Seminare.EIM: Seminar on Electromagnetic Compatibility and Electric Power Systems (Bachelor/Master-ET) |
Semester: |
WiSe 22/23 |
Veranstaltungstyp: |
Seminar (Lehre) |
DozentIn: |
Prof. Dr.-Ing. Christian Becker, Dr. Anna Katharina Kirf, Kathleen Potzahr, Prof. Dr. sc. techn. Christian Schuster, Marwan Mostafa, M.Sc., Mirco Woidelko, M.Sc., M.A., Dr. Cheng Yang, Christoph Klie, M.Sc., Johannes Heise, M.Sc., Dr.-Ing. Jan-Peter Heckel, Simon Stock, M.Sc., Hanko Ipach, M.Sc., Robert Annuth, M.Sc., Béla Wiegel, M.Sc., Tom Steffen, M.Sc. |
Beschreibung: |
Due to the energy transition, an increasing number of renewable energy plants are installed and connected to the grid. Their integration into the existing grid structure leads to challenging problems, which need to be solved to keep the grid stable. In addition to the conventional methods, the increasing availability of computational power allows to explore more computationally expensive algorithms and techniques. Besides optimization algorithms, machine learning approaches have gained popularity in the field of power engineering. Machine learning is a very diverse approach also used in multiple other disciplines and can be tailored to solve various problems. It offers a broad variety of techniques, networks, and algorithms with multiple advantages.
In this joint seminar, the different applications for optimization techniques and machine learning in electrical energy systems are presented and discussed.
The Seminar is open for Bachelor and Master Students in the electrical engineering program of TUHH.
PhD students from both Institutes present their current research, while Bachelor/Master students give presentations on topics related to either power technology or electromagnetic compatibility. |
Bereichseinordnung: |
Studiendekanat Elektrotechnik, Informatik und Mathematik |
Weitere Informationen aus Stud.IP zu dieser Veranstaltung |
Heimatinstitut: Elektrotechnik, Informatik und Mathematik
In Stud.IP angemeldete Teilnehmer: 33
Anzahl der Postings im Stud.IP-Forum: 2
Anzahl der Dokumente im Stud.IP-Downloadbereich: 4
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