  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 {\deg}C and ground temperature errors in
the order of 0-1 {\deg}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.
