Monte Carlo prediction of the energy performance of a photovoltaic panel using detailed meteorological input data

• Published in: International journal of thermal sciences Vol. 195; p. 108672
• Main Authors: Villemin, Thomas, Farges, Olivier, Parent, Gilles, Claverie, Rémy
• Format: Journal Article
• Language: English
• Published: Elsevier Masson SAS 01.01.2024; Elsevier
• Subjects: Engineering Sciences; Heat transfers; Monte Carlo method; Photovoltaics; Renewable technologies; Monte Carlo method; Renewable technologies; Heat transfers; Photovoltaics
• ISSN: 1290-0729; 1778-4166
• DOI: 10.1016/j.ijthermalsci.2023.108672

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 310W 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. •The energy balance of a photovoltaic panel is solved using Monte Carlo method.•The method gives access to the temperature at any probe location in the panel.•Temperatures were validated against experimental data for different weather conditions.•Electrical production for several years using hourly weather data was calculated.