Machine Learning for Enhancing Geothermal energy production

The key target of this project is developing a new AI-based tool, "MALEG" (Machine Learning for Enhancing.

Geothermal energy production) to study and quantify the impact of enhanced heat extraction from thermal waters on geothermal plants in terms of their two most significant aspects, the geochemical and economic characteristics. At the same time, the MALEG simulation tool will be developed for onsite operation and act as a “digital twin controller” for geothermal plants. This development will be accompanied by comprehensive geochemical sampling campaigns. 

The AI-based tool resulting in a digital twin will be part of the “MALEG demonstration system” and complemented by a field laboratory which constitutes a corresponding “hardware twin”. It is conceived to emulate a geothermal plant with process technology for geothermal brine treatment and mineral extraction. 

Main Coordinator: 

Joachim Koschikowski
Fraunhofer Institute for Solar Energy Systems