基于数值模拟的印度住宅冷却负荷分布预测方法——采用Tukey - honest显著差异检验

IF 2.1 Q2 CONSTRUCTION & BUILDING TECHNOLOGY
Chittella Ravichandran, G. Padmanaban
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引用次数: 2

摘要

印度能源安全情景(IESS 2047)预测住宅空调将大幅增加,从2017年的2180万台增加到2038年的1.544亿台。对空间冷却需求的增加使得建筑师和能源工程师有责任研究与建筑设计相关的冷却负荷关系。本文研究了新孟买25种主要住宅类型在高度、形状、占地面积和密度上的冷却负荷分布模式。冷却负荷的模拟是使用Rhinoceros 6工具和energy plus插件完成的。Tukey Honest显著差异(HSD)事后检验是在方差分析后对具有相似冷负荷概况的楼层进行分组。结果表明,低层和中层的冷负荷在顶楼前都有严格的增加。然而,对于高层建筑,大多数中间楼层属于单一子集;因此,楼层间冷负荷的增加是不相似的。由此可见,随着建筑高度的增加,中间楼层的冷负荷差值明显减小。此外,高度的增加与占地面积的减少减少了建筑物的总体冷负荷。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A numerical simulation-based method to predict floor wise distribution of cooling loads in Indian residences using Tukey honest significant difference test
ABSTRACT India's energy security scenario (IESS 2047) projects a mammoth increase in residential air conditioners, from 21.8 million units in 2017 to 154.4 million in 2038. This increased demand for space cooling accounts for an equal responsibility from architects and energy engineers to research building design-related cooling load nexus. This paper studies the pattern of cooling load dispersion between floors for 25 dominant residential typologies in Navi Mumbai that vary in heights, shapes, footprint areas, and densities. Simulation for cooling loads is done using Rhinoceros 6 tool with energy plus plugin. Tukey Honest Significant Difference (HSD) Post Hoc Test is done after ANOVA to group floors with similar cooling load profiles. The results show a strict increase in cooling load till the top floor for low rise and mid-rise. However, for high-rise buildings, most intermediate floors fall under a single subset category; thereby, the increase in cooling load among floors is not similar. This shows that as building height increases, the difference between cooling loads of intermediate floors decreases significantly. Also, an increase in height with a decrease in footprint area reduces the overall cooling load of the building.
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来源期刊
Advances in Building Energy Research
Advances in Building Energy Research CONSTRUCTION & BUILDING TECHNOLOGY-
CiteScore
4.80
自引率
5.00%
发文量
11
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