大型机场航站楼逐时电耗特性及电耗强度
Hourly power consumption characteristics and power consumption intensity of a large airport terminal building
摘要：
以北京市某大型机场航站楼为研究对象,应用皮尔逊相关分析、k均值聚类方法,对2020—2023年实测数据变化特性及其影响因素进行了分析研究,包括逐时电耗特性提取及其电耗强度指标构建。结果表明:航站楼电耗可分为3类,即与建筑规模相关的基础电耗量、与旅客吞吐量相关的变动电耗量Ⅰ,以及与室外气象条件和旅客吞吐量相关的变动电耗量Ⅱ;k均值聚类分析结果反映了部分设计客流负荷对航站楼主要用电设备系统运行方式及其电耗特性的影响规律,可将日旅客吞吐量分为4级。基于这些分析结果,进一步给出了航站楼日总电耗强度及CO2排放指标的试算值。研究结果可为合理确定各分项用电设备系统的电耗强度降低目标提供参考。
Abstract：
Taking the terminal building of a large airport in Beijing as the research object, Pearson correlation analysis and k-means clustering method is used to analyse and study the change characteristics and influencing factors of the measured data from 2020 to 2023, including the extraction of hourly power consumption characteristics and the construction of power consumption intensity indicators. The results show that the power consumption of the terminal building can be divided into three categories, namely, the basic power consumption related to the building scale, the variable power consumption I related to passenger throughput, and the variable power consumption II related to outdoor meteorological conditions and passenger throughput. The analysis results of k-means clustering reflect the influence of part of the design passenger load on the operation mode and power consumption characteristics of the main electrical equipment system of the terminal building, and the daily passenger throughput can be divided into four levels. Based on these analysis results, the trial values of the total daily power consumption intensity and CO2emission indicator of the terminal building are further given. This study’s results can provide a reference for reasonably determining the power consumption intensity reduction target of each sub-item electrical equipment system.
Keywords:airport; terminal building; Pearson correlation analysis; k-means clustering; power consumption characteristic; power consumption intensity; indicator; CO2 emission