摘要
针对能耗监测常用的设定能耗阈值方法和基于历史数据的数据分析方法在实时性和智能性方面的不足,提出了一种基于数据挖掘技术的能耗实时监测方法。该方法通过对历史能耗数据进行聚类分析识别耗能体特有的能耗模式集合,对数据分类后获得能耗模式判定树,在能耗实时监测过程中对动态采集的能耗数据进行模式匹配,与相同模式历史数据进行离群点分析,可判别当前能耗是否异常。结合某综合大楼能耗数据进行了实验,验证了该方法及时发现能耗数据异常的有效性。
A real-time monitoring method of energy consumption based on data mining techniques is proposed to compensate the deficiency of common energy consumption methods in real time and intelligence.The new method can identify energy consumption patterns by clustering analysis of historical energy consumption data,get the decision tree of energy consumption pattern by classifying the energy consumption data,match the real-time energy consumption data with the energy consumption patterns,make outlier analysis with historical data of the same pattern,and then determine whether the current energy consumption is abnormal.The experiment with energy consumption data from the comprehensive building proves that the new method is effective in detecting the abnormal data of energy consumption real-timely.
出处
《重庆大学学报（自然科学版）》
EI
CAS
CSCD
北大核心
2012年第7期133-137,共5页
Journal of Chongqing University
基金
国家科技重大专项资助项目(2009ZX07315-005)
重庆大学研究生创新基金个人项目资助项目(CDJXS11180016)
关键词
能耗
能源管理
数据挖掘
实时
监测
energy consumption
energy management
data mining
real-time
monitoring
