Fraunhofer ISE uses digital twin model and deep learning for optimised tracking

Facebook
Twitter
LinkedIn
Reddit
Email
Fraunhofer ISE testing field
The project is conducted in collaboration with Zimmermann PV-Tracker. Image: Fraunhofer ISE

German research organisation Fraunhofer Institution for Solar Energy Systems (Fraunhofer ISE) has launched a project to improve tracking algorithms, using a digital twin that adopts deep learning to calculate optimised control approaches.

The project, called DeepTrack, was conducted in collaboration with the engineering firm Zimmermann PV-Tracker, part of the Zimmermann PV-Steel Group. In the project, Zimmermann PV-Tracker installed one of its solar tracking systems on Fraunhofer ISE’s outdoor test field to obtain measurements under real conditions.

This article requires Premium SubscriptionBasic (FREE) Subscription

Try Premium for just $1

  • Full premium access for the first month at only $1
  • Converts to an annual rate after 30 days unless cancelled
  • Cancel anytime during the trial period

Premium Benefits

  • Expert industry analysis and interviews
  • Digital access to PV Tech Power journal
  • Exclusive event discounts

Or get the full Premium subscription right away

Or continue reading this article for free

After that, the digital twin learned from data from installed solar tracking systems, using deep learning to calculate optimised control approaches. Based on the results, Zimmermann PV-Tracker and Fraunhofer ISE developed a digital twin that contained solar PV monitoring and modelling tools with weather forecasts thanks to deep learning.

Therefore, the optimal tracking positions of the solar PV modules were mapped for different situations.

“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,” said Matthew Berwind, team leader at Fraunhofer ISE.

Berwind added that the next step was to combine the two approaches so that both aspects could be maximised as much as possible.

“Calculating this sweet spot is challenging but possible with our AI-based approach,” Berwind added.

Fraunhofer ISE cited the German Engineering Federation (VDMA) that 60% of solar PV power plants worldwide will operate with a tracker system in the future. It added that after the adoption of Solar Package I into the German Renewable Energy Sources Act (EEG), strong growth in agriPV systems with trackers can be also expected in Germany.

Hannes Elsen, product manager at Zimmermann PV, said: “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 research project will continue to run until early 2025.

Read Next

August 4, 2026
The Eindhoven University of Technology announced 'Stella Juva', a prototype of the world's first solar-powered ambulance.
August 4, 2026
Solar developer RWE has signed a power purchase agreement (PPA) with tech giant Google to power data centre operations in Oklahoma, US.
August 4, 2026
Australia's CEFC has committed AU$100 million (US$65.8 million) to a new programme targeting mid-scale hybrid solar-plus-storage projects.
August 3, 2026
India’s electricity regulator, CERC, has proposed restoring interstate transmission charge waivers for delayed renewable energy projects.
August 3, 2026
TotalEnergies has acquired a 4GW renewable energy portfolio from fellow oil major Shell, which includes 500MW of solar PV and wind assets.
August 3, 2026
A US court has upheld a FERC plan to speed up the permitting process for connecting energy projects to the grid.

Upcoming Events

Solar Media Events
October 13, 2026
San Francisco Bay Area, USA
Solar Media Events
November 3, 2026
Málaga, Spain
Solar Media Events
November 24, 2026
Warsaw, Poland
Solar Media Events
April 20, 2027
Istanbul, Türkiye