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District-level validation of a shoeboxing simplification algorithm to speed-up Urban Building Energy Modeling simulations

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  • Battini, Federico
  • Pernigotto, Giovanni
  • Gasparella, Andrea

Abstract

The “shoeboxing” algorithm is a simplification approach capable of converting a building of any shape into a representative shoebox, with the aim of speeding-up Urban Building Energy Modeling simulations. The procedure works towards accurately predicting both annual energy needs and hourly thermal loads, going beyond the preliminary assessment of buildings' thermal performance at city-scale. Furthermore, the simplification has been particularly developed to work with buildings of complex geometry considering adjacencies and obstructions. After a first validation performed for stand-alone buildings, in this paper, the capabilities of the algorithm are evaluated at district-level on fictional parametrically generated layouts and in different climatic conditions. As a whole, the shoeboxing algorithm properly predicted both heating and cooling needs at building-level in all the considered climatic conditions, yielding annual differences within ±10% and ± 20%, respectively for cooling and heating. Moreover, both annual and hourly deviations showed to be similar in the different climates considered, suggesting that the simplification can be reliably employed worldwide. Finally, the thermal simulation time has been reduced up to 36 times.

Suggested Citation

  • Battini, Federico & Pernigotto, Giovanni & Gasparella, Andrea, 2023. "District-level validation of a shoeboxing simplification algorithm to speed-up Urban Building Energy Modeling simulations," Applied Energy, Elsevier, vol. 349(C).
    • Handle: RePEc:eee:appene:v:349:y:2023:i:c:s0306261923009340
    DOI: 10.1016/j.apenergy.2023.121570
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    References listed on IDEAS

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    1. Diego Viesi & Gregorio Borelli & Silvia Ricciuti & Giovanni Pernigotto & Md Shahriar Mahbub, 2024. "Modeling the Optimal Transition of an Urban Neighborhood towards an Energy Community and a Positive Energy District," Energies, MDPI, vol. 17(16), pages 1-30, August.
    2. Yucheng Guo & Jie Shi & Tong Guo & Fei Guo & Feng Lu & Lingqi Su, 2024. "Grey-Box Method for Urban Building Energy Modelling: Advancements and Potentials," Energies, MDPI, vol. 17(21), pages 1-25, October.

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