DocumentCode :
976374
Title :
Load pattern-based classification of electricity customers
Author :
Chicco, Gianfranco ; Napoli, Roberto ; Piglione, Federico ; Postolache, Petru ; Scutariu, Mircea ; Toader, Cornel
Author_Institution :
Dipt. di Ingegneria Elettrica Industriale, Politecnico di Torino, Italy
Volume :
19
Issue :
2
fYear :
2004
fDate :
5/1/2004 12:00:00 AM
Firstpage :
1232
Lastpage :
1239
Abstract :
Accurate knowledge of the customers´ consumption patterns represents a worthwhile asset for electricity providers in competitive electricity markets. Various approaches can be used for grouping customers that exhibit similar electrical behavior into customer classes. In this paper, we focus on two approaches for customer classification-a modified follow-the-leader algorithm and the self-organizing maps. We include an overview of basic theory for these methods and discuss the performance of the customer classification on the real case of a set of customers supplied by a distribution company. We compare the results obtained from the two approaches by means of two suitably defined adequacy indicators and discuss the potential applications of the surveyed approaches.
Keywords :
customer services; load distribution; power consumption; power distribution economics; power markets; self-organising feature maps; adequacy indicator; clustering algorithm; customer consumption pattern; distribution company; electricity customers; electricity market; electricity provider; load pattern; load pattern-based classification; self-organizing map; Classification algorithms; Costs; Data mining; Electricity supply industry; Energy consumption; Monitoring; Neural networks; Pattern analysis; Power engineering; Self organizing feature maps;
fLanguage :
English
Journal_Title :
Power Systems, IEEE Transactions on
Publisher :
ieee
ISSN :
0885-8950
Type :
jour
DOI :
10.1109/TPWRS.2004.826810
Filename :
1295037
Link To Document :
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