Objectives
The project aims to complete the microclimate digital twin for agrivoltaic systems with solar tracking panels, extending the prototype developed during the previous phase. To achieve this, Computational Fluid Dynamics simulations are implemented in OpenFOAM to model fluid flows and the dynamic microclimatic conditions generated by the trackers. The model is validated using historical data from environmental sensors and three-dimensional geometric models of the site.
The project also aims to identify quantitative relationships between the dynamic shading produced by the panels and the microclimatic conditions experienced by the crops below. This will provide a rigorous knowledge base for the optimal design of future agrivoltaic systems.
Initial Challenge
Existing research in the agrivoltaic sector has focused primarily on observed production outcomes, without examining in detail the microclimatic conditions created by these systems. Addressing this knowledge gap is essential to enable data-driven design.
While the first phase of the project made it possible to model the microclimate generated by fixed solar panels, tracking systems introduce a significantly higher level of complexity. Shading is no longer static but changes continuously throughout daylight hours, requiring far more sophisticated Computational Fluid Dynamics simulations.
Solution
The developed solution integrates data from physical sensors installed at the agrivoltaic site — including humidity, air and soil temperature, and solar radiation sensors — with three-dimensional geometric models of the field. Using this integrated data foundation, Computational Fluid Dynamics simulations are carried out on the open-source OpenFOAM platform to model fluid flows and the dynamic microclimatic conditions beneath the solar trackers.
A dedicated Python pipeline orchestrates the entire process, from data preprocessing to the analysis of simulation results. The project advances the system from Technology Readiness Level 7, achieved during the previous phase, to Technology Readiness Level 8, corresponding to a complete and qualified system.
Benefits
The digital twin developed through the project provides agrivoltaic system operators and designers with a highly accurate predictive tool for: assessing the impact of dynamic shading on crops; optimising panel layout and orientation during the design phase; improving agronomic management during system operation.
The solution is inherently reusable and can be adapted to different geographical areas and crop types. It also completes IFAB’s agrivoltaic technology suite, which now covers both fixed-panel and solar tracking systems, contributing to the resilience and sustainability of the agricultural sector in the face of climate change.
IFAB’s Role
IFAB participated in the project as a funding organisation, selecting it as part of its investment programmes in research, innovation and technology transfer. IFAB’s contribution consisted of recognising the project’s scientific and practical value and providing financial support, thereby enabling the technical partners to carry out the planned research activities. This involvement further confirms IFAB’s mission as an accelerator of high-impact initiatives for the local area and the wider production ecosystem.
For further information, please contact: projects@ifabfoundation.org
