Lean and interpretable digital twins for building energy monitoring – A case study with smart thermostatic radiator valves and gas absorption heat pumps

散热器(发动机冷却) 能源性能 高效能源利用 恒温器 能量(信号处理) 工程类 计算机科学 模拟 建筑工程 系统工程 工业工程 机械工程 汽车工程 电气工程 数学 统计
作者
Massimiliano Manfren,P.A.B. James,Victoria Aragon,Lamberto Tronchin
出处
期刊:Energy and AI [Elsevier]
卷期号:14: 100304-100304 被引量:14
标识
DOI:10.1016/j.egyai.2023.100304
摘要

The transition to low carbon energy systems poses challenges in terms of energy efficiency. In building refurbishment projects, efficient technologies such as smart controls and heat pumps are increasingly being used as a substitute for conventional technologies with the aim of reducing carbon emissions and determining operational energy and cost savings, together with other benefits. Measured building performance, however, often reveals a significant gap between the predicted energy use (design stage) and actual energy use (operation stage). For this reason, lean and interpretable digital twins are needed for building energy monitoring aimed at persistence of savings and continuous performance improvement. In this research, interpretable regression models are built with data at multiple temporal resolutions (monthly, daily and hourly) and seamlessly integrated with the goal of verifying the performance improvements due to Smart Thermostatic Radiator Valves (TRVs) and Gas Absorption Heat Pumps (GAHPs) as well as giving insights on the performance of the building as a whole. Further, as part of modelling research, Time Of Week and Temperature (TOWT) approach is reformulated and benchmarked against its original implementation. The case study chosen is Hale Court sheltered housing, located in the city of Portsmouth (UK). This building has been used for the field-testing of innovative technologies such as TRVs and GAHPs within the EU Horizon 2020 project THERMOSS. The results obtained are used to illustrate possible extensions of the use of energy signature modelling, highlighting implications for energy management and innovative building technologies development.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
大幅提高文件上传限制,最高150M (2024-4-1)

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
Neo完成签到,获得积分10
刚刚
xiuxiu完成签到 ,获得积分10
刚刚
刚刚
威武的匕完成签到,获得积分10
1秒前
张晓晓发布了新的文献求助10
1秒前
梦里完成签到 ,获得积分10
2秒前
铠甲勇士完成签到,获得积分10
2秒前
落寞平萱发布了新的文献求助10
2秒前
Dr大壮完成签到,获得积分10
3秒前
凑阿库娅完成签到,获得积分10
5秒前
6秒前
天空的小白完成签到,获得积分10
7秒前
7秒前
COC完成签到,获得积分10
8秒前
爱喝水完成签到,获得积分10
9秒前
吴明轩完成签到,获得积分10
9秒前
Owen发布了新的文献求助10
10秒前
12发布了新的文献求助10
10秒前
孟孟发布了新的文献求助10
10秒前
11秒前
铁甲小宝发布了新的文献求助10
12秒前
李帅完成签到,获得积分10
12秒前
内向苡完成签到,获得积分10
12秒前
深情安青应助聪明的宛菡采纳,获得10
12秒前
淡然向南发布了新的文献求助10
13秒前
stephen完成签到,获得积分10
14秒前
酷酷从雪发布了新的文献求助80
15秒前
haoooooooooooooo完成签到,获得积分10
15秒前
16秒前
甜美的音响完成签到 ,获得积分10
17秒前
18秒前
HH应助wang5945采纳,获得10
18秒前
lois完成签到,获得积分10
19秒前
小篆完成签到 ,获得积分10
19秒前
火枪手发布了新的文献求助10
19秒前
20秒前
20秒前
落寞平萱完成签到,获得积分20
20秒前
坚定白风发布了新的文献求助10
21秒前
二师兄来挨打完成签到,获得积分10
22秒前
高分求助中
Sustainability in Tides Chemistry 2800
Kinetics of the Esterification Between 2-[(4-hydroxybutoxy)carbonyl] Benzoic Acid with 1,4-Butanediol: Tetrabutyl Orthotitanate as Catalyst 1000
The Young builders of New china : the visit of the delegation of the WFDY to the Chinese People's Republic 1000
Rechtsphilosophie 1000
Bayesian Models of Cognition:Reverse Engineering the Mind 888
Handbook of Qualitative Cross-Cultural Research Methods 600
Very-high-order BVD Schemes Using β-variable THINC Method 568
热门求助领域 (近24小时)
化学 医学 生物 材料科学 工程类 有机化学 生物化学 物理 内科学 纳米技术 计算机科学 化学工程 复合材料 基因 遗传学 催化作用 物理化学 免疫学 量子力学 细胞生物学
热门帖子
关注 科研通微信公众号,转发送积分 3137360
求助须知:如何正确求助?哪些是违规求助? 2788429
关于积分的说明 7786365
捐赠科研通 2444582
什么是DOI,文献DOI怎么找? 1300002
科研通“疑难数据库(出版商)”最低求助积分说明 625695
版权声明 601023