The temperature prediction for floating PV (FPV) must account for the effect of humidity. In this work, PV temperature prediction for steady-state T_pv and transient conditions T_pv(t) incorporates the effect of humidity and cooling due to seawater (s.w.) splashing and evaporation on PV modules. The proposed formulas take as main inputs the in-plane solar irradiance_, wind speed, ambient temperature, relative humidity (RH), and s.w. temperature. The transient effects of s.w. splashing and the evaporation of the s.w. layer from the module are theoretically described considering the layer’s thickness using Navier–Stokes equations. T_pv and T_pv(t) measurements were taken before and after s.w. splashing on c-Si modules at the seashore and inland. PV temperature predictions compared to measured values showed very good agreement. The 55% RH at the seashore versus 45% inland caused the T_pv to decrease by 18%. The T_pv(t) at the end of the s.w. flow of 50–75 mL/s/m on the module at the seashore was 35–51% lower than the T_pv inland. This T_pv(t) profile depends on the s.w. splashing, lasts for about 1 min, and is attributed to higher convection, water cooling, and evaporation on the modules. The PV efficiency at FPV conditions was estimated to be 4–11.5% higher compared to inland.

PV temperature significantly affects the module’s power output and final system yield, and its accurate prediction can serve the forecasting of PV power output, smart grid operations, online PV diagnostics and dynamic predictive management of Building Integrated Photovoltaic (BIPV) systems. This paper presents a dynamic PV temperature prediction model based on transient Energy Balance Equations, incorporating theoretical expressions for all heat transfer processes, natural convection, forced convection, conduction and radiation exchanges between both module sides and the environment. The algorithmic approach predicts PV temperature at the centre of the cell, the back and the front glass cover with fast convergence and serves the PV power output prediction. The simulation model is robust, predicting PV temperature with high accuracy at any environmental conditions, PV inclination, orientation, wind speed and direction, and mounting configurations, free-standing and BIPV. These, alongside its theoretical basis, ensure the model’s wide applicability and clear advantage over existing PV temperature prediction models. The model is validated for a wide range of environmental conditions, PV geometries and mounting configurations with experimental data from a sun-tracking, a fixed angle PV and a BIPV system. The deviation between predicted and measured power output for the fixed-angle and the sun-tracking PV systems was estimated at −1.4% and 1.9%, respectively. The median of the temperature difference between predicted and measured values was as low as 0.5 °C for the sun-tracking system, and for all cases, the predicted temperature profiles were closely matching the measured profiles. The PV temperature and power output predicted by this model are compared to the results produced by other well-known PV temperature models, illustrating its high predictive capacity, accuracy and robustness.

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.