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Automated Generation of Energy Profiles for Urban Simulations

Author

Listed:
  • Tobias Maile

    (Faculty of Architecture and Civil Engineering, Augsburg University of Applied Sciences, 86161 Augsburg, Germany)

  • Heiner Steinacker

    (Steinbeis-Innovationszentrum Energieplus, Affiliated Institute of the Technische Universität Braunschweig, 38114 Braunschweig, Germany)

  • Matthias W. Stickel

    (Steinbeis-Innovationszentrum Energieplus, Affiliated Institute of the Technische Universität Braunschweig, 38114 Braunschweig, Germany)

  • Etienne Ott

    (Steinbeis-Innovationszentrum Energieplus, Affiliated Institute of the Technische Universität Braunschweig, 38114 Braunschweig, Germany)

  • Christian Kley

    (Steinbeis-Innovationszentrum Energieplus, Affiliated Institute of the Technische Universität Braunschweig, 38114 Braunschweig, Germany)

Abstract

Urban simulations play an important role on the way to a climate neutral society. To enable early assessment of different energy concepts for urban developments, energy profiles for different building types are needed. This work describes the development and use of a new engineering tool GenSim to quickly and reliably generate energy profiles for urban simulations and early building energy predictions. While GenSim is a standalone tool to create energy profiles for early design assessment, it was developed in the context of urban simulations to primarily support energy efficient urban developments within Germany. Energy engineers quickly embraced the tool due to its simplicity and comprehensible results. The development of the tool was recently switched to open source to enable its usage to a broader audience. In order to foster its development and use, a detailed testing framework has been established to ensure the quality of the results of the tool. The paper includes a detailed validation section to demonstrate the validity of the results compared to a detailed building energy simulation model and actual measured performance data.

Suggested Citation

  • Tobias Maile & Heiner Steinacker & Matthias W. Stickel & Etienne Ott & Christian Kley, 2023. "Automated Generation of Energy Profiles for Urban Simulations," Energies, MDPI, vol. 16(17), pages 1-22, August.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:17:p:6115-:d:1222568
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    References listed on IDEAS

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    1. Paul Anton Verwiebe & Stephan Seim & Simon Burges & Lennart Schulz & Joachim Müller-Kirchenbauer, 2021. "Modeling Energy Demand—A Systematic Literature Review," Energies, MDPI, vol. 14(23), pages 1-58, November.
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