Thermal solar tower plants are renewable energy facilities that use mirrors to concentrate sunlight onto a receiver. Here, the heat energy is collected and used for industrial processes or electricity generation without greenhouse gas emissions. Together with the German Aerospace Center, researchers at the SCC are creating a comprehensive digital twin of thermal solar power systems that can simulate how sunlight travels through these plants and collects at the receiver. Based on ray tracing principles, this simulation improves predictions of how much sunlight the mirrors will receive, thus optimizing their alignment to maximize the energy yield without overheating the receiver.
In the new ARTIST project, we aim to enhance a physics-based raytracer with artificial intelligence to create a data-driven digital copy of the power plant, which can then be used to design, control, predict, and diagnose issues during daily operations. This AI-enhanced system can optimize various aspects of the plant's operation, such as the mirror aimpoint, based on real-time conditions. In addition, we can explain certain operative actions in the plant's operation. We will test our digital twin at a real power plant in Jülich, Germany, marking a major milestone towards fully automated solar tower power plants.