Climate change is one of the greatest challenges facing society today. Tackling this challenge will require a complete reorganisation of the infrastructure necessary to satisfy our energy needs: electricity generators, storage, energy networks, heating supply, transport and industrial processes. In Europe hundreds of billions of euros of spending per year are at stake, and we do not have time to correct misallocations of investment before climate change takes effect. Accurate modelling and simulation of future energy systems are therefore crucial.
Our research at the Department of Digital Transformation in Energy Systems (ENSYS) leverages cutting-edge research from a variety of disciplines to understand the most cost-effective pathways to reduce greenhouse gas emissions in the energy system. This involves building models of the energy system and optimising the investment in and operation of the necessary infrastructure. Maintaining sufficient model detail and interdependencies is crucial to avoid misallocation of investment and bad policy advice, but it also presents an extreme computational challenge. To tackle this challenge we’re developing new algorithms and methodologies so that we can capture these details in a manageable way and therefore provide the best possible policy guidance for the transition to a sustainable energy future. We also lead the development of the Python for Power System Analysis (PyPSA) open-source energy modelling framework and ecosystem (www.pypsa.org).
In addition to research, the department makes a contribution to the education of future decision-makers in the energy sector with a comprehensive range of courses, critical scientific discourse and the supervision of theses.
The Department of Digital Transformation in Energy Systems has been under the direction of Prof. Dr. Tom Brown since 2021. Previously, it was led by Prof. Dr. Georg Erdmann.
Sekr. TA 8
Raum FT 024A
+49 (0)30 314 22 890
POST- UND BESUCHERADRESSE
Technische Universität Berlin
Institut für Energietechnik
Einsteinufer 25 (TA 8)