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

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
Massively Parallel Systems: Architecture and Programming
Untertitel:
This course is part of the module: Massiv parallele Systeme: Architektur und Programmierung
Semester:
WiSe 23/24
Veranstaltungstyp:
Vorlesung (Lehre)
Veranstaltungsnummer:
lv2936_w23
DozentIn:
Prof. Dr. Sohan Lal
Beschreibung:
This course will prepare students to understand parallel computer architecture, organization, and programming. The course starts with parallel computer classification and multithreading. It covers the architecture of centralized and distributed shared-memory parallel systems, multiprocessor cache coherence, snooping / directory-based cache coherence protocols, implementation, and limitations. Next, the students study interconnection networks and routing in parallel systems, synchronization, and memory consistency. To ensure the correctness of shared-memory multithreaded programs, independent of the speed of execution of its independent threads, the essential topics of memory consistency and synchronization will be covered in detail. As a case study, the architecture of a few accelerators such as GPUs will also be discussed in detail. Besides understanding the architecture and organization of parallel systems, programming them is also very challenging. The course will cover how to program massively parallel systems using API/libraries such as CUDA/OpenCL, and MPI/OpenMP. Problem-based Assignments/Project: There will be 3-4 assignments for project-based learning consisting of the following: Implement and compare different cache coherence protocols using a simulator or a high-level, event-driven simulation interface such as SystemC Programming massively parallel systems to solve computationally intensive problems such as password cracking using CUDA/OpenCL/MPI/OpenMP
Voraussetzungen:
Basic course on computer architecture and C/C++ programming.
Leistungsnachweis:
Assignments + 30 minutes oral exam.
ECTS-Kreditpunkte:
6
Weitere Informationen aus Stud.IP zu dieser Veranstaltung
Heimatinstitut: Institut für Massively Parallel Systems (E-EXK5)
In Stud.IP angemeldete Teilnehmer: 73
Anzahl der Postings im Stud.IP-Forum: 5
Anzahl der Dokumente im Stud.IP-Downloadbereich: 14

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.