Snow Loss Modeling for Roof Mounted Photovoltaic Systems: Improving the Marion Snow Loss Model

Accurate photovoltaics (PV) energy yield assessments for cold climates necessitate understanding and estimation of snow loss. Estimation of snow loss for a specific system requires a snow loss model. Multiple models to estimate snow loss are suggested in the literature, but extensive validation is lacking. In this work, we describe the effect of snow on PV systems by analyzing signatures in monitoring data and we evaluate the accuracy of a modified adaption of the Marion snow loss model. Eight different systems with a total installed capacity of 1.6 MW _p , installed on both tilted and flat roofs, are analyzed. In the modified model we use different snow clearing rate coefficients for thin and thick snow covers to model the natural snow clearing process. The snow depth dependent coefficients yield lower error in the total modeled snow loss and capture climatic variations between locations more accurately compared to the standard constant coefficient. For most of the systems the total absolute snow loss is modeled with an error of less than 11%, on average 23% points lower than with the default implementation of the Marion model. Some of the systems have larger modeling errors, which can be related to effects not taken into account in the model, such as the effect of building heat leakage and shading on snow clearing.