Thomas Wolgast
Contact
Sekretary
Head
Thomas Wolgast
Thomas Wolgast M. Sc.
- Real-Time Optimal Power Flow
- Multi-Agent Control Systems
- Machine Learning / Deep Learning
- Ancillary Service Markets
- Adversarial Attacks on Power Systems
Department of Computing Science (» Postal address)
Publications
- Wolgast, T., Nieße, A. Towards modular composition of agent-based voltage control concepts. Energy Inform 2, 26 (2019). https://doi.org/10.1186/s42162-019-0079-x
- Neugebauer, T.; Wolgast, T.; Nieße, A. Dynamic Inspection Interval Determination for Efficient Distribution Grid Asset-Management. Energies 2020, 13, 3875. https://doi.org/10.3390/en13153875
Curriculum vitae
Thomas Wolgast is doctoral student in the field of energy informatics at the University of Oldenburg.
He received his Master of Science in Power Engineering from the Leibniz University Hannover. His master thesis was the implementation and evaluation of multi-agent based voltage control concepts in the distribution grid.
Currently, he is working in the field of real-time control of power systems using Machine Learning. A further research interest is market-based optimal reactive power dispatch for ancillary services. Thomas is responsible for the PYRATE project, in which Reinforcement Learning is used to investigate systematic adversarial attacks on the power system.
He received his Master of Science in Power Engineering from the Leibniz University Hannover. His master thesis was the implementation and evaluation of multi-agent based voltage control concepts in the distribution grid.
Currently, he is working in the field of real-time control of power systems using Machine Learning. A further research interest is market-based optimal reactive power dispatch for ancillary services. Thomas is responsible for the PYRATE project, in which Reinforcement Learning is used to investigate systematic adversarial attacks on the power system.