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Methodology for the Development of Virtual Representations within the Process Development Framework of Energy Plants: From Digital Model to Digital Predictive Twin—A Review

Author

Listed:
  • Martin Hammerschmid

    (Institute of Chemical, Environmental and Bioscience Engineering, TU WIEN, Getreidemarkt 9/166, 1060 Vienna, Austria)

  • Daniel Cenk Rosenfeld

    (Institute of Chemical, Environmental and Bioscience Engineering, TU WIEN, Getreidemarkt 9/166, 1060 Vienna, Austria)

  • Alexander Bartik

    (Institute of Chemical, Environmental and Bioscience Engineering, TU WIEN, Getreidemarkt 9/166, 1060 Vienna, Austria)

  • Florian Benedikt

    (Institute of Chemical, Environmental and Bioscience Engineering, TU WIEN, Getreidemarkt 9/166, 1060 Vienna, Austria)

  • Josef Fuchs

    (Institute of Chemical, Environmental and Bioscience Engineering, TU WIEN, Getreidemarkt 9/166, 1060 Vienna, Austria)

  • Stefan Müller

    (Institute of Chemical, Environmental and Bioscience Engineering, TU WIEN, Getreidemarkt 9/166, 1060 Vienna, Austria)

Abstract

Digital reflections of physical energy plants can help support and optimize energy technologies within their lifecycle. So far, no framework for the evolution of virtual representations throughout the process development lifecycle exists. Based on various concepts of virtual representations in different industries, this review paper focuses on developing a novel virtual representation framework for the process development environment within the energy sector. The proposed methodology enables the continuous evolution of virtual representations along the process development lifecycle. A novel definition for virtual representations in the process development environment is developed. Additionally, the most important virtual representation challenges, properties, and applications for developing a widely applicable framework are summarized. The essential sustainability indicators for the energy sector are listed to standardize the process evaluation throughout the process development lifecycle. The virtual representation and physical facility development can be synchronized by introducing a novel model readiness level. All these thoughts are covered through the novel virtual representation framework. Finally, the digital twin of a Bio-SNG production route is presented, to show the benefits of the methodology through a use case. This methodology helps to accelerate and monitor energy technology developments through the early implementation of virtual representations.

Suggested Citation

  • Martin Hammerschmid & Daniel Cenk Rosenfeld & Alexander Bartik & Florian Benedikt & Josef Fuchs & Stefan Müller, 2023. "Methodology for the Development of Virtual Representations within the Process Development Framework of Energy Plants: From Digital Model to Digital Predictive Twin—A Review," Energies, MDPI, vol. 16(6), pages 1-30, March.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:6:p:2641-:d:1094182
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    References listed on IDEAS

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    Cited by:

    1. Stanger, Lukas & Bartik, Alexander & Hammerschmid, Martin & Jankovic, Stefan & Benedikt, Florian & Müller, Stefan & Schirrer, Alexander & Jakubek, Stefan & Kozek, Martin, 2024. "Model predictive control of a dual fluidized bed gasification plant," Applied Energy, Elsevier, vol. 361(C).
    2. Martin Hammerschmid & Alexander Bartik & Florian Benedikt & Marton Veress & Simon Pratschner & Stefan Müller & Hermann Hofbauer, 2023. "Economic and Ecological Impacts on the Integration of Biomass-Based SNG and FT Diesel in the Austrian Energy System," Energies, MDPI, vol. 16(16), pages 1-29, August.

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