Welcome
We help building a sustainable energy future by researching new technologies for the intelligent control of renewable energy systems across sectors and industries. Our research focus is the use of novel information technologies, in particular distributed systems, data-driven control algorithms and machine learning.
Grid planning Frankfurt - Optimized grid structures for power, natural gas and district heating
Transfer learning in building thermodynamics - Development and efficient training of machine learning models for the control of energy systems in buildings
e-SparX - A graph-based platform for machine learning in energy systems research
DSML - A framework for evaluating Machine Learning methods for electrical distribution system state estimation
Join our Research Seminar
Dive deeper into our research! Join our weekly research seminar where we present and discuss current topics. We welcome exchanges with the industry and warmly invite external experts to share their insights with us. The colloquium takes place every Wednesday from 11:30 to 12:30 in room N2816 or online. Interested parties are welcome – no registration is required.
If you would like to present or participate, you can find details here: https://collab.dvb.bayern/pages/viewpage.action?pageId=76053715
Open-Source Data for Energy Research
In our Open Energy Data Collection, we collect open-source data for energy research. Feel free to take a look if you are looking for data for your energy research. If you have or know of any data that should be included there, please feel free to contact us at any time at the following email address: manuel.katholnigg(at)tum.de