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    1. Friedrich-Alexander-Universität
    2. Technische Fakultät
    3. Department Informatik
    Friedrich-Alexander-Universität Computer Science 7 CS7
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    Multi-sector coupled energy system modeling on a regional level

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    Multi-sector coupled energy system modeling on a regional level

    Logo ESM Regio

    Project Description

    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.

    Project Period

      2021-05-01 – 2024-04-30

    Project leader

      Reinhard German

    Project Participants

      Alexander Martin, Jürgen Karl, Marco Pruckner, Daniel Scharrer, Natalia Luna-Jaspe Roa, Kevin-Martin Aigner

    Contact

      Daniel Scharrer

    Sponsored by

      Bundesministerium für Wirtschaft und Technologie (BMWi)

    External Partners

    • Institut für Hoch­spannungs­technik, Energiesystem- und Anlagendiagnose – Hochschule für angewandte Wissenschaften Coburg
    • Energieagentur Nordbayern GmbH
    • Stadtwerke Bayreuth Holding GmbH
    • Bayern Innovativ Bayerische Gesellschaft für Innovation und Wissenstransfer mbH

    Related Publications

    •  
    • Aigner KM., Schaumann P., von Loeper F., Martin A., Schmidt V., Liers F.:
      Robust DC Optimal Power Flow with Modeling of Solar Power Supply Uncertainty via R-Vine Copulas
      In: Optimization and Engineering (2022)
      ISSN: 1389-4420
      DOI: 10.1007/s11081-022-09761-0
      URL: https://link.springer.com/article/10.1007/s11081-022-09761-0
      BibTeX: Download
    • Aigner KM., Bärmann A., Braun K., Liers F., Pokutta S., Schneider O., Sharma K., Tschuppik S.:
      Data-driven Distributionally Robust Optimization over Time
      In: INFORMS Journal on Optimization (2023)
      ISSN: 2575-1484
      DOI: 10.1287/ijoo.2023.0091
      URL: https://opus4.kobv.de/opus4-trr154/frontdoor/index/index/docId/496
      BibTeX: Download
    • Luna-Jaspe Roa N., Aigner KM., Kolb S., Karl J.:
      Modellierung des Wärmesektors und dessen Flexibilität für Simulationen gekoppelter Energiesysteme
      EnInnov2024 - 18. Symposium Energieinnovation 2024 (Graz, 2024-02-14 - 2024-02-16)
      Open Access: https://www.tugraz.at/fileadmin/user_upload/tugrazExternal/f560810f-089d-42d8-ae6d-8e82a8454ca9/files/lf/Session_E3/533_LF_Luna-Jaspe.pdf
      BibTeX: Download

    Links

      https://www.esm-regio.de
      https://cris.fau.de/converis/portal/Project/261431764
    Computer Science 7 (Computer Networks and Communication Systems)
    Friedrich-Alexander-Universität Erlangen-Nürnberg

    Martensstr. 3
    91058 Erlangen
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