Thermal-humidity and fresh air dual-layer operation optimization for airport terminal air conditioning systems considering spatiotemporal passenger flow distribution

doi:10.3785/j.issn.1008-973X.2026.05.010

Journal of ZheJiang University (Engineering Science)

2026, Vol. 60

Issue (5): 1006-1015 DOI: 10.3785/j.issn.1008-973X.2026.05.010

Thermal-humidity and fresh air dual-layer operation optimization for airport terminal air conditioning systems considering spatiotemporal passenger flow distribution

Wenbi LIAO1(

),Menglian ZHENG2,*(

),Zitao YU2

1. Polytechnic Institute, Zhejiang University, Hangzhou 310015, China
2. College of Energy Engineering, Zhejiang University, Hangzhou 310027, China

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Abstract

To address the issues of energy waste in air conditioning systems and reduced passenger comfort caused by load variations and uneven spatiotemporal distribution of passenger flow in multifunctional zones of airport terminals, a spatiotemporal distribution model of passenger flow that integrates dwell and movement behaviors was constructed. Furthermore, a dual-layer operation optimization strategy for air conditioning systems was proposed, jointly considering thermal-humidity comfort and indoor air quality. A model predictive control algorithm was employed in the strategy, where the upper thermal-humidity optimization layer dynamically adjusts air supply parameters, while the lower fresh air optimization layer dynamically regulates the fresh air ratio, achieving rolling-horizon optimization. Simulation results indicate that, compared to the baseline strategy relying solely on temperature control, the proposed strategy synergistically incorporates thermal-humidity regulation, fresh air optimization and passenger flow responsiveness. Under the premise of ensuring zonal thermal-humidity comfort and air quality, this strategy achieves a 14.6% reduction in air conditioning energy consumption.

Key words： airport terminal HVAC system spatiotemporal passenger flow distribution thermal-humidity environment air quality operation optimization

Received: 16 June 2025 Published: 06 May 2026

CLC:

TP 393

Fund: 中央高校基本科研业务费专项资金资助项目（2022ZFJH04）.

Corresponding Authors: Menglian ZHENG E-mail: 22360185@zju.edu.cn;menglian_zheng@zju.edu.cn

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Cite this article:

Wenbi LIAO,Menglian ZHENG,Zitao YU. Thermal-humidity and fresh air dual-layer operation optimization for airport terminal air conditioning systems considering spatiotemporal passenger flow distribution. Journal of ZheJiang University (Engineering Science), 2026, 60(5): 1006-1015.

URL:

https://www.zjujournals.com/eng/10.3785/j.issn.1008-973X.2026.05.010 OR https://www.zjujournals.com/eng/Y2026/V60/I5/1006

考虑客流时空分布的航站楼空调系统热湿-新风双层运行优化

针对机场航站楼多功能区域负荷差异及客流时空分布不均导致的空调系统能耗浪费与乘客舒适性较低问题，构建融合乘客停留模型和移动模型的客流时空分布模型，提出兼顾热湿舒适性与空气质量的空调系统双层运行优化策略. 采用模型预测控制算法，通过上层热湿优化层动态调节送风参数，下层新风优化层动态调节新风比，实现滚动时域优化. 仿真结果表明，相较于传统温度调控的基线策略，所提策略协同考虑热湿调控、新风优化、客流响应等因素，在保证区域热湿舒适性和空气质量的前提下，空调系统能耗降低了14.6%.

关键词： 航站楼暖通空调系统, 客流时空分布, 热湿环境, 空气质量, 运行优化

Fig.1 Schematic of air supply zone division for airport terminal

Fig.2 HVAC system structure for air supply zone

Fig.3 Passenger departure process for individual flight

Fig.4 Dual-layer operation optimization strategy considering spatiotemporal passenger flow distribution

Tab.1 Heat and moisture load design parameters

Tab.2 Envelope components parameters

Tab.3 HVAC system operational parameters

Fig.5 Air supply zone distribution in check-in area

Tab.4 Scheme settings for different optimization strategies

Fig.6 Standardized daily flight schedule

Tab.5 Passenger dwell time model parameters

Fig.7 Passenger flow simulation in airport terminal functional zones

Fig.8 Spatiotemporal passenger flow distribution in different air supply zones of check-in area

Fig.9 Comparison of operation results for different strategies in thermal-humidity optimization layer

Tab.6 Temperature and humidity deviation

Fig.10 Comparison of typical daily energy consumption among different strategies (thermal-humidity optimization layer)

Fig.11 Comparison of air supply humidity optimization results among different strategies

Fig.12 Comparison of operation results for different strategies in fresh air optimization layer

Fig.13 Comparison of typical daily energy consumption among different strategies (fresh air optimization layer)

Fig.14 Energy consumption comparison of HVAC systems among different strategies

Tab.7 Energy consumption composition of HVAC systems for different strategies kW·h


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