IEET: Simon Stock

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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

E-mail: simon.stock@tuhh.de

Personal Homepage

Research Projects

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

Reinforcement learning based coordination of virtual inertia provision from inverter-dominated distribution grids
Stock, Simon; Babazadeh, Davood; Hund, Philipp; Becker, Christian
32nd IEEE International Symposium on Industrial Electronics (ISIE 2023)
Publisher DOI
Bayesian physics-informed neural networks for robust system identification of power systems
Stock, Simon; Stiasny, Jochen; Babazadeh, Davood; Becker, Christian; Chatzivasileiadis, Spyros J.
IEEE Belgrade PowerTech (2023)
Publisher DOI

2022

Modelling the influence of virtual inertia in distribution systems on frequency stability
Hund, Philipp; Stock, Simon; Babazadeh, Davood; Becker, Christian
IEEE Power and Energy Student Summit 2022 and Power Electronics Student Summit: (2022)
Application of physics-based graph convolutional network in real-time state estimation of under-determined distribution grids
Stock, Simon; Dressel, Markus; Babazadeh, Davood; Becker, Christian
IEEE PES Innovataive Smart Grid Technologies Europe, ISGT Europe (2022)
Publisher DOI
Interconnected network protection systems - the basis for the reliable and safe operation of distribution grids with a high penetration of renewable energies and electric vehicles
Lorenz, Matthias; Pletzer, Tobias Markus; Schuhmacher, Malte; Sowa, Torsten; Dahms, Michael; Stock, Simon; Babazadeh, Davood; Becker, Christian; Jaeger, Johann; Lorz, Tobias; Dahlmanns, Markus; Fink, Ina Berenice; Wehrle, Klaus; Ulbig, Andreas; Linnartz, Philipp; Selimaj, Antigona; Offergeld, Thomas
CIRED Porto Workshop 2022: 548-552 (2022)
Publisher DOI
Real-time inertia estimation in an inverter-dominated distribution grid using a physics-informed recurrent neural network
Plant, Rebecca; Stock, Simon; Babazadeh, Davood; Becker, Christian
CIRED Porto Workshop 2022: 1403 (2022)
Publisher DOI

2021

Applications of artificial intelligence in distribution power system operation
Stock, Simon; Babazadeh, Davood; Becker, Christian
IEEE Access 9 : 150098-150119 (2021-11)
Open Access | Publisher DOI
A Modified Branch-Current Based Algorithm for Fast Low Voltage Distribution Grid State Estimation using Smart Meter Data
Ipach, Hanko; Stock, Simon; Becker, Christian
Von Komponenten bis zum Gesamtsystem fur die Energiewende (ETG-Kongress 2021)

Courses

Stud.IP

zur Veranstaltung in Stud.IP

Modellprüfung - Beweiser und Algorithmen

Untertitel:

Diese Lehrveranstaltung ist Teil des Moduls: Modellprüfung - Beweiser und Algorithmen

Semester:

SoSe 24

Veranstaltungstyp:

Vorlesung (Lehre)

Veranstaltungsnummer:

lv1979_s24

DozentIn:

Prof. Dr.-Ing. Görschwin Fey, Dr. Gianluca Martino

Beschreibung:

Correctness is a major concern in embedded systems. Model checking can fully automatically proof formal properties about digital hardware or software. Such properties are given in temporal logic, e.g., to prove "No two orthogonal traffic lights will ever be green."

And how do the underlying reasoning algorithms work so effectively in practice despite a computational complexity of NP hardness and beyond?

But what are the limitations of model checking?
How are the models generated from a given design?
The lecture will answer these questions. Open source tools will be used to gather a practical experience.

Among other topics, the lecture will consider the following topics:

Modelling digital Hardware, Software, and Cyber Physical Systems
Data structures, decision procedures and proof engines
- Binary Decision Diagrams
- And-Inverter-Graphs
- Boolean Satisfiability
- Satisfiability Modulo Theories
Specification Languages
- CTL
- LTL
- System Verilog Assertions
Algorithms for
- Reachability Analysis
- Symbolic CTL Checking
- Bounded LTL-Model Checking
- Optimizations, e.g., induction, abstraction
Quality assurance

Leistungsnachweis:

695 - Modellprüfung - Beweiser und Algorithmen<ul><li>695 - Modellprüfung - Beweiser und Algorithmen: mündlich</li></ul><br>m1397 - Modellprüfung - Beweiser und Algorithmen<ul><li>p1309 - Modellprüfung - Beweiser und Algorithmen: mündlich</li><li>vl360 - Verpflichtende Studienleistung Modellprüfung - Beweiser und Algorithmen - Fachtheoretisch-fachpraktische Studienleistung: Fachtheoretisch-fachpraktische Studienleistung</li></ul>

ECTS-Kreditpunkte:

6

Weitere Informationen aus Stud.IP zu dieser Veranstaltung

Heimatinstitut: Institut für Eingebettete Systeme (E-13)
In Stud.IP angemeldete Teilnehmer: 22
Anzahl der Dokumente im Stud.IP-Downloadbereich: 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.

Simon Stock

Contact

Simon Stock, M. Sc.

Research Projects

Applications of AI in distribution system operation

Applications of AI in distribution system operation

VeN²uS

VeN²uS

Networked grid protection systems - Adaptive and interconnected

Research Focus

Publications

TUHH Open Research (TORE)

2023

2022

2021

Courses

Stud.IP

Supervised Theses

ongoing

completed

2021

2020

TU Hamburg

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