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A Generic Data Model for Describing Flexibility in Power Markets

Author

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  • Paul Schott

    (Project Group Business & Information Systems Engineering of the Fraunhofer FIT, 95444 Bayreuth, Germany)

  • Johannes Sedlmeir

    (Project Group Business & Information Systems Engineering of the Fraunhofer FIT, 95444 Bayreuth, Germany)

  • Nina Strobel

    (Institute of Production Management, Technology and Machine Tools, Technische Universität Darmstadt, 64287 Darmstadt, Germany)

  • Thomas Weber

    (Institute of Production Management, Technology and Machine Tools, Technische Universität Darmstadt, 64287 Darmstadt, Germany)

  • Gilbert Fridgen

    (FIM Research Center, University of Bayreuth Project Group Business & Information Systems Engineering of the Fraunhofer FIT, 95444 Bayreuth, Germany)

  • Eberhard Abele

    (Institute of Production Management, Technology and Machine Tools, Technische Universität Darmstadt, 64287 Darmstadt, Germany)

Abstract

In this article, we present a new descriptive model for industrial flexibility with respect to power consumption. The advancing digitization in the energy sector opens up new possibilities for utilizing and automatizing the marketing of flexibility potentials and therefore facilitates a more advanced energy management. This requires a standardized description and modeling of power-related flexibility. The data model in this work has been developed in close collaboration with several partners from different industries in the context of a major German research project. A suitable set of key figures allows for also describing complex production processes that exhibit interdependencies and storage-like properties. The data model can be applied to other areas as well, e.g., power plants, plug-in electric vehicles, or power-related flexibility of households.

Suggested Citation

  • Paul Schott & Johannes Sedlmeir & Nina Strobel & Thomas Weber & Gilbert Fridgen & Eberhard Abele, 2019. "A Generic Data Model for Describing Flexibility in Power Markets," Energies, MDPI, vol. 12(10), pages 1-29, May.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:10:p:1893-:d:232300
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    References listed on IDEAS

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    Cited by:

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    3. Alejandro Tristán & Flurina Heuberger & Alexander Sauer, 2020. "A Methodology to Systematically Identify and Characterize Energy Flexibility Measures in Industrial Systems," Energies, MDPI, vol. 13(22), pages 1-35, November.
    4. Cantu Rodriguez, Roman & Palacios-Garcia, Emilio J. & Deconinck, Geert, 2024. "Redesign for flexibility through electrification: Multi-objective optimization of the operation of a multi-energy industrial steam network," Applied Energy, Elsevier, vol. 362(C).
    5. Körner, Marc-Fabian & Sedlmeir, Johannes & Weibelzahl, Martin & Fridgen, Gilbert & Heine, Moreen & Neumann, Christoph, 2022. "Systemic risks in electricity systems: A perspective on the potential of digital technologies," Energy Policy, Elsevier, vol. 164(C).
    6. Rusche, Simon & Weissflog., Jan & Wenninger, Simon & Häckel, Björn, 2023. "How flexible are energy flexibilities? Developing a flexibility score for revenue and risk analysis in industrial demand-side management," Applied Energy, Elsevier, vol. 345(C).
    7. Martin Bichler & Hans Ulrich Buhl & Johannes Knörr & Felipe Maldonado & Paul Schott & Stefan Waldherr & Martin Weibelzahl, 2022. "Electricity Markets in a Time of Change: A Call to Arms for Business Research," Schmalenbach Journal of Business Research, Springer, vol. 74(1), pages 77-102, March.
    8. Cezar-Petre Simion & Cătălin-Alexandru Verdeș & Alexandra-Andreea Mironescu & Florin-Gabriel Anghel, 2023. "Digitalization in Energy Production, Distribution, and Consumption: A Systematic Literature Review," Energies, MDPI, vol. 16(4), pages 1-30, February.
    9. Wanapinit, Natapon & Thomsen, Jessica & Weidlich, Anke, 2022. "Integrating flexibility provision into operation planning: A generic framework to assess potentials and bid prices of end-users," Energy, Elsevier, vol. 261(PB).
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