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

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

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
Organizational Design for Innovation and Collaboration (VL)
Untertitel:
This course is part of the module: Business & Management
Semester:
WiSe 23/24
Veranstaltungstyp:
Vorlesung (Lehre)
Veranstaltungsnummer:
lv3123_w23
DozentIn:
Prof. Dr. Tim Schweisfurth
Beschreibung:

The course focuses on organizational designand collaboration engineering inside the boundaries of the firm: How canwe design/engineer an organization internally such that it favors innovation?

The class will cover the basics oforganizational design (universal problems of organizing), division of labor andintegration of effort in organizations (task division, task allocation,decomposability of tasks, specialization and customization, agency problems), neworganizational forms (novel forms of task division/allocation (e.g.self-selection), reward distribution, (e.g. user needs), information flow(virtual collaboration), incentivizing collaboration in firms (job design forcollaboration, collocation, shared rewards, job rotation, physical layout), incentivizinginnovation in firms (job design for innovation, resistance to innovation,experimentation and tinker time, intrinsic motivation, self-selection), authorityand Control (hierarchies, flat/tall organizations, holocracies, span ofcontrol, minimal chain of command), specialization and Coordination (functionalstructures, divisional structures, product team structures, organization ofinnovation and R&D), informal organizational structure and innovationculture (innovation culture, psychological safety, networks in organizations),coordination roles for innovation and collaboration (promotor model, boundaryspanners, technological gatekeepers), modularity and organizational designs (conway’slaw, mirroring of technological architectures, design structure matrices), geographicalaspects of collaborative innovation (innovation laboratories, spatial  layouts, technology and science parks,innovation clusters).


Leistungsnachweis:
tm3123 - Gestaltung innovativer und kollaborativer Organisationen (Vorlesung)<ul><li>p1912-2023 - Gestaltung innovativer und kollaborativer Organisationen: Klausur schriftlich</li></ul>
ECTS-Kreditpunkte:
2
Weitere Informationen aus Stud.IP zu dieser Veranstaltung
Heimatinstitut: Institute for Organizational Design and Collaboration Engineering (W-13)
In Stud.IP angemeldete Teilnehmer: 75
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.