Prediction of the spatiotemporal passenger distribution of a large airport terminal and its impact on energy simulation. (March 2022) - Gu, Xianliang; Xie, Jingchao; Huang, Chengyang; Ma, Kai; Liu, Jiaping
Highlights: The passenger distribution in the airport terminals is related to their functions and the peak flow should not occur all over the terminal simultaneously. A spatiotemporal passenger distribution model was proposed for energy simulation of large airport terminals. The proposed model can reduce the HVAC energy consumption by over 11% compared to traditional passenger distribution model. Optimize the design and operation of HVAC systems in airport terminals. Abstract: As the essential infrastructure and one of the transportation centers, most cities now have more than one airport. Mass constructions of sustainable airports play an important role for sustainable cities and societies. The energy consumption of airport terminals poses a major challenge to the carbon neutrality policy due to the high energy demand and round-the-clock operation of these terminals. One major direction for sustainable future is to make buildings smart in terms of energy use and management. One of the solutions is to refine the energy supply according to needs, which calls for knowledge of the locations and dwell duration of passengers in the airport. With this background, this study established a spatiotemporal passenger distribution model to describe the transient passenger distribution in 14 characteristic zones of an airport terminal. After validation against airport operation data and results from passenger flow simulation software AnyLogic, the passenger flows calculated by the spatiotemporal model were inputted into the energy simulation software IES as well as the traditional calculation method to compare the energy consumptions. Results showed that the difference of the cooling and heating loads from the two models was 7%–148.9% in different zones. And the designed annual cooling and heating consumption of the terminal given by the proposed passenger distribution model was 11.3% lower. The proposed model could potentially optimize the HVAC system of future airport design.