Agrivoltaics (AgriPV) is an emerging approach that integrates solar energy generation with agricultural production, using the same land for both electricity generation and crop production to improve land-use efficiency and support sustainable food-energy systems. Designing an effective agriPV system, however, requires balancing competing objectives, including light availability, shading, spectral quality, and heat and water stress, across both electricity generation and crop growth. Because these trade-offs are complex and interdependent, achieving an effective balance requires a systematic approach.
This project aims to use physical modelling and machine learning to optimise agriPV system design and improve the combined performance of electricity generation and crop growth, without relying solely on field trials.
Students will apply physical simulation models of agriPV systems, for example modelling how panel geometry and spacing affect light and heat distribution across a crop canopy, and use machine learning to optimise design based on these models. This may include efficiently searching design options such as panel angle and spacing, or building models that predict PV output or crop yield faster than a full simulation.
The specific research direction can be tailored to student interest, and the project will be carried out in a collaborative research environment, with students working mainly alongside two or three academic researchers as part of a wider team that includes both undergraduate and postgraduate students. An interest in Python programming is encouraged. Even a basic familiarity will help you get the most out of the project, and we will support you in developing your skills further.
School
Photovoltaic and Renewable Energy Engineering
Research Area
Agrivoltaics | Photovoltaics | Physical modelling | Simulation | Machine learning | Sustainable energy systems
Suitable for recognition of Work Integrated Learning (industrial training)?
No
- Research environment
- Expected outcomes
- Supervisory team
- Reference material/links
You will work with the ACDC Research Group, a lively team of more than 20 researchers dedicated to solar energy research. The group has a friendly and supportive environment. You'll benefit from close mentoring, regular meetings with supervisors, and opportunities to share your work with other team members. In addition to your research, you'll also be able to take part in a variety of social activities with the team.
- Students will gain practical experience in physical modelling and simulation of energy systems, along with hands-on experience applying machine learning techniques for design optimisation. They will develop Python programming skills applied within real research context and build an understanding of the trade-offs involved in designing sustainable, multi-purpose energy and agricultural systems.
- ACDC group website: https://www.acdc-pv-unsw.com/