Identifying Residential Building Occupancy Profiles with Demographic Characteristics:Using a National Time Use Survey Data

35 Pages Posted: 15 Feb 2022

See all articles by Jiasha Fu

Jiasha Fu

Southwestern University of Finance and Economics (SWUFE) - Research Institute of Economics & Management

Xin He

affiliation not provided to SSRN

Shan Hu

Tsinghua University

Shunsuke Managi

Kyushu University

Da Yan

Tsinghua University

Abstract

Occupancy patterns in residential buildings and profiles with family information are essential for the energy system design and optimization, for the electricity demand responses and management of buildings, and for constructing household energy efficiency policies. To address the shortcomings of current research, this study conducted a national-wide survey in China with a valid sample of 8,190 urban households representing 19,352 individuals. On this basis, a novel approach was generated and conducted to identify the occupancy patterns in residential buildings and describe profiles of typical families in this research. As a result, typical residential occupancy profiles in urban China were obtained by analyzing distribution of the duration of residential occupation and the sequence of occupancy patterns in this research. Meanwhile, detailed results of four typical occupancy patterns with demographic characteristics during workdays, and five patterns during weekends were described for further research and application.

Keywords: occupant behavior, occupancy pattern, household survey, time of use, building energy efficiency

Suggested Citation

Fu, Jiasha and He, Xin and Hu, Shan and Managi, Shunsuke and Yan, Da, Identifying Residential Building Occupancy Profiles with Demographic Characteristics:Using a National Time Use Survey Data. Available at SSRN: https://ssrn.com/abstract=4015216 or http://dx.doi.org/10.2139/ssrn.4015216

Jiasha Fu

Southwestern University of Finance and Economics (SWUFE) - Research Institute of Economics & Management ( email )

55 Guanghuacun Street
Chengdu, Sichuan 610074
China

Xin He

affiliation not provided to SSRN ( email )

No Address Available

Shan Hu (Contact Author)

Tsinghua University ( email )

Beijing, 100084
China

Shunsuke Managi

Kyushu University ( email )

Fukuoka, Fukuoka
Japan

HOME PAGE: http://www.managi-lab.com/english.html

Da Yan

Tsinghua University ( email )

Beijing, 100084
China

Do you have negative results from your research you’d like to share?

Paper statistics

Downloads
85
Abstract Views
299
Rank
751,313
PlumX Metrics