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地铁车站公共区域空调能耗影响因素的敏感性分析
引用本文:黄 莉,苏子怡,李晓锋. 地铁车站公共区域空调能耗影响因素的敏感性分析[J]. 都市快轨交通, 2021, 34(6): 125-130. DOI: 10.3969/j.issn.1672-6073.2021.06.019
作者姓名:黄 莉  苏子怡  李晓锋
作者单位:清华大学中国新型城镇化研究院,北京100084;清华大学建筑学院,北京100084
基金项目:“十三五”国家重点研发计划课题(2018YFC0705006)
摘    要:随着地铁建设规模和能耗的不断增加,地铁车站通风空调系统节能逐渐成为研究热点.采用基于回归、筛选和方差的3种方法对地铁车站通风空调系统能耗的影响因素进行敏感性分析.对比发现,3种方法识别出的重要性排序前25%的参数相同但排序有差异,其中方差和筛选方法排序较一致,回归方法差异较大;回归方法的计算效率最高,方差和筛选方法计算...

关 键 词:地铁车站  通风空调系统  能耗影响因素  敏感性分析  节能运行

Influential Parameters of Ventilation and Air-conditioning Energy Model for Subway Stations Using Sensitivity Analysis
HUANG Li,SU Ziyi,LI Xiaofeng. Influential Parameters of Ventilation and Air-conditioning Energy Model for Subway Stations Using Sensitivity Analysis[J]. Urban Rapid Rail Transit, 2021, 34(6): 125-130. DOI: 10.3969/j.issn.1672-6073.2021.06.019
Authors:HUANG Li  SU Ziyi  LI Xiaofeng
Affiliation:Institute for China Sustainable Urbanization, Tsinghua University;School of Architecture, Tsinghua University
Abstract:With the continuous expansion of subway scale and energy consumption, energy-saving ventilation and air-conditioning (VAC) systems in subway stations have gradually become a research focus. In this study, the influential parameters of the VAC energy model in subway stations are identified and ranked using three commonly used sensitivity analysis methods (regression-based, screening-based, and variance-based). The results show that the top 25% ranked parameters identified by the three methods are the same, but the orders are different. Among the three sensitivity analysis methods, the rankings of the variance- and screening-based methods are basically the same, whereas the ranking of the regression-based method is quite different from the previous two. In addition, the regression method is the most efficient method considering the computational cost, and the calculation times of the variance- and screening-based methods are 25 and 3 times, respectively. By comparison, it can be concluded that the screening-based method performs best in terms of parameter ranking and computational cost. Furthermore, the quantitative influence of the above-mentioned parameters on the energy consumed by the VAC system in a typical island subway station was studied. The results show that the impact of outdoor air parameters is as high as 84%, the effects of the mechanical fresh air volume, air infiltration volume through the entrances, and air infiltration volume through the platform screen doors are 43%, 29%, and 12%, respectively; the impact of equipment efficiency reaches 39% and is non-linear. The influence of the air parameters inside the station and the tunnel is 37% and 33%, respectively. Ultimately, the outcome of this research points out important variables that must be underlined in the energy conservation design and operation of subway stations, providing guidance for energy-saving operations and the management of stations.
Keywords:subway station   ventilation and air-conditioning system   influential factors   sensitivity analysis   energy-saving operation
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