The increasing worldwide population leads to a constant increase in energy and food demand. These increasing demands have led to fierce land-use conflicts as we need agricultural land for food production while striving towards renewable energy systems such as large-scale solar photovoltaic (PV) systems, which also require in most of the cases agricultural flat land for implementation. It is therefore essential to identify the interrelationships between the food, and energy sectors and develop intelligent solutions to achieve global goals such as food and energy security. A technology that has shown promising potential in supporting food, and energy security, as well as support water security, is agrivoltaic (AV) systems. This technology combines conventional farm activities with PV systems on the same land. Understanding the microclimatic conditions in an AV system is essential for an accurate assessment of crop yield potential as well as for the energy performance of the PV systems. Nevertheless, the complex mechanisms governing the microclimatic conditions under agrivoltaic systems represent an underdeveloped research area. In this study, a computational fluid dynamics (CFD) model for a vertical AV system is developed and validated. The CFD model showed PV module temperature estimation errors in the order of 0-2 °C and ground temperature errors in the order of 0-1 °C. The shadings that occurred due to the vertical module had a reduction of the solar intensity of 38%. CFD modelling can be seen as a robust approach to analysing microclimatic parameters and assessing AV systems performances.
Sebastian Zainali, Omar Qadir, Sertac Cem Parlak, Silvia Ma Lu, Anders Avelin, Bengt Stridh, Pietro Elia Campana. 2023. Computational Fluid Dynamics Modelling of Microclimate for a Vertical Agrivoltaic System. Energy Nexus. 9:
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