Marco Pruckner

Prof. Dr.-Ing. Marco Pruckner

Junior Professorship in Computer Science for Energy Systems, Head of Group Smart Energy

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

Room: Room -----

Short Biography

Marco Pruckner is a Junior Professor in Computer Science for Energy Systems at the University of Erlangen-Nuremberg. He received his Ph.D. degree in engineering (Dr.-Ing.) and his M.Sc. degree in mathematics (Dipl. Math. Univ.) from the University of Erlangen-Nuremberg in 2015 and 2011, respectively. Marco’s research focuses on energy system modeling on different scales, vehicle grid integration and smart control of energy systems based on reinforcement learning.

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  • Multi-sector coupled energy system modeling on a regional level

    (Third Party Funds Group – Overall project)

    Term: 2021-05-01 - 2024-04-30
    Funding source: Bundesministerium für Wirtschaft und Technologie (BMWi)
    Reducing primary energy use and greenhouse gases are central goals of the energy transition. However, switching from fossil to regenerative energy sources is not enough to achieve them. An overarching view and optimization of the different sectors of the energy system - electricity, gas, heat and transport - can significantly advance the further development of the energy system in Germany. Potential exists above all on a regional level.

    The goal of the ESM-Regio project - short for "Multisectoral Coupled Energy System Modeling on a regional level" - is to create a temporally high-resolution energy system model on a county level that takes into account the four sectors of electricity, gas, heat and transport as well as the required interface technologies. A key feature of the project is a cross-sector model logic. Suitable simulation methods enable a holistic analysis and optimization of the system operation under consideration of the four relevant sectors of the energy system.

  • Control of energy systems based on self-learning algorithms

    (Own Funds)

    Term: since Tools.php2017-05-16
    The worldwide expansion of decentralized generation units, such as photovoltaic systems and wind power plants, means that the generation of electrical energy depends on the fluctuating supply of renewable energy sources. In the project "Control of energy systems based on self-learning algorithms", new self-learning control algorithms for energy systems are investigated and compared with classical control algorithms. Models written in Python will make it possible to create several self-learning agents and simulate them in a common environment.

    It is also planned to model further components such as electric charging stations in order to take into account the influence of electromobility on the power system.

  • Pal-Grid: A Comprehensive Simulation Framework for the Palestinian Power Grid

    (Third Party Funds Single)

    Term: 2017-03-01 - 2019-02-28
    Funding source: Bundesministerium für Bildung und Forschung (BMBF)

    The aim of this project is to develop a comprehensive simulation framework for the Palestinian electric power network system with a focus on a specific area. The simulation framework should be able to capture the different aspects of the future energy supply.

    The project will provide two levels of abstraction. The first simulation level will be very abstract and it helps the authorities, and especially the energy regulatory authority to take decisions to boost the penetration of renewable energy resources (RES) and improve the Palestinian power grid. Thus, the most important political, economic and technical characteristics and interactions will be addressed. This level of abstraction will provide the essential tools to compare and evaluate different scenarios to enhance of the Palestinian power grid for long planning horizons. The second model will be particularly characterized by a detailed modeling of the different components of a power system. Therefore, the power grid as well as the communication network will be addressed in this model. This will enable exploring ICT-enabled power grid application, i.e., the emerging smart grid applications.

  • 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).