MATRIX - Evaluation of the first agrivoltaic systems facility in Sweden

Agrivoltaic systems are likely to play a key role in the future energy systems by avoiding the conflict between land for energy versus land for food that characterize conventional solar parks. This research project follows the previous pioneering project founded by the Swedish Energy Agency to build the first experimental agrivoltaic system in Sweden.

From a theoretical perspective, this project aims to improve the modelling accuracy of APVs models by developing state-of-the-art algorithms and tools to better predict the interrelationships between solar radiation distribution at crop level, microclimate, and solar energy conversion into electricity and biomass under different APV solutions. From an implementation and industrial perspective, this project aims to develop algorithms for the dynamic simulation, optimal design, and operation of APVs, especially for those equipped with solar tracking systems.

Project objectives

This project aims at developing the first agrivoltaic system experimental facility in Sweden to compare commercially available agrivoltaic technologies. The project will generate a unique database for Sweden and worldwide on the effects of different agrivoltaic configurations on microclimate, PV production, and crops production. This will allow to develop cutting-edge tools for the simulation, optimal design, and operation of agrivoltaic systems. A demonstrator of control system for agrivoltaic systems equipped with solar tracker will be developed.

Specific objectives include:

• Upgrade the existing facility with one or two more APV technologies
• Assess the total solar radiation intercepted by the PV modules and crops under complex shading and reflection conditions created by APVs technologies and validate the model
• Develop optimization strategies for APV design and operation based on multiple criteria. We will create a matrix of APV configurations, versus crops management strategies, versus objective functions to provide a map of optimal system configurations.
• Develop software tools, and industrial control systems prototypes based on the algorithms that depict the relationships between shadings, intercepted solar radiation, microclimate, and crop yield.