Examining the interplay of dust and defects: A comprehensive experimental analysis on the performance of photovoltaic modules.

The performance of photovoltaic (PV) modules is greatly impacted by dust accumulation and defects appearing in photovoltaic (PV) modules. Existing studies primarily focus on the effect of dust on general photovoltaic performance, neglecting the interactions with pre-existing defects such as snail trails. These defects are known to degrade the efficiency of PV modules. However, their interaction with environmental factors like dust accumulation has not been extensively analyzed. This research comprehensively analyzes the impact of dust accumulation on the performance of PV modules affected by snail trails. Using an experimental setup under outdoor conditions, the study incorporates thermal imaging, current-voltage characteristic curve tracing (IV curve tracing), electroluminescence (EL) imaging, and chemical analysis of the accumulated dust, to evaluate the electrical and thermal parameters affecting PV module performance. The study focuses on three types of modules, clean serves as a reference module (PV-R), normal unclean (PV-N), and snail trail-affected unclean PV module (PV-S). Compared to the PV-R module, the study meticulously quantifies the effect of accumulated dust on key performance indicators such as output power, V, and I. The PV-N module exhibits reductions of 17.7 % in current, 3.91 % in voltage, and 18.15 % in power output. The PV-S module experienced a decrease of 7.4 % in current, 7.55 % in voltage, and 14.87 % in power output under the dust deposition density of 6.984 g/m^2 having a mean particle size of 2.2279 μm. The dust deposition reduced the transmittance of glass, which indicates a potentially adverse impact on the PV module's efficiency. The findings highlighted in the current work provide a significant understanding of the detrimental impacts of dust accumulation on defected photo voltaic modules, highlighting the need for regular maintenance and cleaning to ensure optimal performance.