A mathematical simulator to evaluate the crop production in agrivoltaic systems

Agrivoltaic systems may contribute to sustainable food systems by combining crop production and photovoltaic energy generation on the same surface, especially in territories where land availability is limited. This work presents a simulator designed as a decision-support tool for the preliminary assessment of agrivoltaic systems in Mediterranean and Tropical regions, with special attention to crops of local interest.

The simulator was developed from scientific literature, agronomic information and solar radiation databases. It allows users to configure scenarios by defining geographical location, simulation period, terrain resolution, albedo, photovoltaic geometry, module height, tilt, transparency, row spacing, crop type and baseline yield. The selected crops are assigned to shade-tolerance groups according to literature data, allowing comparison between species with different responses to reduced radiation. The terrain is discretised into a two-dimensional mesh, where solar position and shading patterns are calculated at 15-min intervals. Direct, diffuse and global radiation data are obtained from PVGIS typical meteorological year datasets to estimate irradiance distribution at ground level. Crop productivity is evaluated through the relative shading ratio, and yield is estimated using empirical equations specific to each shade-tolerance group.

The simulator provides accumulated irradiance maps, monthly photovoltaic energy production, the proportion of cultivated area affected by different shading intervals and relative crop yield. These outputs make it possible to analyse how photovoltaic design modifies light availability and crop performance. In simulations comparing different horticultural crops such as chard, pepper and onion, chard showed the best performance under shade, pepper an intermediate response, and onion the greatest sensitivity to radiation reduction. Overall, the simulator offers a reproducible framework to explore agrivoltaic configurations, support crop selection and guide the design of systems aimed at improving food security, renewable energy production and land-use efficiency.