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Workflow automation for combined modeling of buildings and district energy systems

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  • Fuchs, Marcus
  • Teichmann, Jens
  • Lauster, Moritz
  • Remmen, Peter
  • Streblow, Rita
  • Müller, Dirk

Abstract

In many urban contexts, energy systems are undergoing fundamental change towards more interconnected system layouts. Appropriate planning tools are necessary to guide this transition towards more energy efficient system designs. Thus, the aim of this paper is to present workflow automation approaches to model buildings and district energy systems for dynamic simulation and integral system analyses. For data collection and management, we use a Geographic Information System coupled with a PostgreSQL database. In this paper, we present the software tools TEASER and uesmodels which use this data to automatically generate dynamic building and district energy system models in the modeling language Modelica.

Suggested Citation

  • Fuchs, Marcus & Teichmann, Jens & Lauster, Moritz & Remmen, Peter & Streblow, Rita & Müller, Dirk, 2016. "Workflow automation for combined modeling of buildings and district energy systems," Energy, Elsevier, vol. 117(P2), pages 478-484.
    • Handle: RePEc:eee:energy:v:117:y:2016:i:p2:p:478-484
    DOI: 10.1016/j.energy.2016.04.023
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    References listed on IDEAS

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    7. Jiang, Feifeng & Ma, Jun & Li, Zheng & Ding, Yuexiong, 2022. "Prediction of energy use intensity of urban buildings using the semi-supervised deep learning model," Energy, Elsevier, vol. 249(C).
    8. Nageler, P. & Schweiger, G. & Schranzhofer, H. & Mach, T. & Heimrath, R. & Hochenauer, C., 2018. "Novel method to simulate large-scale thermal city models," Energy, Elsevier, vol. 157(C), pages 633-646.
    9. Bünning, Felix & Sangi, Roozbeh & Müller, Dirk, 2017. "A Modelica library for the agent-based control of building energy systems," Applied Energy, Elsevier, vol. 193(C), pages 52-59.
    10. Ranalli, Joseph & Alhamwi, Alaa, 2020. "Configurations of renewable power generation in cities using open source approaches: With Philadelphia case study," Applied Energy, Elsevier, vol. 269(C).
    11. Schweiger, Gerald & Heimrath, Richard & Falay, Basak & O'Donovan, Keith & Nageler, Peter & Pertschy, Reinhard & Engel, Georg & Streicher, Wolfgang & Leusbrock, Ingo, 2018. "District energy systems: Modelling paradigms and general-purpose tools," Energy, Elsevier, vol. 164(C), pages 1326-1340.
    12. Zhang, Xiang & Rasmussen, Christoffer & Saelens, Dirk & Roels, Staf, 2022. "Time-dependent solar aperture estimation of a building: Comparing grey-box and white-box approaches," Renewable and Sustainable Energy Reviews, Elsevier, vol. 161(C).
    13. Kate Doubleday & Faeza Hafiz & Andrew Parker & Tarek Elgindy & Anthony Florita & Gregor Henze & Graziano Salvalai & Shanti Pless & Bri‐Mathias Hodge, 2019. "Integrated distribution system and urban district planning with high renewable penetrations," Wiley Interdisciplinary Reviews: Energy and Environment, Wiley Blackwell, vol. 8(5), September.
    14. Nageler, P. & Zahrer, G. & Heimrath, R. & Mach, T. & Mauthner, F. & Leusbrock, I. & Schranzhofer, H. & Hochenauer, C., 2017. "Novel validated method for GIS based automated dynamic urban building energy simulations," Energy, Elsevier, vol. 139(C), pages 142-154.
    15. Michael Mans & Tobias Blacha & Thomas Schreiber & Dirk Müller, 2022. "Development and Application of an Open-Source Framework for Automated Thermal Network Generation and Simulations in Modelica," Energies, MDPI, vol. 15(12), pages 1-25, June.

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