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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
Applied Design Methodology in Mechatronics (VL)
Untertitel:
This course is part of the module: Applied Design Methodology in Mechatronics, Konstruieren und Gestalten (GTW MT BC T3.1), Mechanical Design Methodology
Semester:
SoSe 24
Veranstaltungstyp:
Vorlesung (Lehre)
Veranstaltungsnummer:
lv1523_s24
DozentIn:
Prof. Dr. Thorsten Kern
Beschreibung:
  • Systematic analysis and planning of the design process for products combining a multitude of disciplines
  • Structure of the engineering process with focus on engineering steps (task-definition, functional decomposition, physical principles, elements for solution, combination to systems and products, execution of design, component-tests, system-tests, product-testing and qualification/validation)
  • Creative methods (Basics, methods like lead-user-method, 6-3-5, BrainStorming, Intergalactic Thinking, … - Applications in examples all around mechatronics topics)
  • Several design-supporting methods and tools (functional strcutures, GALFMOS, AEIOU-method, GAMPFT, simulation and its application, TRIZ, design for SixSigma, continous integration and testing, …)
  • Evaluation and final selection of solution (technical and business-considerations, preference-matrix, pair-comparision), dealing with uncertainties, decision-making
  • Value-analysis
  • Derivation of architectures and architectural management
  • Project-tracking and -guidance (project-lead, guiding of employees, organization of multidisciplinary R&D departments, idea-identification, responsibilities and communication)
  • Project-execution methods (Scrum, Kanbaan, …)
  • Presentation-skills
  • Questions of aesthetic product design and design for subjective requirements (industrial design, color, haptic/optic/acoustic interfaces)
  • Evaluation of selected methods at practical examples in small teams
Leistungsnachweis:
605 - Mechanical Design Methodology<ul><li>605 - Mechanical Design Methodology: mündlich</li></ul><br>m1143 - Applied Design Methodology in Mechatronics<ul><li>p842 - Applied Design Methodology in Mechatronics: Subject theoretical and practical work</li></ul><br>m1540 - Konstruieren und Gestalten (GTW MT BC T3.1)<ul></ul>
ECTS-Kreditpunkte:
2
Weitere Informationen aus Stud.IP zu dieser Veranstaltung
Heimatinstitut: Institut für Mechatronik im Maschinenbau (M-4)
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 36
21079 Hamburg
E-mail : ieet(at)tuhh.de
Phone : +49 40 42878 3213
Fax : +49 40 42878 2382
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