Open Theses

 

Here you will find offers for theses at the ACS. These are sorted by our six research teams.

 

Automation, Interoperability and Resilience	Degree	Language	Contact
A Data-Driven Technique for Dynamic States Estimation Using Gaussian Processes	Master	en	Priyanka Arkalgud Ganeshamurthy
Hosting Capacity and Sensitivity Analysis for Distribution Grids	Master	en	Mirko Ginocchi
Quantification of Resilience in Current and Future Interdependent Power Systems	Master	en	Nikolaus Wirtz
A Dynamic Phasor based Dynamic State Estimation for Converter Driven Grids	Master	en	Priyanka Arkalgud Ganeshamurthy
Interdependency and Uncertainty in a Graph-Based Approach to Complex Power System Modelling and Analysis	Master	en	Nikolaus Wirtz Abraham Obinwanne Ezema
Implementation of Blockchain-based Virtual Redundancy as a Novel Distribution Power System Protection concept	Master	en	César Cazal Thanakorn Penthong
Data-Driven Technique for Dynamic States Estimation Using Gaussian Processes	Master	en	Priyanka Ganeshamurthy
Sensitivity Analysis in power systems applications	Master	en	Mirko Ginocchi
Validation of representative distribution networks based on Sensitivity Analysis	Master	en	Mirko Ginocchi
Implementation and interoperability analysis of a distribution system automation in real time application	Bachelor/Master	en	Amir Ahmadifar Mirko Ginocchi

 

Advanced Control Methods for Power Systems and HiL	Degree	Language	Contact
Faster Big Data generation and analysis for AI-assisted design of MVDC control and protection system	Master	en	Jaqueline Cabanas Ramos
Knowledge-based Control of Load Frequency in Microgrid System using Reinforcement Learning	Master	en/de	Ahmed Tijani Salawudeen
Fault-Observer-based Distributed Control of Load Frequency in Multiple Area AC Microgrid System	Master	en/de	Ahmed Tijani Salawudeen
Functional Modelling of Multi-Vendor HVDC Systems	Bachelor	en/de	Ilka Jahn
Sensitivity Analysis of Hardware and Software Parameters in HVDC Protection	Master	en/de	Ilka Jahn
Distributed Model Predictive Secondary Control for AC/DC Microgrid	Master	en	Asimenia Korompili
Distributed OPF Algorithm for System-Level Control of DC Distribution Grids Considering Uncertainties	Master	en	Asimenia Korompili

 

Simulation Methods and Automation Software Solutions	Degree	Language	Contact
Co-simulation of Power Systems using Shifted-Frequency	Bachelor/Master	de/en	Andres Acosta Jan Dinkelbach
Improved setting up of Distributed Co-simulation scenarios for Power Systems with Hardware in the Loop (HIL)	Bachelor/Master	de/en	Andres Acosta Jan Dinkelbach
Measurement devices models with open-source simulator DPSim	Master	en	Leonardo Carreras
Load and power forecasting in electrical power systems using AI/ML	Master	en	Leonardo Carreras

 

Energy Flexibility Management and Optimization	Degree	Language	Contact
Review of open-source energy modeling and optimization frameworks for urban energy systems	Bachelor/Master	de/en	Sebastian Uerlich
Techno-Economic Analysis of Alternative Microgrid Configurations and Domains for V2X Applications	Bachelor	en	Erdem Gümrükcü
Co-Simulation for Smart Grid Oriented EV Charging	Master	en	Erdem Gümrükcü Felix Wege

 

Energy Management Systems and Data Analytics	Degree	Language	Contact
Multi-stage GNN-based reinforcement learning solution for real-time operation of distribution grid	Master	en	Chijioke Eze
Pre-Trained Deep Learning Model for Semantic Annotation in Energy Domain	Master	de/en	Zhiyu Pan
Entwicklung eines integrierten Standardschemas für die gemeinsame Ontologie zur Unterstützung der Big-Data-Interoperabilität	Master	de/en	Zhiyu Pan
Development of Common Ontology Integrated Standard Schema to Support Big Data Interoperability	Master	de/en	Zhiyu Pan
Developing a Flexible Interface for Agent-Behaviors in Multi-Agent-System Simulations of Electrical Power Systems	Master	de/en	Katharina Wehrmeister
Distributed Active Voltage Control via Decision Transformer-based MARL Policy	Master	en	Chijioke Christian Eze
Explainable Deep Sequence Model for Energy Forecasts	Master	en	Abraham Obinwanne Ezema
Data and Ontology Model Definition in Energy Systems using Deep Reinforcement Learning	Master	en	Charles Emehel