New Method for Non-intrusive Data Extraction and Classification of Residential Appliances
This paper is focused on the non-intrusive load monitoring(NILM) system, which allows the identi.cation of residential appliances in a non-intrusive way. The previous techniques are not performing perfectly in all aspects of economy, feasibility and accuracy. A new method, via the feature of working style and power characteristic of residential appliances, using human reaction time as the time scale unit (sampling frequency), to complete the classi.cation and identification in a financially viable and easily applicable solution. The attribution of this paper is simplify the identi.cation, which can be integrated into the meters now, and this simplification will improve the application of NILM system in demand side management(DSM). Feature selection, mathematic model and algorithm details are described. Analysis of typical experiments is shown in detail. Classi.cation objects including 12 important power consumption types of the most common residential appliances.
NILM Data Extraction Residential Appliances Classification
Zhenyu Wang Guilin Zheng
Department of Automation, Wuhan University Wuhan, Hubei Province, China
国际会议
2011 China Control and Decision Conference(2011中国控制与决策会议 CCDC)
四川绵阳
英文
2200-2205
2011-05-23（万方平台首次上网日期，不代表论文的发表时间）