基于数据挖掘的楼宇电力能耗分析模型研究  

Study on the power consumption analysis model of building based on data mining

作　　者：林顺富 胡飞 郝朝 李东东 符杨 Lin Shunfu;Hu Fei;Hao Chao;Li Dongdong;Fu Yang(College of Electrical Engineering,Shanghai University of Electric Power,Shanghai 200090,China;Huairou Power Supply Company,Beijing Electric Power Company,Beijing 101400,China)

机构地区：[1]上海电力学院电气工程学院,上海200090 [2]北京电力公司怀柔供电公司,北京101400

出　　处：《电测与仪表》2018年第20期52-59,共8页Electrical Measurement & Instrumentation

基　　金：国家自然科学基金资助项目(51207088);上海市科委科创项目资助(14DZ1201602);上海绿色能源并网工程技术研究中心(13DZ2251900)

摘　　要：电力能耗分析对于建筑楼宇制定有效节能方案具有重要指导意义。提出一种基于K-均值聚类和FP-Growth关联规则的楼宇电力能耗分析模型,对商业楼宇总能耗、分项计量数据、气象温度等数据进行数据挖掘,得到具有一定启发性的强关联规则,为进一步完善楼宇设备的优化运行策略提供理论支撑。将所提方法应用于上海某栋建筑楼宇的能耗分析中,验证了所提方法的有效性和实用性。Power consumption analysis is instructive to formulate effective energy-saving scheme in buildings.This paper proposes an analysis model of power consumption in buildings based on K-means clustering and FP-Growth association rules.It has been some inspiration of strong association rules through cluster analysis and association analysis to the total energy consumption of commercial buildings,sub metering data and weather temperature data,which provides the theory support for improving the optimal operation strategy of building equipment.The proposed method was applied to the energy consumption analysis of an office building in Shanghai.The results proved that the presented technique is of the validity and practicability.

关 键 词：电力能耗分析 楼宇节能 数据挖掘 K-均值 频繁树增长 

分 类 号：TM933[电气工程—电力电子与电力传动]