基于数据挖掘的地铁车站热湿特征抽取

针对城市轨道交通系统车站环控能耗高占比问题，从城轨交通地下站点热湿环境角度探索轨交站点环控运行能效提升策略。本研究通过K-means对地铁公司各车站站内全年日均温湿度数据进行聚类，再对各聚类车站通过时空分布、埋深等物理属性影响进行分析。结果表明：(1)相同线路、相邻车站温湿度变化曲线存在差异较大；(2)温度聚类二类车站表现为冬冷夏热，舒适度最差，11-12月的西南季风造成温度聚类四车站温度较低；(3)利用室内外温湿度差的标准差分析发现，曲线波动与埋深、方位角等物理特征均表现为强相关。因此不同车站因物理特征差异站点环控系统应差异化运行，也应对不同车站分类设定不同环控能耗定额标准，本研究为地铁车站设计、环控设备选型和运行提供依据，并对城轨交通的深绿运行及低碳城市建设有积极意义。

Research on Thermal and Humidity Feature Extraction in Metro Station Based on Data Mining

Aiming at reducing the high proportion of energy consumption for Environment Control System (ECS) in Urban rail Transit System (UTS), the energy efficiency improvement strategy of ECS operation is explored from the perspective of thermal and humid environment of subway stations. This study adoptesK-means to cluster the annual average daily temperature and humidity data in each station of the metro company, and then analyses the influence of physical attributes such as spatiotemporal distribution and burial depth of each clustered station. The results show that: (1) The temperature and humidity curves of the same line and adjacent stations are quite different; (2) The second-class temperature clustering of the stations is colder in winter and hotter in summer, and the comfort is the worst. The southwest monsoon from November to December caused the fourth temperature clustering stations to be relatively low, which can be adjusted strategically; (3) After conducting the standard deviation analysis on the indoor and outdoor temperature and humidity differences, it is found that the curve fluctuation is related to physical characteristics such as burial depth and azimuth. showed strong correlation. The ECS of different stations should be operated in a differentiated manner due to differences in physical characteristics, and different environmental control energy consumption quota standards should be set for different station categories. This research provides a basis for the subway stations design and the power selection of ECS, it has positive environmental significance for the dark green operation of UTS and the construction of low-carbon cities.