2024-10-10

AI-supported optimization of mirrors enables cost-effective solar thermal power plants

In collaboration with DLR, researchers at Helmholtz.AI are developing an AI-supported heliostat optimization. Heliostats are sun-tracking mirrors for solar thermal power plants. This significantly increases the efficiency of the power plants.

Blick auf das Solarkraftwerk am Forschungszentrum Jülich

At a test facility in Jülich, operated by the German Aerospace Center (DLR), nearly 2,000 mirrors are aligned to reflect sunlight onto an absorber atop a tower. These solar tower power plants can complement wind and photovoltaic energy as a renewable energy source. The heat they concentrate can be used to generate electricity, power thermal industrial processes, or even stored for use during nighttime or in calm wind conditions. Like other renewable technologies, solar thermal power plants face significant cost pressures. To stay competitive, cost-saving measures are essential. Given that heliostats are a key expense, optimizing their production and performance is crucial. Currently, the mirrors are not perfectly flat, leading to uneven heat distribution at the tower, requiring high safety margins and thus reducing efficiency.

Researchers from the German Aerospace Center (DLR), together with consultants from Helmholtz.AI at Forschungszentrum Jülich (FZJ) and SCC at KIT, have therefore developed a new AI-based method to easily detect irregularities in the mirrors. Their results have been published in Nature Communications.

 

Contact at SCC: Dr. Markus Götz

 

Achim Grindler