A method for improving the accuracy of numerical simulations of a photovoltaic panel

Numerical simulations of photovoltaic solar panels are performed using temperature-dependent layer properties. The results are compared with experimental data recorded from a 50 W mono-crystalline panel and a 50 W poly-crystalline panel. The comparison shows that, for both panels, introducing temperature dependencies in the layer properties can significantly improve the accuracy of numerical simulations. On a sample day in August 2019, the mean absolute error in power prediction is found to decrease from 9.13 to 4.32% for the mono-crystalline panel and from 9.49 to 5.55% for the poly-crystalline panel, representing accuracy improvements of 52.7% and 41.5%, respectively. On an annual basis, the accuracy of estimating the power generated by the mono- and poly-crystalline panels improves by 52.8% and 41.4%, respectively. Finally, it is found that as the standard deviation of the temperature distribution on the panel increases, so does the effect of the temperature-dependent layer properties. This study highlights the need to account for the temperature dependencies of the different layer properties when numerically simulating photovoltaic panels.

Automated summary

Numerical simulations of photovoltaic solar panels show that incorporating temperature-dependent layer properties leads to significant improvements in accuracy. The study also reveals that as the standard deviation of temperature distribution increases on the panel, the impact of temperature-dependent layer properties also increases.