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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
zur Veranstaltung in Stud.IP Studip_icon
Current issues in behavioral economics
Semester:
WiSe 23/24
Veranstaltungstyp:
Seminar (Lehre)
Veranstaltungsnummer:
lv2993
DozentIn:
Timo Heinrich, Anika Bittner
Beschreibung:
The goal of the seminar is to discuss current issues in behavioral and to shed light on their relationship to economic theory and our own behavior. Students will first read a current popular science book (in English) as well as the relevant scientific literature. Then the individual topics will be presented and critically discussed during the seminar. Furthermore, students will develop individual research questions. This term, we will read the following book: Thaler, R. H. (2016). Misbehaving: The making of Behavioral Economics. W.W. Norton & Company, New York. Available at the university library: https://katalog.tub.tuhh.de/Record/1621785726
Voraussetzungen:
None
Lernorganisation:
- First meeting (Introduction to course and procedures): October 17, 2023 - Second meeting (Questions and clarifications): October 24, 2023 - Start date of the presentations and comments: November 14, 2023 In each session there will be one presentation, followed by the comments.
Leistungsnachweis:
Presentation: You will work on a section of the book by Thaler (2016). Allocation of the topics will be done via Stud.IP. Details will be announced in the first meeting. Evaluation will be based on the following elements: 20 min group presentation (up to 3 students) and 10 min comment. You can find more information in uploaded syllabus.
Sonstiges:
Admission
You can sign up to the course in Stud.IP. Please note that you are expected to attend the first session, otherwise we may sign you out of the course in order to grant admission to students from the waiting list.
In order to participate in the course, you will have to select a section to present in the group presentation and to discuss in the comment. Please make your section selections as soon as possible after the first meeting (October 18, 2023 at 12:00 noon), but at the latest by the end of October 31, 2023. Later selections will not be accepted. Procedures will be explained in the first meeting.
ECTS-Kreditpunkte:
2
Weitere Informationen aus Stud.IP zu dieser Veranstaltung
Heimatinstitut: Institut für Digital Economics (W-5)
In Stud.IP angemeldete Teilnehmer: 27
Anzahl der Dokumente im Stud.IP-Downloadbereich: 1

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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