Title :
Intelligent electrical event recognition on general household power appliances
Author :
Lei Jiang ; Suhuai Luo ; Jiaming Li
Author_Institution :
Sch. of DCIT, Univ. of Newcastle, Newcastle, NSW, Australia
Abstract :
The management of electricity system in home environments plays an important role in managing energy consumption and improving efficiency of energy usage. At present, nonintrusive appliance load monitoring (NIALM) techniques are the most effective approach for estimating the electrical power consumption of individual appliances. This paper presents our contributions in intelligent electrical appliance recognition in home environment. The novel method is for general power load classification and disaggregation which is mainly carried out by combining support vector machines with various power features. The experiments on real world data have demonstrated higher recognition accuracy and faster computational speed of the approach, and illustrated the effectiveness for distinguishing the different loads with promising results.
Keywords :
domestic appliances; energy consumption; support vector machines; electricity system management; energy consumption management; general household power appliances; intelligent electrical event recognition; nonintrusive appliance load monitoring techniques; power load classification; support vector machines; Microwave circuits; Microwave ovens; Monitoring; Portable computers; Support vector machines; NIALM; electrical feature extraction; general power appliance; pattern recognition; smart meter;
Conference_Titel :
Control and Modeling for Power Electronics (COMPEL), 2014 IEEE 15th Workshop on
Conference_Location :
Santander
DOI :
10.1109/COMPEL.2014.6877183
