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IEET > Staff > Research Assistants > Johannes Heise, M.Sc.

Johannes Heise

M.Sc.
Research Assistant

Contact

Johannes Heise, M.Sc.
E-6 Elektrische Energietechnik
  • Elektrische Energietechnik
Harburger Schloßstraße 36,
21079 Hamburg
Building HS36, Room C3 0.009
Phone: +49 40 42878 4099
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Research Project

iNeP
Integrated network planning for the electricity, gas and heat sectors

iNeP

Integrated network planning for the electricity, gas and heat sectors

Federal Ministry for Economic Affairs and Climate Action (BMWK); Duration: 2021 to 2026

to the project page

Publications

TUHH Open Research (TORE)

2023

2022

2021

Courses

Stud.IP
link to course in Stud.IP Studip_icon
Seminare.EIM: Seminar on Electromagnetic Compatibility and Electric Power Systems (Bachelor/Master-ET)
Semester:
WiSe 22/23
Course type:
Seminar
Lecturer:
Prof. Dr.-Ing. Christian Becker, Dr. Anna Katharina Kirf, Kathleen Potzahr, Prof. Dr. sc. techn. Christian Schuster, Marwan Mostafa, M.Sc., Mirco Woidelko, M.Sc., M.A., Dr. Cheng Yang, Christoph Klie, M.Sc., Johannes Heise, M.Sc., Dr.-Ing. Jan-Peter Heckel, Simon Stock, M.Sc., Hanko Ipach, M.Sc., Robert Annuth, M.Sc., Béla Wiegel, M.Sc., Tom Steffen, M.Sc.
Description:
Due to the energy transition, an increasing number of renewable energy plants are installed and connected to the grid. Their integration into the existing grid structure leads to challenging problems, which need to be solved to keep the grid stable. In addition to the conventional methods, the increasing availability of computational power allows to explore more computationally expensive algorithms and techniques. Besides optimization algorithms, machine learning approaches have gained popularity in the field of power engineering. Machine learning is a very diverse approach also used in multiple other disciplines and can be tailored to solve various problems. It offers a broad variety of techniques, networks, and algorithms with multiple advantages. In this joint seminar, the different applications for optimization techniques and machine learning in electrical energy systems are presented and discussed. The Seminar is open for Bachelor and Master Students in the electrical engineering program of TUHH. PhD students from both Institutes present their current research, while Bachelor/Master students give presentations on topics related to either power technology or electromagnetic compatibility.
Area classification:
Studiendekanat Elektrotechnik, Informatik und Mathematik
Stud.IP informationen about this course:
Home institute: Studiendekanat Elektrotechnik, Informatik und Mathematik (E)
Registered participants in Stud.IP: 33
Postings: 2
Documents: 4

Supervised Theses

ongoing

2024

  • Westphal, M (2024). Optimierte Planung eines gekoppelten Verteilnetzes unter der Berücksichtigung flexibler Komponenten.

2023

  • Hülfenhaus, V (2023). Modellierung und Planung eines urbanen sektorgekoppelten Verteilnetzes.

completed

2023

  • Körber, C (2023). Quantifizierung und Modellierung von Flexibilitätsoptionen im Mittelspannungsverteilnetz für eine optimierte Netzplanung.

  • Oboreh, J (2023). Einsatz von Gas-gefeuerten Blockheizkraftwerken zur Stabilisierung des Stromnetzes bei hoher Durchdringung von Wärmepumpen.

  • Velikov, S (2023). Entwicklung und Parametrisierung eines Wärmepumpen- und Speichermodells für die Netzberechnung und -planung.

  • Westphal, M (2023). Aggregation von Flexibilitäten im Niederspannungsnetz zur Netzplanung unter Berücksichtigung der Auslastung von Betriebsmitteln.

2022

  • Albrecht, J. P. (2022). Entwicklung einer netzdienlichen Regelungsstrategie für einen Elektrolyseur im Verteilnetz.

  • Barthelme, J. (2022). Technisch-ökonomische Systemmodellierung und -anlayse eines urbanen Quatiers hinsichtlich des Einsatz von Wasserstoff als primärer Energieträger.

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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