Classification of thermal environment control indicators according to the thermal sensitivity of office occupants

被引:2
|
作者
Kim, Sungkyung [1 ]
Ryu, Jihye [1 ]
Hong, Won-Hwa [2 ]
机构
[1] Kyungpook Natl Univ, Convergence Inst Construct Environm & Energy Engn, Daegu, South Korea
[2] Kyungpook Natl Univ, Sch Architectural Civil Environm & Energy Engn, Daegu, South Korea
基金
新加坡国家研究基金会;
关键词
Thermal comfort; Occupant; Sensitivity analysis; Clustering; Office buildings; ENERGY-CONSUMPTION; STOCHASTIC-MODEL; COMFORT; OPTIMIZATION; TEMPERATURE; BUILDINGS; PERFORMANCE; ADAPTATION; SIMULATION; STRATEGIES;
D O I
10.1016/j.heliyon.2024.e26038
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
The control that have the greatest influence on comfortable in the office occupants are the heating, ventilation, and air conditioning (HVAC) system operation and the thermal environment. However, comfortable HVAC operation is difficult in the office space characterized by a recommended standard thermal environment or a centralized HVAC system. To consider the occupant's thermal comfort to the greatest possible extent, must establish a method to quantify the variables related to the occupant's thermal comfort. This study aims to group occupants in Thermal sensation vote (TSV) clusters and perform sensitivity analysis (SA) on the relationship between thermal environmental factors in an office building and each cluster's TSV to establish the typology of the control indicators for each cluster. A total of 10 field experiments were conducted in the same office. This field study was carried out 2022. The indoor thermal environmental parameters, the subjective evaluation of the thermal comfort of the resident and the operation pattern of the heating system were monitored at the same time. A total of 4,200 datasets related to indoor thermal environmental parameters and a total of 1,680 datasets related to occupants' thermal comfort were collected and analyzed. The results of this study show that people have different levels of adaptability and sensitivity to a given thermal environment. This study founded distinguishable similarities in their thermal sensation traits and grouped similar TSV values into five clusters that responded differently to the same thermal environment. Each cluster showed different TSV and Thermal comfort vote (TCV) patterns, which allowed us to classify the groups that had sensitive responses to the thermal environment and those that did not. This study was determined different control indicators and guidelines for the divided groups according to thermal sensitivity.
引用
收藏
页数:17
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