TY - JOUR
T1 - Determining the optimal occupancy density for reducing the energy consumption of public office buildings
T2 - A statistical approach
AU - Kang, Hyuna
AU - Lee, Minhyun
AU - Hong, Taehoon
AU - Choi, Jun Ki
N1 - Funding Information:
This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government ( MSIP; Ministry of Science, ICT & Future Planning ) (No. NRF-2015R1A2A1A05001657 ).
Publisher Copyright:
© 2017 Elsevier Ltd
PY - 2018/1
Y1 - 2018/1
N2 - Due to the various restrictions on the energy performance of public office buildings, it is essential to obtain occupancy information for not only evaluating but also regulating the building energy performance. There is still a lack of information and standard, however, for occupancy density due to the limitations on data collection and the lack of reliable data. Therefore, this study aimed to determine the optimal occupancy density for reducing the energy consumption in public office buildings. Towards this end, this study used various statistical methods, such as correlation analysis, decision tree, and Mann-Whitney U test, based on the actual occupancy data from public office buildings in South Korea. This study was conducted in three steps: (i) establishment of the database; (ii) determination of the optimal occupancy density using the statistical approach; and (iii) application of the proposed occupancy density using building energy policies. As a result, it was shown that buildings with an occupancy density above 31.41 m2/person could save up to 50.3% energy on average compared to those with an occupancy density below 31.41 m2/person. The analysis results showed that the proposed occupancy density could help in deciding the appropriate occupancy density for reducing the energy consumption of public office buildings.
AB - Due to the various restrictions on the energy performance of public office buildings, it is essential to obtain occupancy information for not only evaluating but also regulating the building energy performance. There is still a lack of information and standard, however, for occupancy density due to the limitations on data collection and the lack of reliable data. Therefore, this study aimed to determine the optimal occupancy density for reducing the energy consumption in public office buildings. Towards this end, this study used various statistical methods, such as correlation analysis, decision tree, and Mann-Whitney U test, based on the actual occupancy data from public office buildings in South Korea. This study was conducted in three steps: (i) establishment of the database; (ii) determination of the optimal occupancy density using the statistical approach; and (iii) application of the proposed occupancy density using building energy policies. As a result, it was shown that buildings with an occupancy density above 31.41 m2/person could save up to 50.3% energy on average compared to those with an occupancy density below 31.41 m2/person. The analysis results showed that the proposed occupancy density could help in deciding the appropriate occupancy density for reducing the energy consumption of public office buildings.
KW - Building energy
KW - Decision tree
KW - Energy consumption
KW - Mann–Whitney U test
KW - Occupancy density
KW - Public office building
UR - http://www.scopus.com/inward/record.url?scp=85033710239&partnerID=8YFLogxK
U2 - 10.1016/j.buildenv.2017.11.010
DO - 10.1016/j.buildenv.2017.11.010
M3 - Journal article
AN - SCOPUS:85033710239
SN - 0360-1323
VL - 127
SP - 173
EP - 186
JO - Building and Environment
JF - Building and Environment
ER -