| 基于BIM技术的被动式建筑节能因子多目标优化研究 |
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| 引用本文： | 孙少楠,吴家伟. 基于BIM技术的被动式建筑节能因子多目标优化研究[J]. 图学学报, 2021, 42(1): 124-132. DOI: 10.11996/JG.j.2095-302X.2021010124 |
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| 作者姓名： | 孙少楠 吴家伟 |
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| 作者单位： | 华北水利水电大学水利学院,河南郑州450000 |
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| 基金项目： | 国家自然科学基金项目(51709115);河南省重点研发与推广专项(科技攻关)项目(182102210066)。 |
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| 摘 要： | 为了研究被动式建筑节能策略,在原有的BIM模型基础上生成建筑能耗模型,通过gbXML数据标准进行数据共享,在Grasshopper平台导入参数化建筑性能模拟模型,对目标建筑外表面进行太阳辐射分析,确定以西面遮阳板倾斜角和深度、南面和西面窗墙比、外墙保温板厚度为被动式节能技术变量指标.利用OpenStudio进行建筑能耗...
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| 关 键 词： | 建筑信息模型 被动式建筑 节能因子 建筑性能分析 多目标优化 |
Research on multi-objective optimization of passive building energy-saving factor based on BIM |
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| SUN Shao-nan,WU Jia-wei. Research on multi-objective optimization of passive building energy-saving factor based on BIM[J]. Journal of Graphics, 2021, 42(1): 124-132. DOI: 10.11996/JG.j.2095-302X.2021010124 |
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| Authors: | SUN Shao-nan WU Jia-wei |
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| Affiliation: | School of Water Conservancy, North China University of Water Resources and Electric Power, Zhengzhou Henan 450000, China |
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| Abstract: | Building energy models on the basis of the original building information modeling(BIM) model were established to research the passive energy-saving strategies. This model adopted the gbXML data standard for data sharing, which imported a parametric building performance simulation model on the Grasshopper platform. In addition, the solar radiation analysis was performed on the outer surface of the target building to determine the variables index of the passive energy-saving technology, such as the angle and depth of the west overhangs, the window-to-wall ratio on the south and west sides, and the thickness of the insulation board. This platform established the objective function based on the spatial daylight autonomy(sDA300/50%), annual cooling and heating energy consumption, which employed OpenStudio for building energy analysis and Daysim for annual dynamic natural lighting analysis. Finally, using the NSGA-Ⅱ algorithm for multi-objective optimization, the Pareto solution set was obtained. The result shows that on cold zone B, the fixed shading cannot balance cooling and heating energy consumption. The window-to-wall ratio cannot be optimized only through cooling and heating energy consumption, which should combine natural lighting performance. At the same time, it should increase the thickness of the insulation layer to enhance the insulation effect of the external wall. The BIM model provides a source of building performance simulation data, and the Grasshopper platform combines simulation engines and optimization algorithms for coupling analysis, bringing new ideas to the search of optimal values of passive energy-saving factor index. |
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| Keywords: | building information modeling passive building energy-saving factor building performance analysis multi-objective optimization |
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