Merten Schuster, M.Sc.
Mitarbeiter am elenia: 2019 bis 2025
Studentic theses Finished Grid integration of a 2.0 MW safety power system in the power supply grid of VW Kraftwerk GmbH Further development of a self-learning reactive power control in an active reactive power management Development of a method for cross-process quality analysis in the congestion management processes of German transmission system operators Forecasting reactive power behavior in electrical energy systems using a machine-learning forecasting method Development of grid operation-dependent reactive power provision for converter-coupled renewable energy systems Implementation of a data-driven analysis and evaluation for real reactive power management in the distribution grid Exploratory data analysis of datasets across voltage levels and grid operators Investigation of machine learning models for time series forecasting in electrical energy systems Design and application of a data preprocessing process for machine-learning forecasting methods Development of a simulation environment for testing fallback strategies within an active reactive power management Development and validation of a methodology for predicting reactive power in electric power systems using a machine-learning forecasting technique Development of a tool for data-driven analysis and evaluation of grid data across voltage levels and grid operators Implementation of a state estimation in the scope of a cross-voltage level grid operation Investigation of the increase of resource efficiency in the balancing system of wastewater plants through sector coupling Development and investigation of fallback strategies in the case of an ICT failure in the distribution grid Modeling and evaluation of statistical and machine learning Methods for forecasting electric spot market prices Design and evaluation of a methodology to model feed-in and load time series from aggregated measurement time series Investigation of the legal and regulatory framework for reactive power management across voltage levels and grid operators Development and validation of an evaluation scheme for the provision of ancillary services by renewable energies Approaches for modeling grid and simulation scenarios across voltage levels in the context of future grid developments in Germany Development and validation of a methodology for forecasting reactive power demands in electrical power grids
Publications Eichner, S., Schuster, M., Köppe, H., Sass, F., Grab, R.: Development of a pricing model for the reactive power supply via STATCOM capability of a real PV power plant Köppe, H., Schuster, M., Engel, B.: Improving power system efficiency: a case study on optimized reactive power management in high-voltage grids Türk, J., Schuster, M., Köppe, H., Engel, B.: Development approach of a volt-var control for inverter-coupled renewable energy plants using deep reinforcement learning Müller, N., Reinköster, N., Di-Modica, G., Schuster, M., Engel, B.: Simulation-aided evaluation of regulatory requirements for control in the low-voltage grid ISBN 978-3-8007-6134-0 Schuster, M., Pape, M., Studt, J., Bollhorn, S., Engel, B.: Design of a Data Driven Reactive Power Forecasting for an Active Cross-Voltage Level Reactive Power Management ,
ETG Congress 2023, Kassel, 25.-26. Mai 2023, S. 1-6. DOI: https://ieeexplore.ieee.org/document/10172984 Schuster, M., Kufeld, ., Köppe, H., Engel, B.: Development Approach for Short-term Forecasting of Reactive Power at the Interface Distribution and Transmission Grid ISBN 978-380-075-549-3 Studt, J., Schuster, M., Herr, H., Hadlak, M., Engel, B.: Electricity Spot Price Forecast: An in-depth analysis of different machine learning methods Grab, R., Köppe, H., Schuster, M.: PV-Wind-Symbiose - Ausnutzung der sich ergänzenden Eigenschaften von PV- und Wind-Kraftwerken hinsichtlich Spannungsqualität und der Bereitstellung von Wirk- und Blindleistung: Schlussbericht zum Verbundvorhaben , Fraunhofer ISE , Jg.(2019). DOI: 10.2314/KXP:1693034069 Köppe, H., Schuster, M., Grab, R., Engel, B.: Reactive Power Provision with Distributed Energy Resources: Limitations, Potentials and Losses
