An automatic energy saving strategy for a water dispenser based on user behavior

地铁列车时刻表 能源消耗 用水量 消费(社会学) 计算机科学 模式(计算机接口) 水冷 实时计算 模拟 汽车工程 工艺工程 工程类 废物管理 电气工程 机械工程 操作系统 社会科学 社会学
作者
Shuo‐Yan Chou,Anindhita Dewabharata,Yudhistira C. Bayu,Ray-Guang Cheng,Ferani E. Zulvia
出处
期刊:Advanced Engineering Informatics [Elsevier]
卷期号:51: 101503-101503 被引量:7
标识
DOI:10.1016/j.aei.2021.101503
摘要

Nowadays, numerous public buildings provide water dispensers to supply drinking water which causes more energy consumption. A typical water dispenser periodically heats and cools the water to ensure that hot, warm, and cold water are always available for the user. However, this mechanism is inefficient because the users do not request hot and cool water continuously. Ideally, the boiling and cooling schedule should follow the demand pattern to save electricity consumption. When no demand, a water dispenser can enter a sleep mode. Therefore, this study presents an automatic energy-saving strategy for a water dispenser based on user behavior. The proposed system allows the water dispenser to automatically determine the appropriate time to heat, boil, and enter sleep mode based on user behavior. The proposed control strategy involves several steps. First, it collects historical data, analyzes water consumption behavior. The sensors installed in the water dispenser collect water consumption data. Second, this study applies Recurrent Neural Networks with Long-Short Term Memory to predict future water consumption. Finally, the proposed system utilizes the prediction result to determine heating, cooling, and sleep mode schedule. This study uses a water dispenser on a university campus as a prototype to test the proposed system. The effectiveness of the proposed system is measured by two factors, namely electricity consumption, and customer satisfaction. These two parameters are chosen because the proposed system should reduce electricity consumption while maintaining hot and cold water availability whenever needed. According to the simulation results, the proposed controlling strategy can reduce electricity consumption up to 28% monthly while maintaining a service level of 97%. This result shows that the proposed system is a good control system for water dispensers. By applying this controlling system, public buildings could reduce their energy bills without sacrificing their provision of drinking water.
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
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
颗粒完成签到,获得积分10
刚刚
刚刚
2秒前
Elsa完成签到,获得积分10
2秒前
2秒前
榴下晨光完成签到 ,获得积分10
2秒前
2秒前
3秒前
3秒前
章铭-111发布了新的文献求助10
3秒前
薪炭林应助su采纳,获得10
4秒前
am完成签到 ,获得积分10
4秒前
Hangerli发布了新的文献求助10
5秒前
Akim应助嘟嘟采纳,获得10
6秒前
6秒前
优雅铭完成签到,获得积分10
6秒前
Elsa发布了新的文献求助10
7秒前
7秒前
Mars完成签到,获得积分10
8秒前
杰克完成签到,获得积分20
8秒前
Chen关注了科研通微信公众号
9秒前
红红发布了新的文献求助10
9秒前
10秒前
小二郎应助高磊采纳,获得10
10秒前
11秒前
yu完成签到,获得积分10
11秒前
li完成签到,获得积分10
12秒前
Stephanie发布了新的文献求助10
14秒前
口腔飞飞完成签到 ,获得积分10
14秒前
充电宝应助翠翠采纳,获得10
14秒前
雨下着的坡道完成签到,获得积分10
16秒前
lisizheng完成签到,获得积分10
16秒前
科研通AI2S应助汤姆采纳,获得10
17秒前
高磊完成签到,获得积分10
17秒前
WZ0904发布了新的文献求助10
17秒前
Akim应助无情向梦采纳,获得10
17秒前
joey完成签到,获得积分10
18秒前
19秒前
所所应助坚强的樱采纳,获得10
19秒前
20秒前
高分求助中
Continuum Thermodynamics and Material Modelling 3000
Production Logging: Theoretical and Interpretive Elements 2700
Social media impact on athlete mental health: #RealityCheck 1020
Ensartinib (Ensacove) for Non-Small Cell Lung Cancer 1000
Unseen Mendieta: The Unpublished Works of Ana Mendieta 1000
Bacterial collagenases and their clinical applications 800
El viaje de una vida: Memorias de María Lecea 800
热门求助领域 (近24小时)
化学 材料科学 生物 医学 工程类 有机化学 生物化学 物理 纳米技术 计算机科学 内科学 化学工程 复合材料 基因 遗传学 物理化学 催化作用 量子力学 光电子学 冶金
热门帖子
关注 科研通微信公众号,转发送积分 3527961
求助须知:如何正确求助?哪些是违规求助? 3108159
关于积分的说明 9287825
捐赠科研通 2805882
什么是DOI,文献DOI怎么找? 1540070
邀请新用户注册赠送积分活动 716926
科研通“疑难数据库(出版商)”最低求助积分说明 709808