Use of Computational Fluid Dynamics to investigate heat exchanges in Floating Solar Plate Systems

Resumo

This study aims to investigate the temperature gradient between floating and non-floating solar panels, with the purpose of comparing results and enhancing the efficiency of solar energy production by reducing the temperature of the solar modules. This modeling is crucial to inform future development and implementation of more effective and sustainable solar systems, as well as to pursue the implications caused by these installations.

Thermal analyses between floating and non-floating solar modules were conducted using Computational Fluid Dynamics (CFD) via the Finite Volume Method to obtain the variables of interest. These finite volumes are interconnected by points called nodes. The set of all these elements and nodes is called a mesh, produced by the discretization of the geometry. All stages of this simulation were performed by entirely open-source software, from geometry and mesh generation to result visualization.

The simulation revealed a significant difference between the temperatures of the floating and non-floating panels, approximately 6 K (6°C), considering only one photovoltaic module. This discrepancy tends to have a positive impact on energy production, as the temperature of the solar cell affects its electrical current. Thus, reducing the temperature of the solar cells, as observed in the floating panel, results in an improvement in energy production. However, it is important to note that the increase in temperature resulting from the installation of a photovoltaic array on a large scale may lead to an increase in water temperature.

In summary, the experimental data presented by the simulation, corroborated by previous experiments, highlights the relevance of research in the field of solar energy, emphasizing the potential of innovative solutions, such as solar panel floating, to boost the efficiency and sustainability of photovoltaic energy generation. All of this supports our results and encourages us to continue investigating innovative solutions in the field, with the learning and improvement of simulations via computational methods and the perpetuation of the use of open-source tools.