Passenger spatiotemporal distribution prediction in airport terminals based on insect intelligent building architecture and its contribution to fresh air energy saving

As the essential infrastructure and important transportation hubs, airport terminals play a strategic role in sustainable cities and urbanization. Due to the strict service requirement and round-the-clock operation, the high energy consumption poses unprecedented challenges to developing environment-friendly airport terminals. Actually, passenger flow as a root cause decides the startup and operation of service facilities including air-conditioning systems. But due to spatial connectivity, parameter coupling, and passenger mobility, resource allocation and system tuning have not been effectively related to passenger travel. In this work, Guangzhou Baiyun International Airport Terminal 2 was taken as an object, and a passenger spatiotemporal distribution model was developed and its contribution to fresh air energy saving was estimated. Among them, zone partition and expression rules were formulated based on insect intelligent building (I²B) architecture to construct Wi-Fi positioning system; Next, for domestic and international passenger, their arrival patterns were fitted by Chi-Square distribution with R² > 0.993, and their spatiotemporal distribution was predicted with R² over 0.74 and 0.67 respectively; Lastly, a hybrid reset strategy for fresh air volume set-point combining fuzzy and linear rules was proposed with results showing that HVAC systems running on variable occupancy would lead to considerable energy savings.

• Record URL:
  • https://doi.org/10.1016/j.scs.2023.104772
• Record URL:
  • http://www.sciencedirect.com/science/article/pii/S2210670723003839
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/22106707
• Supplemental Notes:
  • © 2023 Published by Elsevier Ltd. Abstract reprinted with permission of Elsevier.
• Authors:
  • Li, Zhiwei
  • Zhang, Jili
  • Mu, Song
• Publication Date: 2023-10

Language

• English

Media Info

• Media Type: Web
• Features: References;
• Pagination: 104772
• Serial:
  • Sustainable Cities and Society
  • Volume: 97
  • Issue Number: 0
  • Publisher: Elsevier
  • ISSN: 2210-6707
  • Serial URL: http://www.sciencedirect.com/science/journal/22106707?sdc=2

Subject/Index Terms

• TRT Terms: Air quality; Airport terminals; Energy consumption; Heating, cooling and ventilation equipment; Passenger traffic; Predictive models
• Identifier Terms: Guangzhou Baiyun International Airport
• Geographic Terms: Guangzhou (China)
• Subject Areas: Aviation; Environment; Operations and Traffic Management; Safety and Human Factors; Terminals and Facilities;

Filing Info

• Accession Number: 01890655
• Record Type: Publication
• Files: TRIS
• Created Date: Aug 23 2023 3:24PM