Monte Carlo prediction of the energy performance of a photovoltaic panel using detailed meteorological input data
Abstract
Modeling the thermal behavior of a photovoltaic system is one step toward a better simulation of its electrical performances. In this study, a numerical model of the energy balance of a 310 W photovoltaic panel is developed and used to estimate the panel’s temperature by integrating the meteorological parameters over time. The input factors are the global irradiance, wind speed, ambient temperature, ground and sky temperatures if available. The energy balance is interpreted in a probabilistic way using the Monte Carlo method which provides access to an estimation of the system temperature at any probe location. This estimation is validated using experimental data for typical days with clear, cloudy and rainy conditions. Then the model is used to determine the electrical production. Firstly, it is used for the month of June 2022 where the energy estimate is compared to the experimental measurements in Nancy (France). Secondly, the model is applied over the year 2019 for two different locations — in Nancy (France) and in Las Vegas (Nevada, USA). The results are analyzed and compared with the European photovoltaic simulation tool PVGIS. Finally, the electrical production in Nancy from 2013 to 2020 is estimated using the present model.
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