【Applied Energy最新原创论文】用于城市建筑能源快速模拟的简化“鞋盒”算法：区域建筑层面的验证

AEii国际应用能源 · 公众号 · · 2023-08-13 11:27

正文

原文信息：

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

原文链接：

https://www.sciencedirect.com/science/article/pii/S0306261923009340?via%3Dihub

Highlights

• District-scale validation of an algorithm for Urban Building Energy Modeling

• Buildings are converted in shoeboxes including adjacencies and urban context

• The simplification is validated on 64 districts of 324 buildings in three climates

• Heating and cooling needs are predicted with differences within ±20% and ± 10%

• The algorithm reduced the thermal simulation time up to 36 times

摘要

“鞋盒”算法是一种简化的模拟方法，该算法可将任意形状的建筑转化为等价的鞋盒模型，进而提高城市建筑能源模型的运算速度。简化过程立足于城市建筑热特性的基础评估，并进一步致力于建筑年度能耗和小时热负荷的精确预测。此外，该简化过程还对具有邻接和障碍物等复杂构型的建筑进行了专门的适应性设计。本文首先采用独立式建筑的能源数据对该算法进行了验证。随后，基于虚拟参数生成的建筑构型和多种气候环境，评估了该算法在区域建筑层面的运算能力。总体而言，在考虑的各种气候环境中该鞋盒算法均能够对建筑的热冷需求进行合理的预测，所产生的年度热冷误差分别为±10%和±20%。另外，在不同的气候环境中年度差异和小时差异非常接近，这意味着该简化算法有望应用于全球气候背景。最后，该简化算法的另一巨大优势是大幅提升运算速度，从而将热计算时间缩减了36倍。

更多关于“Building Energy”的文章请见：https://www.sciencedirect.com/search?pub=Applied%20Energy&cid=271429&qs=building%20energy

Abstr act

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.

Keywords

Urban building energy modeling

Simplification algorithm

Building energy modeling

Shoebox

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