Nonintrusive Load Monitoring: A Temporal Multilabel Classification Approach

被引:133
作者
Basu, Kaustav [1 ]
Debusschere, Vincent [1 ]
Bacha, Seddik [1 ]
Maulik, Ujjwal [2 ]
Bondyopadhyay, Sanghamitra [3 ]
机构
[1] Grenoble Alpes Univ, G2ELab, F-38400 Grenoble, France
[2] Jadavpur Univ, Dept Comp Sci & Engn, Kolkata 700032, India
[3] Indian Stat Inst, Kolkata 700108, India
关键词
Appliances identification; disaggregating algorithms; energy management; machine learning; multilabel classification; nonintrusive load monitoring; smart grid; smart meter;
D O I
10.1109/TII.2014.2361288
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The article tackles the issues related to the identification of electrical appliances inside residential buildings. Each appliance can be identified from the aggregate power readings at the meter panel. The possibility of applying a temporal multilabel classification approach in the domain of nonintrusive load monitoring is explored (nonevent-based method). A novel set of metafeatures is proposed. The method is tested on sampling rates based on the capabilities of current smart meters. The proposed approach is validated over a dataset of energy readings at residences for a period of a year for 100 houses containing different sets of appliances (water heater, washing machines, etc.). This method is applicable for the demand side management of households in the current limitation of smart meters; from the inhabitants or from the grid operator's point of view.
引用
收藏
页码:262 / 270
页数:9
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