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Institute of Electrical Power and Energy Technology
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Institute of Electrical Power and Energy Technology
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IEET > Staff > Research Assistants > Finn Nußbaum, M.Sc.

Finn Nußbaum

M.Sc.
Research Assistant

Contact

Finn Nußbaum, M. Sc.
E-6 Elektrische Energietechnik
  • Elektrische Energietechnik
Office Hours
nach Vereinbarung
Harburger Schloßstraße 36,
21079 Hamburg
Building HS36, Room C2 1.005
Phone: +49 40 42878 4092
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Research Project

KoLa
Optimized Load Management and Flexibility Coordination for Electrified Urban Public Transport

KoLa

Optimized Load Management and Flexibility Coordination for Electrified Urban Public Transport

Federal Ministry for Economic Affairs and Climate Action (BMWK); Duration: 2022 to 2026

to the project page

Publications

TUHH Open Research (TORE)

2024

2023

Courses

Stud.IP
link to course in Stud.IP Studip_icon
Machine Learning Applications in Electric Power Systems (VL)
Subtitle:
This course is part of the module: Machine Learning in Electrical Engineering and Information Technology
Semester:
SoSe 24
Course type:
Lecture
Course number:
lv3008_s24
Lecturer:
Prof. Dr.-Ing. Christian Becker, Dr. Davood Babazadeh, Simon Stock, M.Sc.
Description:

This part of the course focuses on how to utilize ML methods to model and operate electric power systems. Electric power systems consist of generation units such as PV, loads or consumers and the grid that connects those actors and supports to transport energy. This part of the course helps to understand the data-driven modelling of generation units (e.g. PV & fuel cells), modelling of load behavior, and to formulate and solve a state estimation problem for distribution grids using neural networks.

This part of the course includes lectures to introduce the basics that are followed by practical examples and coding.

Performance accreditation:
m1785-2022 - Machine Learning in Electrical Engineering and Information Technology<ul><li>p1778-2022 - Machine Learning in Electrical Engineering and Information Technology: mündlich</li></ul>
ECTS credit points:
1
Stud.IP informationen about this course:
Home institute: Elektrische Energietechnik (E-6)
Registered participants in Stud.IP: 3

Supervised Theses

ongoing
completed

2023

  • Kock am Brink, J. (2023). Entwicklung einer Engpassprognose für elektrische Verteilnetze mittels probabilistischer Verfahren.

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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