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Dr.-Ing. David Steber

Department of Computer Science
Chair of Computer Science 7 (Computer Networks and Communication Systems)

Room: Room 06.150
Martensstr. 3
91058 Erlangen

Short Biography

From 2008, David Steber studied Business Administration & Engineering with specialization in electrical power engineering at the RWTH in Aachen. After his successful graduation in 2014 he worked as a project manager at the largest distribution grid operator in Baden-Württemberg. 2015 he decided to return to university and started his doctorate in the field of simulation of distributed energy storage systems as a research assistant at the chair of Computer Science 7 located at the FAU Erlangen-Nürnberg.

More Information

  • Combined Optimization, Simulation and Grid Analysis of the German Electrical Power System in an European Context

    (Third Party Funds Group – Overall project)

    Term: 2016-10-01 - 2019-09-30
    Funding source: Bundesministerium für Wirtschaft und Technologie (BMWi)
    Germany decided to reorganize its energy supply system in a sustainable way by initiating the energy transition (Energiewende). One of its main targets is to be one of the most environmentally friendly and energy-conserving economies worldwide with competitive energy prices at the same time. This requires the support of all-embarrassing analytical systems, which take into account the technical, market and regulatory framework at once. Existing energy system analysis models often neglect or simplify the modeling of the electrical grid, which motivated the preliminary multidisciplinary work of the chairs of the FAU Erlangen-Nürnberg in the recent years.

    A holistic system-oriented modeling approach for the electrical power supply system in Germany was initially developed with a focus on Bavaria. The model of the German electrical power supply system includes the transmission grid, conventional power plants and feed-in from renewables concerning the current market mechanisms in Germany. With the developed model it is possible to derive statements about grid and storage expansion or the development of CO2 emissions for the federal state Bavaria. The overall model includes sub-models for optimization (determination of cost-optimal expansion scenarios), for simulation (stochastic simulation of different scenarios with high temporal resolution and technical detail) and grid analysis (quasi-stationary AC load flow calculations) for checking the required grid planning criteria and stable system operation.

    Within the research project KOSiNeK funded by the Federal Ministry for Economic Affairs and Energy (BMWi) we now extend the existing holistic system-oriented modeling approach for the German electric energy system to derive statements about the future development of the system within the European context. This includes both the evaluation of net expansion scenarios and the simulation and analysis of regulatory frameworks. In order to cope with the increasing complexity of the problem, new approaches from the fields of mathematics, computer sciences and net analysis are necessary, which includes aggregation and decomposition techniques, hierarchical multipoint model approaches as well as probabilistic methods to determine the probability of occurrence of certain conditions. This leads to models of high complexity. To take this into account, the approaches from mathematics, computer science and grid analysis will also be coupled iteratively. This enables displaying technical and economic aspects with regard to the control of power plants in a very detailed manner as well as considering grid-regulations in order to guarantee a safe electrical power supply. In addition, it is possible to examine energy markets in an European context including their regulatory framework. The flexible and component-based model construction allows the influence of new market mechanisms such as dividing Germany into price zones or changing market conditions or funding mechanisms with a detailed, agent-based market model. For the integrated power grid analysis, the continental European transmission grid is integrated by network equivalents. A novel probabilistic approach will also be developed to evaluate the grid expansion scenarios.

    The project KOSiNeK (project number 03ET4035) is funded by the 6th energy research program of the German Federal Ministry for Economic Affairs and Energy (BMWi).

  • Koordinierte Kleinspeicher im Verteilnetz der N-ERGIE Aktiengesellschaft (SWARM)

    (Third Party Funds Single)

    Term: 2015-01-01 - 2017-12-31
    Funding source: Industrie
    Im Rahmen des Kooperationsprojektes SWARM der N-ERGIE AG und dem Energie Campus Nürnberg (EnCN) beschäftigt sich unter anderem der Lehrstuhl für Informatik 7 (Rechnernetze und Kommunikationssysteme) mit den Fragestellungen, unter welchen Bedingungen Privathaushalte in innovative Stromspeicher investieren, wie sich diese Speicher auf die Stabilität des Stromnetzes auswirken und welchen ökonomischen Nutzen sie aus Sicht des Netzbetreibers bzw. der Privathaushalte schaffen.

    Übergeordnetes Ziel der Untersuchungen ist es, Erkenntnisse über vernetzte Speicher zu gewinnen und zu vertiefen.Das von der Caterva GmbH entwickelte Energiespeichersystem (ESS) mit einer Gesamtleistung von 20 kW und einer Bruttokapazität von 21 kWh richtet sich an Privathaushalte, die deutlich mehr als die durchschnittlich üblichen 30 Prozent ihres selbst erzeugten PV-Stroms nutzen möchten, da das ESS eine hohe Deckung des individuellen Strombedarfs aus Eigenerzeugung ermöglicht.

    Die Innovation des Systems liegt jedoch in seiner zweiten Funktion: Die Energiespeichersysteme können sich zu einem virtuellen Großspeicher vernetzen, der am Primärregelleistungsmarkt teilnimmt und damit eine Stabilisierungsfunktion im Stromnetz übernimmt. Der virtuelle Großspeicher speichert Strom bei einem Überangebot im Netz und speist umgekehrt bei Strombedarf in das Netz ein.Der Lehrstuhl für Informatik 7 (Rechnernetze und Kommunikationssysteme) entwickelt ein Simulationsmodell eines Kleinspeicher-Verbunds. Ziel des Modells ist es, die technischen Auswirkungen der Speicher auf die Netze zu ermitteln, sowie den ökonomischen Nutzen sowohl für die beteiligten Privathaushalte als auch für das gesamte Energiesystem zu identifizieren.