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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 22a,
21079 Hamburg
Building HS22a, Room 2.002
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
NOT OFFERED - International Production Management and Enterprise Resource Planning: CERMEDES AG (SE)
Untertitel:
This course is part of the module: International Production Management and Enterprise Resource Planning: CERMEDES AG
Semester:
SoSe 24
Veranstaltungstyp:
Seminar (Lehre)
Veranstaltungsnummer:
lv1232_s24
DozentIn:
Prof. Dr. Christian Ringle
Beschreibung:

The course involves two main parts:

During the first part of the course, participants are provided with insights into the market for ERP-Software and are provided with knowledge on how ERP-implementation projects proceed and how these projects should ideally be managed from a theoretical and practical perspective. In addition, participants are provided with an understanding of business functions and processes by means of visiting the TUHH model factory. In the model factory, participants and are solving special business cases on the basis of group-specific tasks. Finally, participants are introduced into the basic functioning of ERP-Software referring to the most common system (SAP). Participants gain a basic understanding of implementing organizational data, master data and processes into the system. 

During the second phase of this course, the students work independently in groups on deepening challenges, which conceptually build up on the executed case studies from phase one. Using the knowledge from phase one, the students are able to transfer the theoretical knowledge on the practical execution of the challes in SAP. The results of the group work will be presented in phase two.
Leistungsnachweis:
621 - International Production Management and Enterprise Resource Planning: CERMEDES AG<ul><li>621 - International Production Management and Enterprise Resource Planning: CERMEDES AG: schriftliche Ausarbeitung</li></ul><br>622 - International Production Management and Enterprise Resource Planning: CERMEDES AG<ul><li>621 - International Production Management and Enterprise Resource Planning: CERMEDES AG: schriftliche Ausarbeitung</li><li>821 - Compulsory Course Work International Production Management and Enterprise Resource Planning: CERMEDES AG - Presentation: Presentation</li><li>822 - Compulsory Course Work International Production Management and Enterprise Resource Planning: CERMEDES AG - Written Essay: schriftliche Ausarbeitung</li></ul><br>m1255 - International Production Management and Enterprise Resource Planning: CERMEDES AG<ul><li>821 - Compulsory Course Work International Production Management and Enterprise Resource Planning: CERMEDES AG - Presentation: Presentation</li><li>822 - Compulsory Course Work International Production Management and Enterprise Resource Planning: CERMEDES AG - Written Essay: schriftliche Ausarbeitung</li><li>p1044-2022 - International Production Management and Enterprise Resource Planning: CERMEDES AG: Subject theoretical and practical work</li></ul>
ECTS-Kreditpunkte:
6
Weitere Informationen aus Stud.IP zu dieser Veranstaltung
Heimatinstitut: Management and Decision Sciences [MDS] (W-9)
In Stud.IP angemeldete Teilnehmer: 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 22a
21079 Hamburg
E-mail : ieet(at)tuhh.de
Phone : +49 40 42878 3213
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