Hourly occupant density prediction in commercial buildings for urban energy simulation

4th Asia Conference of International Building Performance Simulation Association

土木建筑工程

Wu, Yue^1^2 ; Li, Yanxia^1^2 ; Wang, Chao^1^2 ; Shi, Xing^1^2

Key Laboratory of Urban and Architectural Heritage Conservation, Ministry of Education, Nanjing

210096, China^1

School of Architecture, Southeast University, Nanjing

210096, China^2

关键词: Commercial building;    Fixed numbers;    Key factors;    Model linking;    Nanjing , China;    Occupant densities;    Urban energy;    Urban energy consumption;   

Others  :  https://iopscience.iop.org/article/10.1088/1755-1315/238/1/012039/pdf
DOI  :  10.1088/1755-1315/238/1/012039

学科分类：土木及结构工程学

来源: IOP

【 摘 要 】

Building occupant density is a key factor influencing urban energy consumption. However, it is difficult to predict and thus often simplified to be an assumed and fixed number in urban energy simulation. In this study, the hourly occupant densities of ten representative commercial buildings in Nanjing, China were measured. The pattern of the hourly occupant density was analyzed and the key parameters defining the pattern were identified. To expand the measured hourly occupant density pattern to thousands of commercial buildings in Nanjing, five predictors, namely function, accessibility, population, business diversity, business density, were proposed. Big data technique was used to obtain the value of the five predictors for more than 3000 commercial buildings. A regression analysis was conducted to establish a model linking the five predictors with the parameters defining the hourly occupant density pattern. The methodology developed provides an effective means to predict the hourly occupant density of buildings and thus substantially improves the accuracy and reliability of urban energy consumption.