DocumentCode :
581401
Title :
Smart meter systems detection & classification using artificial neural networks
Author :
Bier, Thomas ; Abdeslam, Djaffar Quid ; Merckle, Jean ; Benyoucef, Dirk
Author_Institution :
Univ. Furtwangen, Furtwangen, Germany
fYear :
2012
fDate :
25-28 Oct. 2012
Firstpage :
3324
Lastpage :
3329
Abstract :
The goal of that paper is to show a possibility for the disaggregation of electrical appliances in the power profile of residential buildings. The advantage is that the measurement system is at a central point in the household. So the installation effort decrease. For the disaggregation of the appliances out of the load curve, an approach for the development of a system based on pattern recognition is presented. One method for the classification of appliances is to use Artificial Neural Network. This idea is the main part of that paper. It is shown a method, to classify one kind of appliances. At the end, the first results and a comparison with the famous approach, for the disaggregation of electrical appliances, from Hart is presented.
Keywords :
building management systems; domestic appliances; electrical products; intelligent sensors; neural nets; pattern recognition; power engineering computing; smart meters; artificial neural network; electrical appliance; load curve; pattern recognition; residential building; smart classification system; smart detection system; smart meter system; Artificial neural networks; Manuals; Monitoring; Refrigerators; Switches; Weight measurement;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
IECON 2012 - 38th Annual Conference on IEEE Industrial Electronics Society
Conference_Location :
Montreal, QC
ISSN :
1553-572X
Print_ISBN :
978-1-4673-2419-9
Electronic_ISBN :
1553-572X
Type :
conf
DOI :
10.1109/IECON.2012.6389365
Filename :
6389365
Link To Document :
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