Design optimization of building geometry and fenestration for daylighting and energy performance
Design optimization of building geometry and fenestration for daylighting and energy performance
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DOI：
10.1016/j.solener.2019.08.039
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发表时间：
2019-10-01
期刊：
影响因子：
6.7
通讯作者：
Cho, Soolyeon
中科院分区：
文献类型：
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作者：
Fang, Yuan;Cho, Soolyeon
随着对可持续设计和绿色建筑的需求不断增长，建筑性能对设计决策的影响越来越大。在早期设计阶段，建筑围护结构的设计决定，特别是建筑几何形状、窗户和天窗的尺寸和位置至关重要。这项研究提出了一个建筑性能优化过程，可以帮助设计师同时评估众多设计方案的采光和能源性能，并生成优化设计。所提出的方法利用参数化设计，建筑仿真建模，遗传算法。最后，以某小型办公楼为例，验证了优化过程的有效性。案例研究建筑的几何形状在三种不同的气候条件下进行了优化，即迈阿密、亚特兰大和芝加哥。优化后，与平均性能值相比，采光性能指标UDI增加了38.7%，31.6%和28.8%，而能源性能指标EUI减少了20.2%，18.5%和17.9%。进行敏感性分析，以分析设计变量和性能指标之间的关系。天窗宽度和长度是所有位置的最重要的变量，而其他变量的影响差异很大。
With the increasing demand for sustainable design and green buildings, building performance is having a greater influence on design decisions. Design decisions on building envelop, especially on building geometry, window and skylight size and placement are essential in the early design stage. This research proposes a building performance optimization process that can help designers simultaneously evaluate the daylighting and energy performance of numerous design options and generate optimized design. The proposed method utilizes parametric design, building simulation modeling, and genetic algorithms. A case study of a small office building is conducted to test and verify the effectiveness of the optimization process. The geometry of the case study building is optimized in three different climates, Miami, Atlanta, and Chicago. After the optimization, the daylighting performance metric UDI is increased by 38.7%, 31.6%, and 28.8%, and the energy performance metric EUI is decreased by 20.2%, 18.5%, and 17.9% compared to average performance values. Sensitivity analysis is performed to analyze the relationship between design variables and performance metrics. The skylight width and length are the most important variables for all locations, while the influence of the other variables varies greatly.