The interactive indoor-outdoor building energy modeling for enhancing the predictions of urban microclimates and building energy demands
The interactive indoor-outdoor building energy modeling for enhancing the predictions of urban microclimates and building energy demands
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交互式室内外建筑能源模型，增强对城市微气候和建筑能源需求的预测
DOI：
10.1016/j.buildenv.2023.111059
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发表时间：
2024
影响因子：
7.4
通讯作者：
Lee, Edwin
中科院分区：
文献类型：
--
作者：
Wang, Liping;Wu, Lichen;Norford, Leslie Keith;Aliabadi, Amir A.;Lee, Edwin
缺乏考虑周围建筑和当地城市气候对建筑热性能影响的城市建筑能源建模框架。这可能会导致结果不准确，因为各个建筑物的热性能很大程度上受到周围建筑和气候环境的影响。本研究建立了一种交互式室内外建筑能源建模方法，通过将城市物理模型与基于物理的建筑能源模型相结合来增强对城市微气候和建筑能源需求的预测。交互式耦合方案的验证使用现场测量数据集。通过参数模拟和分析，了解屋顶与峡谷宽度比、峡谷朝向和地面植被比例对峡谷温度、建筑能耗和能源需求的影响。此外，使用两个案例研究建筑演示了建筑能源模型复杂性（例如，详细与简化的建筑模型）和耦合方法对峡谷温度和建筑能源概况的影响。与单向耦合方法相比，动态双向耦合方法预测的详细中型办公楼模型和高层建筑模型的制冷能耗分别变化了 3.5% 和 0.5%，详细中型办公楼模型和高层建筑模型的峰值制冷需求分别变化了 8.4% 和 7.0%。这项研究还表明，采用复杂的双向耦合方法与不同高度的环境数据交换对于城市尺度的高层建筑建模是必要的。
There is a lack of an urban building energy modeling framework that considers the influence of surrounding buildings and local urban climate on building thermal performance. This can lead to inaccurate results since the thermal performance of individual buildings is heavily influenced by their surrounding built and climatic environment. This study establishes an interactive indoor-outdoor building energy modeling method to enhance the predictions of urban microclimates and building energy demands by coupling an urban physics model with a physics-based building energy model. Validation of the interactive coupling scheme uses field measurement datasets. Parametric simulation and analysis are conducted to understand the influence of the roof-to-canyon width ratio, canyon orientation, and ground vegetation fraction on canyon temperature, building energy consumption, and energy demand. Furthermore, the impacts of building energy model complexity (e.g., detailed vs. simplified building models) and coupling approaches on canyon temperature and building energy profiles are demonstrated using two case study buildings. In comparison with the one-way coupling approach, cooling energy consumption predicted with the dynamic two-way coupling approach varies by 3.5 % and 0.5 % for the detailed medium office building model and high-rise building model, respectively, and peak cooling demand varies by 8.4 % and 7.0 % for the detailed medium office building model and high-rise building model, respectively. This study also suggests that adopting a complex two-way coupling approach with environmental data exchange at various elevations is necessary for modeling tall buildings at the urban scale.