Hourly power consumption characteristics and power consumption intensity of a large airport terminal building

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.