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
         
        
        
        
        
        
            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;
         
        
        
        
            Conference_Titel : 
IECON 2012 - 38th Annual Conference on IEEE Industrial Electronics Society
         
        
            Conference_Location : 
Montreal, QC
         
        
        
            Print_ISBN : 
978-1-4673-2419-9
         
        
            Electronic_ISBN : 
1553-572X
         
        
        
            DOI : 
10.1109/IECON.2012.6389365