Seminar: Artificial Intelligence for Energy Systems
- Type: Seminar (S)
- Chair: TM Hagenmeyer
- Semester: WS 26/27
-
Time:
Mo. 26.10.2026
14:00 - 15:30, einmalig
50.28 Seminarraum 1
50.28 InformatiKOM 2 (EG)
Mo. 02.11.2026
14:00 - 15:30, wöchentlich
50.28 Seminarraum 2
50.28 InformatiKOM 2 (EG)
Mo. 09.11.2026
14:00 - 15:30, wöchentlich
50.28 Seminarraum 2
50.28 InformatiKOM 2 (EG)
Mo. 16.11.2026
14:00 - 15:30, wöchentlich
50.28 Seminarraum 2
50.28 InformatiKOM 2 (EG)
Mo. 23.11.2026
14:00 - 15:30, wöchentlich
50.28 Seminarraum 2
50.28 InformatiKOM 2 (EG)
Mo. 30.11.2026
14:00 - 15:30, wöchentlich
50.28 Seminarraum 2
50.28 InformatiKOM 2 (EG)
Mo. 07.12.2026
14:00 - 15:30, wöchentlich
50.28 Seminarraum 2
50.28 InformatiKOM 2 (EG)
Mo. 14.12.2026
14:00 - 15:30, wöchentlich
50.28 Seminarraum 2
50.28 InformatiKOM 2 (EG)
Mo. 21.12.2026
14:00 - 15:30, wöchentlich
50.28 Seminarraum 2
50.28 InformatiKOM 2 (EG)
Mo. 11.01.2027
14:00 - 15:30, wöchentlich
50.28 Seminarraum 2
50.28 InformatiKOM 2 (EG)
Mo. 18.01.2027
14:00 - 15:30, wöchentlich
50.28 Seminarraum 2
50.28 InformatiKOM 2 (EG)
Mo. 25.01.2027
14:00 - 15:30, wöchentlich
50.28 Seminarraum 2
50.28 InformatiKOM 2 (EG)
Mo. 01.02.2027
14:00 - 15:30, wöchentlich
50.28 Seminarraum 2
50.28 InformatiKOM 2 (EG)
Mo. 08.02.2027
14:00 - 15:30, wöchentlich
50.28 Seminarraum 2
50.28 InformatiKOM 2 (EG)
Mo. 15.02.2027
14:00 - 15:30, wöchentlich
50.28 Seminarraum 2
50.28 InformatiKOM 2 (EG)
- Lecturer: TT-Prof. Dr. Benjamin Schäfer
- SWS: 2
- Lv-No.: 2400175
- Information: Präsenz
| Inhalt | Artificial Intelligence (AI) is a key technology in many areas of society and research. Energy systems with the ongoing energy transition (“Energiewende”) make it a fascinating field for the deployment of AI methods. Machine learning algorithms can play a crucial role in improving energy efficiency, optimizing power generation and distribution or in enhancing system stability, while facilitating additional renewable energy integration. In this proseminar, we will explore fundamental AI algorithms and their applications in energy systems. Examples may include forecasting of energy demand or renewable generation, explainability of algorithms as well as optimization via AI. |