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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
Advanced Topics in Management, Organization, and Human Resource Management (SE)
Untertitel:
This course is part of the module: Advanced Topics in Management, Organization, and Human Resource Management, Management, Organization and Human Resource Management
Semester:
WiSe 23/24
Veranstaltungstyp:
Seminar (Lehre)
Veranstaltungsnummer:
lv111_w23
DozentIn:
Prof. Dr. Christian Ringle, Janna Ehrlich
Beschreibung:

This course focuses on multinational firms and advanced issues of management, organizations, and human resource management. The students learn about the process and structure of a scientific article and deepen their knowledge while working in groupds. Selected topics focus, for example, on:

  • Human Resource Management: aging workforce, e-human resource management, generation X, Y, Z, human resource metrics/ analytics, recruitment/ selection/ hiring
  • Organisation: employee voice, exploration/ exploitation, networks, organisational identity, trust measurement
  • Management: change management, corporate social responsibility, firm performance measurement, gender, innovation management
Leistungsnachweis:
615 - Management, Organization and Human Resource Management<ul><li>615 - Management, Organization and Human Resource Management: schriftliche Ausarbeitung</li></ul><br>616 - Management, Organization and Human Resource Management<ul><li>615 - Management, Organization and Human Resource Management: schriftliche Ausarbeitung</li><li>815 - Management, Organization and Human Resource Management - Presentation: Presentation</li></ul><br>m543-2021 - Advanced Topics in Management, Organization, and Human Resource Management<ul><li>815 - Management, Organization and Human Resource Management - Presentation: Presentation</li><li>p40-2021 - Advanced Topics in Management, Organization, and Human Resource Management: schriftliche Ausarbeitung</li></ul><br>m543-2022 - Advanced Topics in Management, Organization, and Human Resource Management<ul><li>815 - Management, Organization and Human Resource Management - Presentation: Presentation</li><li>p40-2022 - Advanced Topics in Management, Organization, and Human Resource Management: Subject theoretical and practical work</li></ul>
ECTS-Kreditpunkte:
3
Weitere Informationen aus Stud.IP zu dieser Veranstaltung
Heimatinstitut: Management and Decision Sciences [MDS] (W-9)
In Stud.IP angemeldete Teilnehmer: 30
Anzahl der Postings im Stud.IP-Forum: 3
Anzahl der Dokumente im Stud.IP-Downloadbereich: 35

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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