• Distribution grid topology identification
• Distribution grid planning
• Data analytics
• Probabilistic modelling

Research project:

Power distribution systems are currently undergoing a transformation due to the rising penetration of distributed renewable energy sources, electric vehicle home-chargers, and heat pumps. The integration of these solutions can often affect the stability of the grid and can lead to feeder congestions or the overload of grid equipment. To design mitigation measures for these challenges, grid planners need a digital representation of the existing infrastructure. Trustworthy and readily usable grid models are, however, often not available.

In a project funded by Siemens AG, we propose a framework that uses available data about a distribution grid (e.g., geodata, GIS data, etc.) to generate different, possible grid models, that appropriately represent the uncertainty in the estimation procedure. We apply the proposed framework conduct follow-up grid analyses, e.g., evaluate the potential overload of grid equipment with an increased roll-out of EV home-chargers.

• Since 2021: PhD student at Siemens Technology in coll. with EINS.
• 2018 – 2021: M.Sc. in Electrical Engineering and Information Technology at TUM
• 2015 – 2018: B.Sc. in Electrical Engineering and Information Technology at TUM.