A sensitivity analysis on effective parameters for sliding/melting prediction of snow cover on solar photovoltaic panels

Abstract The electricity generation of solar photovoltaic (PV) panels can be significantly affected by snow cover on the panels. This influence must be accurately predicted for PV systems to be considered a reliable source of electricity generation. Previous studies have shown the effectiveness of threshold-type empirical models in predicting the condition of snow cover on PV panels; these models use plane-of-array irradiance and present ambient temperature to determine if clearing will occur on the panels. This study conducts a sensitivity analysis that examines the effectiveness of absorbed and accumulated solar irradiances as well as the thermal capacitance of PV panels on the prediction process. The analysis has experimentally proven that front absorbed irradiance substantially improves prediction models compared to ones based only on plane-of-array irradiance. Further analyses were executed on the solar radiation absorbed by a panel's back surface and accumulated solar heat caused by the thermal capacitance of PV panels. Experimental data was used to develop a preliminary model that can generate time-series weighting factors to calculate the accumulated solar heat in panels. The results of this analysis would assist subsequent investigations in reducing the uncertainties of empirical threshold models that determine meteorological conditions of snow cover melting and enhance the forecasting of electricity generation from PV systems in regions that experience snowfall.