[1]陈淑琴,李鑫悦,李鸿亮,等.基于数据挖掘的空调使用行为特征及运行模式分析[J].南京理工大学学报(自然科学版),2020,44(06):637-644.[doi:10.14177/j.cnki.32-1397n.2020.44.06.001]
 Chen Shuqin,Li Xinyue,Li Hongliang,et al.Data mining based behavior characteristics analysis andoperation mode for air-conditioning use[J].Journal of Nanjing University of Science and Technology,2020,44(06):637-644.[doi:10.14177/j.cnki.32-1397n.2020.44.06.001]
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基于数据挖掘的空调使用行为特征及运行模式分析()
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《南京理工大学学报》(自然科学版)[ISSN:1005-9830/CN:32-1397/N]

卷:
44卷
期数:
2020年06期
页码:
637-644
栏目:
出版日期:
2020-12-31

文章信息/Info

Title:
Data mining based behavior characteristics analysis andoperation mode for air-conditioning use
文章编号:
1005-9830(2020)06-0637-08
作者:
陈淑琴1李鑫悦1李鸿亮23楼云霄3
浙江大学 1.建筑工程学院; 2.控制科学与工程学院,浙江 杭州 310027; 3.浙江中易和节能技术有限公司,浙江 杭州 310052
Author(s):
Chen Shuqin1Li Xinyue1Li Hongliang23Lou Yunxiao3
1.College of Civil Engineering and Architecture; 2.College of Control Scienceand Engineering,Zhejiang University,Hangzhou 310027,China; 3.Zhejiang Excenergy Energy-saving Technology Co.,Ltd.,Hangzhou 310052,China
关键词:
数据挖掘 空调 行为特征 运行模式 教学建筑 关联规则分析
Keywords:
data mining air-conditioning behavior characteristics operation mode teaching buildings association rule analysis
分类号:
TU201.5
DOI:
10.14177/j.cnki.32-1397n.2020.44.06.001
摘要:
为明确教学建筑的空调使用特征以及其运行规则,该文基于某高校校园节能监管平台夏季逐时监测数据,统计分析了校园内的空调使用行为特征以及温度特征。利用数据挖掘中的关联规则分析方法提炼了空调使用行为的频繁模式,并揭示了不同空调使用行为与室内温度的对应关系。结果表明,高校授课期间空调使用5 h以下情况占比为67.2%,且空调开启时间在上午与下午的占比接近。得到了短时间、中长时间、长时间空调使用情况下的3种频繁模式:短时间使用情况下,空调设定温度低于26 ℃,空调开启时温度通常处于热感受为中性的温度区间; 长时间使用情况下,空调设定温度高于26 ℃,且开启时室内温度对应热感受为暖的温度区间。
Abstract:
In order to make clear the air-conditioning use characteristics of teaching buildings and its operation rules,based on the hourly monitoring data of a campus energy-saving monitoring platform in summer,the air-conditioning use behavior characteristics and temperature characteristics in the campus are analyzed. Using association rule analysis method in data mining,the frequent patterns of air-conditioning use behavior are extracted,and the corresponding relationships between different air-conditioning use behavior and the indoor temperature are revealed. The results illustrate that air-conditioning operation with usage hour shorter than 5 hours has the largest proportion of 67.2% in school days,and the proportion of air-conditioning on time in the morning and afternoon is close. Three frequent patterns of short-term,medium-term and long-term air-conditioner use are obtained:under short-term use,the set temperature of the air-conditioning is lower than 26 ℃,and the indoor temperature is usually in the temperature range of thermal neutral when the air-conditioning is turned on; under long-term use,the set temperature of the air-conditioning is higher than 26 ℃,and the indoor temperature corresponds to the temperature range of warm when the air-conditioning is turned on.

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备注/Memo

备注/Memo:
收稿日期:2019-03-07 修回日期:2019-06-13
基金项目:国家重点研发计划(2016YFC0700301); 国家自然科学基金(51508500)
作者简介:陈淑琴(1981-),女,博士,副教授,博士生导师,主要研究方向:建筑与能源系统优化设计与运行,E-mail:hn_csq@126.com; 通讯作者:李鸿亮(1976-),男,博士,副研究员,硕士生导师,主要研究方向:智能控制,E-mail:lihongliang_zju@zju.edu.cn。
引文格式:陈淑琴,李鑫悦,李鸿亮,等. 基于数据挖掘的空调使用行为特征及运行模式分析[J]. 南京理工大学学报,2020,44(6):637-644.
投稿网址:http://zrxuebao.njust.edu.cn
更新日期/Last Update: 2020-12-30