Fraunhofer ISE and Zimmermann PV-Tracker Collaborate on Advanced Solar Tracking Technology

German institution and engineering firm -Tracker have unveiled their collaborative effort, “,” designed to enhance solar tracking algorithms through cutting-edge digital twin technology.

The initiative, conducted in partnership with the Zimmermann PV-Steel Group, integrates deep learning techniques to refine control strategies for solar tracking systems.

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The project involved installing a Zimmermann PV-Tracker solar tracking system in Fraunhofer ISE's outdoor test field, facilitating real-world data collection. Utilizing deep learning algorithms, a digital twin was developed to analyze data from operational solar tracking systems, thereby optimizing control strategies. This digital twin incorporates solar PV monitoring tools and weather forecasting capabilities, enabling precise mapping of optimal tracking positions for various scenarios.

Matthew Berwind, team leader at Fraunhofer ISE, highlighted the project's focus on maximizing energy yield and enhancing conditions for agrivoltaic systems: “As a first step, we developed control sequences that were geared towards the optimal electricity yield of bifacial solar modules or the best conditions for the plants underneath the agrivoltaics (agriPV) system.” Berwind emphasized the project's future direction: “Calculating this sweet spot is challenging but possible with our AI-based approach.”

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The collaboration aligns with industry projections; Fraunhofer ISE referenced the German Engineering Federation (VDMA) prediction that 60% of global solar PV power plants will incorporate tracker systems in the future. The implementation of Solar Package I under the German Sources Act (EEG) is expected to drive significant growth in agriPV systems utilizing trackers within Germany.

Hannes Elsen, product manager at Zimmermann PV, underscored the potential benefits for agrivoltaic applications: “For agriPV systems in particular, with its wide variety of crops and systems, we see great potential for tracking PV systems with optimised tracking algorithms.”

The DeepTrack project signifies a significant advancement in solar technology, leveraging AI-driven innovations to enhance energy efficiency and agricultural compatibility in solar PV installations.

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