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Energy Design Synthesis: Algorithmic Generation of Building Shape Configurations

Author

Listed:
  • Tamás Storcz

    (Department of Systems and Software Technologies, Faculty of Engineering and Information Technology, University of Pécs, Boszorkány Street 2, 7624 Pécs, Hungary)

  • Zsolt Ercsey

    (Department of Systems and Software Technologies, Faculty of Engineering and Information Technology, University of Pécs, Boszorkány Street 2, 7624 Pécs, Hungary)

  • Kristóf Roland Horváth

    (Marcel Breuer Doctoral School, Faculty of Engineering and Information Technology, University of Pécs, Boszorkány Street 2, 7624 Pécs, Hungary)

  • Zoltán Kovács

    (Optin Ltd., 6720 Szeged, Hungary)

  • Balázs Dávid

    (InnoRenew CoE, Livade 6a, 6310 Izola, Slovenia
    Department of Information Sciences and Technologies, Faculty of Mathematics, Natural Sciences and Information Technologies, University of Primorska, Glagoljaška 8, 6000 Koper, Slovenia)

  • István Kistelegdi

    (Department of Simulation Driven Design, Ybl Miklós Faculty of Architecture and Civil Engineering, Institute of Architecture, Óbuda University, Thököly Street 74, 1146 Budapest, Hungary)

Abstract

The building industry is responsible for a significant degree of energy consumption in the world, causing negative climate changes and energy supply uncertainties due to low energy efficiency as well as the high resource demand of construction. Consequently, energy design optimization has become an important research field. Passive design strategies are one of the most definitive factors concerning energy-related building development. The given architectural problem calls for a method that can create all potentially feasible building geometries, thus guaranteeing the optimal solution which is addressed in the current paper. To reach this requirement, the necessity of a modular space arrangement system and architectural selection rules were determined, focusing on the relationship between the rules and the generation of geometries with mathematical rigor. Next, the architecture-based congruency analysis performed, further reduced the number of simulation cases. With the simulations, it is illustrated how the building shape versions affect the heating energy demands: the performance of the configurations themselves. Results clearly illustrate the importance of the synthesis step of the architectural design.

Suggested Citation

  • Tamás Storcz & Zsolt Ercsey & Kristóf Roland Horváth & Zoltán Kovács & Balázs Dávid & István Kistelegdi, 2023. "Energy Design Synthesis: Algorithmic Generation of Building Shape Configurations," Energies, MDPI, vol. 16(5), pages 1-17, February.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:5:p:2254-:d:1081240
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    References listed on IDEAS

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    1. Waibel, Christoph & Evins, Ralph & Carmeliet, Jan, 2019. "Co-simulation and optimization of building geometry and multi-energy systems: Interdependencies in energy supply, energy demand and solar potentials," Applied Energy, Elsevier, vol. 242(C), pages 1661-1682.
    2. Effrosyni Giama & Georgios Chantzis & Serafim Kontos & Stavros Keppas & Anastasia Poupkou & Natalia Liora & Dimitrios Melas, 2022. "Building Energy Simulations Based on Weather Forecast Meteorological Model: The Case of an Institutional Building in Greece," Energies, MDPI, vol. 16(1), pages 1-15, December.
    3. Ciardiello, Adriana & Rosso, Federica & Dell'Olmo, Jacopo & Ciancio, Virgilio & Ferrero, Marco & Salata, Ferdinando, 2020. "Multi-objective approach to the optimization of shape and envelope in building energy design," Applied Energy, Elsevier, vol. 280(C).
    4. Mert, Yelda & Saygın, Nicel, 2016. "Energy efficient building block design: An exergy perspective," Energy, Elsevier, vol. 102(C), pages 465-472.
    5. Nguyen, Anh-Tuan & Reiter, Sigrid & Rigo, Philippe, 2014. "A review on simulation-based optimization methods applied to building performance analysis," Applied Energy, Elsevier, vol. 113(C), pages 1043-1058.
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    Cited by:

    1. Tamás Storcz & Géza Várady & István Kistelegdi & Zsolt Ercsey, 2023. "Regression Models and Shape Descriptors for Building Energy Demand and Comfort Estimation," Energies, MDPI, vol. 16(16), pages 1-20, August.

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