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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
Sustainable Innovation Management (VL)
Untertitel:
This course is part of the module: Innovation Management, Sustainable Innovation Management
Semester:
SoSe 24
Veranstaltungstyp:
Vorlesung (Lehre)
Veranstaltungsnummer:
lv1937_s24
DozentIn:
Cornelius Herstatt, Stephan Bergmann, Luise Degen
Beschreibung:

The course aims to equip studentswith an understanding of key issues in the management of innovation and anappreciation of the relevant skills needed to manage innovation at bothstrategic and operational levels. It provides evidence of different approachesbased on leading research, real world examples and experiences of firms andorganizations from around the world.

The management of innovation is oneof the most important and challenging aspects of modern organization.Innovation is a fundamental driver of competitiveness and it plays a large partin improving quality of life. Innovation, and particularly technologicalinnovation, is inherently difficult, uncertain and risky, and most newtechnologies fail to be translated into successful products and services. Giventhis, it is essential that students understand the strategies, tools and techniquesfor managing innovation, which often requires a different set of managementknowledge and skills from those employed in everyday business administration.The course itself draws upon research activities of the Institute forTechnology and Innovation Management at the TUHH (www.tuhh.de/tim)

Lecture Topics:

  • The Management of (Technological)Innovation
  • Strategy and Organization forInnovation
  • Managing the Innovation Process
  • Innovation in the Age of CircularEconomy (C2C)
  • Market-Research for Innovationand Design-thinking
  • Capturing value from R&D,Open Innovation and IP
  • Creativity and mindfulness in Innovation
Leistungsnachweis:
615 - Innovation Management<ul><li>615 - Innovation Management: Klausur schriftlich</li></ul><br>m1360-2021 - Sustainable Innovation Management<ul><li>p1269-2021 - Sustainable Innovation Management: Klausur schriftlich</li></ul>
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 Dokumente im Stud.IP-Downloadbereich: 19

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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