a diagnostics methodology developed in this work to qualitatively and quantitatively identify a wide range of PV defects. The methodology is based on (a) the deviation of the module electrical parameters at STC from their nominal values, for which a set of mathematical expressions was developed that provide an insight into potential defects and their quantitative impact on the module electrical parameters, and (b) the variation analysis of EL images captured at a sequence of bias voltages for a qualitative investigation on the spatial distribution and strength of the defects. The synergy of these two pillars, supported by UVF imaging, IR thermography, and I–V analysis cross-correlating their findings, makes the diagnostics methodology effective and reliable. It was applied on c-Si and pc-Si modules operating from 0–24 years, exhibiting a diversity of defects of varying severity, either pre-existing or formed by natural ageing or externally induced degradation. Defects such as EVA degradation, browning, corrosion in the busbar/interconnect ribbons, EVA/cell-interface delamination, pn-junction damage, e−+hole recombination regions, breaks, microcracks, finger interruptions, and passivation issues are detected. Degradation factors triggering a cascade of internal degradation processes through cause and effect are analysed and additional models are proposed for the temperature pattern under current mismatch and corrosion along the busbar, further empowering the cross-correlation of NDT results. Power degradation was determined from 1.2% in 2 years of operation to more than 50% in modules with film deposition.

Application of the Energy Efficiency Mathematical Model to Diagnose Photovoltaic Micro-Systems

“…Therefore, optimizing the energy efficiency of PV micro-systems, which should be taken into account not only at the engineering stage but also during operation, is an important aspect [2][3][4]. Maintaining the highest efficiency level of PV systems throughout their operation requires reliable and rapid servicing and diagnosing [5][6][7]. In light of the territorial dispersion of micro-systems (with most of them located on buildings), methods that involve systematic human-conducted equipment inspections are costly [8][9][10].…”

PV Temperature Prediction Incorporating the Effect of Humidity and Cooling Due to Seawater Flow and Evaporation on Modules Simulating Floating PV Conditions

“…Other empirical and semi-empirical formulas that predict T pv and T pv (t) have been proposed and validated in a large diversity of PV configurations [11][12][13][14], while formulas based on artificial neural networks (ANNs) [15][16][17] predicted T pv for FPV installations studied for each case. T pv is a crucial factor that affects efficiency, η pv , and evidently the PV power output, P m , [18], while high T pv and humidity accelerate the PV cell's aging [19][20][21][22]. In the last decade, the study of the PV performance in lakes and reservoirs, nearshore and offshore, has been given special attention because of interest in floating PV (FPV) [23][24][25][26], with a focus on the effect of the environmental conditions, such as I T , wind speed, v w , ambient temperature, T a , seawater (s.w.)…”