Optimizing Land Productivity with Customized Tracking Algorithms for Single-Axis Trackers in Agrivoltaic Systems

We have developed a comprehensive tool that integrates both crop and photovoltaic modelling, aiming to optimize the design of agrivoltaic (APV) tracking systems. This research provides practical insights into the design and operation of agrivoltaic systems, equipping the industry with valuable knowledge. Using this tool, we evaluated the land productivity of a large-scale bifacial APV system with single-axis trackers in Germany. We simulated the growth of shade-intolerant crops (maize) across various tracker configurations, including row spacing and tracking algorithms. Our findings reveal a clear relationship between tracker row spacing, tracking algorithms and land productivity. Results suggest that customized tracking algorithms are a very good solution for shade-intolerant crops as 66% crop yield is not achievable with only row spacing. Using customized tracking algorithms with lower row spacing generates higher crop yield.