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Institute of Electrical Power and Energy Technology
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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
Technology Management (VL)
Untertitel:
This course is part of the module: Technology Management
Semester:
WiSe 23/24
Veranstaltungstyp:
Vorlesung (Lehre)
Veranstaltungsnummer:
lv849_w23
DozentIn:
Cornelius Herstatt, Johanna Zeller
Beschreibung:

The role of technology for the competitive advantage of the firm and industries; Basic concepts, models and tools for the management of technology; managerial decision making regarding the identification, selection and protection of technology (make or buy, keep or sell, current and future technologies). Theories, practical examples (cases), lectures, interactive sessions and group study.

This lecture is part of the Module Technology Management and can not separately choosen.

TeilnehmerInnen:
This module has a limited capacity of 40 seats. Until the end of the registration period you can only reserve a spot on the waiting list. You have to attend the mandatory introductory session on 24th of October to be able to attend the course.
Voraussetzungen:
Bachelor knowledge in business management.
Leistungsnachweis:
To pass this module, every student has to a) give one presentation during the Übung or Seminar, b) give their fellow students feedback for their presentation once, and c) pass the written exam at the end of the semester.
Sonstiges:
REGISTRATION PROCESS: Until the end of the registration period you can only register on the waiting list (FOR BOTH LECTURE AND SEMINAR). We will upload the final enrolment list around the the 15th of October.
If you don't get a spot right away there is still the chance of getting a spot later if you are on the waiting list and students don't attend the mandatory introductory session on 24th of October. You will get a notification if you can join the course then.
As every year, we will try our best to make sure that every student can at least participate one of the two modules Technology Management or Product Planning.
ECTS-Kreditpunkte:
3
Weitere Informationen aus Stud.IP zu dieser Veranstaltung
Heimatinstitut: Institut für Technologie u. Innovationsmanagement (W-7)
In Stud.IP angemeldete Teilnehmer: 41
Anzahl der Postings im Stud.IP-Forum: 2
Anzahl der Dokumente im Stud.IP-Downloadbereich: 14

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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