Warm, moderate, or cool-liker? A Benchmarking Framework to Characterize Occupant Overall Thermal Preferences based on Large-Scale Thermostat Data

恒温器 标杆管理 比例(比率) 热的 计算机科学 环境科学 汽车工程 工程类 机械工程 气象学 物理 经济 管理 量子力学
作者
Kai Chen,Ali Ghahramani
出处
期刊:Building and Environment [Elsevier]
卷期号:: 112046-112046
标识
DOI:10.1016/j.buildenv.2024.112046
摘要

Humans could exhibit distinct overall thermal preferences when exposed to identical indoor thermal environments, leading to distinct preference groups such as "warm-likers" or "cool-likers", who consistently prefer warmer or cooler conditions than the average population, respectively. Currently, most thermal comfort modelling studies focus on capturing momentary or instantaneous comfort states/preferences, ignoring the overall thermal preference. This paper proposes a benchmarking framework to identify and characterize overall thermal preferences based on preferred setpoint/outdoor temperature relationships derived from ECOBEE Donate Your Data program. Using descriptive statistics, we establish 3 temporally consistent overall preference groups, including warm-liker, moderate and cool-liker, along with a temporally chaotic preference group termed random. Our results demonstrate that warm-likers' preferred temperature setpoints are above 21.5°C on heating days and 24-25°C on cooling days, while cool-likers prefer setpoints below 19.6°C on heating days and 22°C on cooling days. We observed that around 50% of users exhibit secondary overall preferences, implying that overall thermal preference could change over time. On average, overall thermal preference can be established in 10 to 16 setpoint adjustments. The study reveals varied responses to outdoor temperature changes among users: many maintain constant indoor temperature preferences, while a significant number adjust their indoor temperatures upwards by 0.1°C to 0.4°C for each 1°C rise in outdoor temperature. A smaller group prefers cooler indoor temperatures as it gets warmer outside, showing a unique negative adjustment trend of -0.1. We also found that climate interacts with the overall preference group, with warmer climates having more warm-likers and vice versa.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
Lianna完成签到 ,获得积分10
刚刚
拉长的远山完成签到,获得积分10
1秒前
充电宝应助zzzxh采纳,获得10
1秒前
充电宝应助朴素的云朵采纳,获得10
1秒前
1秒前
1秒前
2秒前
范雅寒发布了新的文献求助10
2秒前
快乐滑板应助爱科研采纳,获得10
2秒前
傅艺煊发布了新的文献求助30
3秒前
hzy发布了新的文献求助10
3秒前
没有昵称发布了新的文献求助10
3秒前
3秒前
祖诗云完成签到,获得积分10
4秒前
4秒前
lx840518发布了新的文献求助10
4秒前
懵懂的弱完成签到,获得积分20
4秒前
5秒前
科研通AI6.1应助Qing灿采纳,获得10
5秒前
科研通AI2S应助sunrise采纳,获得10
5秒前
禧壹完成签到,获得积分10
6秒前
JamesPei应助Xiaohui_Yu采纳,获得10
6秒前
喵miao完成签到,获得积分10
6秒前
量子星尘发布了新的文献求助10
6秒前
星辰大海应助逍遥子采纳,获得10
6秒前
Arrow完成签到,获得积分10
6秒前
6秒前
luoziwuhui完成签到,获得积分10
7秒前
姜彩秀发布了新的文献求助10
7秒前
哼1完成签到 ,获得积分10
7秒前
8秒前
8秒前
沉默的倔驴应助why采纳,获得10
8秒前
熊啾啾完成签到,获得积分10
8秒前
852应助可达可达采纳,获得10
9秒前
LBJ完成签到,获得积分10
9秒前
Aaaaguo完成签到 ,获得积分10
9秒前
10秒前
10秒前
馥芮白完成签到,获得积分10
11秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Encyclopedia of Forensic and Legal Medicine Third Edition 5000
Introduction to strong mixing conditions volume 1-3 5000
Agyptische Geschichte der 21.30. Dynastie 3000
„Semitische Wissenschaften“? 1510
从k到英国情人 1500
Cummings Otolaryngology Head and Neck Surgery 8th Edition 800
热门求助领域 (近24小时)
化学 材料科学 生物 医学 工程类 计算机科学 有机化学 物理 生物化学 纳米技术 复合材料 内科学 化学工程 人工智能 催化作用 遗传学 数学 基因 量子力学 物理化学
热门帖子
关注 科研通微信公众号,转发送积分 5766395
求助须知:如何正确求助?哪些是违规求助? 5565174
关于积分的说明 15412411
捐赠科研通 4900635
什么是DOI,文献DOI怎么找? 2636548
邀请新用户注册赠送积分活动 1584789
关于科研通互助平台的介绍 1540042