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IEET > Staff > Research Assistants > Simon Stock, M.Sc.

Simon Stock

M.Sc.
Research Assistant

Contact

Simon Stock, M. Sc.
E-6 Elektrische Energietechnik
  • Elektrische Energietechnik
Office Hours
Jederzeit
Harburger Schloßstraße 36,
21079 Hamburg
Building HS36, Room C3 0.006
Phone: +49 40 42878 2378
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Research Projects

Applications of AI in distribution system operation

Applications of AI in distribution system operation

Hamburg University of Technology (TUHH); Duration: 2020 to 2024

to the project page
VeN²uS
Networked grid protection systems - Adaptive and interconnected

VeN²uS

Networked grid protection systems - Adaptive and interconnected

Federal Ministry for Economic Affairs and Climate Action (BMWK); Duration: 2021 to 2024

to the project page

Research Focus

Optimal operation and energy managment in electrical distribution grids (Smart Grids) using artifical intelligence

Publications

TUHH Open Research (TORE)

2023

2022

2021

Courses

Stud.IP
link to course in Stud.IP Studip_icon
Seminare.EIM: From non-classical quantum phenomena to quantum computing (CSBS, IIWBS, TMBS, CSMS, IIWMS)
Semester:
WiSe 23/24
Course type:
Seminar
Lecturer:
Dr. Anna Katharina Kirf, Prof. Dr. Martin Kliesch
Description:
There are many phenomena in quantum physics that cannot be explained with a classical understanding of Nature. These phenomena can be exploited to develop novel, powerful quantum information processing methods, which include the development of quantum computers. They can be used to run quantum algorithms with which one can efficiently solve problems that seem intractable with usual computation. Quantum computation has many potential applications, e.g., in material science, quantum chemistry, and combinatorial optimization. In this course, we aim to develop a deeper understanding of quantum phenomena. In order to do so, we start with some basics from classical probability and information theory. Then, we first see some non-classical phenomena, such as the no-cloning theorem (quantum information cannot be copied) and entanglement, to name just two basic examples. Potential topics for the end of the course are selected quantum algorithms, examples from quantum communication, and quantum error correction. This course has an emphasis on conceptual aspects of the topic, and we try to avoid technical discussions. Nevertheless, a solid mathematical understanding is required. The first part of the seminar requires no prior knowledge of quantum mechanics, which can be obtained in the course `Introduction to Quantum Computing' in parallel.
Area classification:
Studiendekanat Elektrotechnik, Informatik und Mathematik
Stud.IP informationen about this course:
Home institute: Studiendekanat Elektrotechnik, Informatik und Mathematik (E)
Registered participants in Stud.IP: 7
Documents: 9

Supervised Theses

ongoing
completed

2021

  • Hund, P. (2021). Modellierung eines elektrischen Netzes zur Demonstration des Einflusses von virtueller Trägheit durch umrichterbasierte Energieanlagen.

  • Hund, P. (2021). Koordinierte Bereitstellung von virtueller Trägheit durch erneuerbare umrichterbasierte Energieanlagen in Verteilnetzen mithilfe von künstlicher Intelligenz.

  • Möller, P. (2021). Erfassung der Knotenspannung in Niederspannungsnetzen auf Basis von dezentralen Messeinrichtungen mithilfe von Machine learning.

  • Plant, R. (2021). Estimation of Power System Inertia in an Inverter-Dominated Distribution Grid Using Machine Learning.

2020

  • Dressel, M. (2020). Modellierung der Zustandsschätzung eines elektrischen Netzes mit Hilfe von Graph neuronalen Netzen.

  • Schmidt, M. (2020). Vorhersage von zuverlässig bereitstellbarer Regelleistung aus Erneuerbaren Energien mithilfe von neuronalen Netzen.

TU Hamburg
Institute of Electrical Power and Energy Technology (ieet) E-6
Prof. Dr.-Ing. Christian Becker
Harburger Schloßstraße 36
21079 Hamburg
E-mail : ieet(at)tuhh.de
Phone : +49 40 42878 3213
Fax : +49 40 42878 2382
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