The airport terminal is a multi-region public transport building with special functions and the cooling load is a basic parameter determining the air-conditioning system for this special building. The large uncertainty in the parameters of the terminal cooling load calculation will affect the input data, which will lead to the uncertainty of the model results. In this paper, the load of a typical hub airport terminal is simulated and calculated on the basis of uncertainty analysis, and the sensitivity analysis of the influencing factors is carried out. The result shows that compared with the given parameters, more accurate average probability distribution and peak load distribution of terminal cooling load can be obtained under uncertainty parameters. The average load of the terminal is in the range of 55.2-78.5 W/m² within the 95% confidence interval, and the peak load is in the range of 79.8-117.9 W/m² within the 95% confidence interval. Load curves of various areas in the terminal are clustered. The results show that there are two main types of areas, i.e. one exhibits a single-peak curve and the other exhibits a peak-flat curve, which demonstrate the load characteristics of different zones. The sensitivity analysis shows that the most performance influencing factors are indoor temperature and humidity set point.

机场航站楼是具有特殊功能的多区域公共交通建筑物，而冷却负荷是确定该特殊建筑物的空调系统的基本参数。终端冷却负荷计算参数的较大不确定性将影响输入数据，这将导致模型结果的不确定性。本文在不确定性分析的基础上，对典型枢纽机场航站楼的负荷进行了仿真计算，并对影响因素进行了敏感性分析。结果表明，与给定参数相比，在不确定性参数下可以获得更准确的终端冷却负荷平均概率分布和峰值负荷分布。终端的平均负载在55.2-78.5 W / m ²的范围内在95％置信区间内，峰值负载在79.8-117.9 W / m ^2的范围内。终端中各个区域的负载曲线是聚类的。结果表明，区域主要有两种类型，一种表现出单峰曲线，另一种表现出峰平曲线，这表明了不同区域的负荷特性。灵敏度分析表明，影响性能的最大因素是室内温度和湿度设定点。