DocumentCode :
1799949
Title :
Customer classification and load profiling using data from Smart Meters
Author :
Grigoras, Gheorghe ; Ivanov, Ovidiu ; Gavrilas, Mihai
Author_Institution :
Dept. of Power Syst., Gh. Asachi Tech. Univ., Iasi, Romania
fYear :
2014
fDate :
25-27 Nov. 2014
Firstpage :
73
Lastpage :
78
Abstract :
The paper presents a self-organization based integrated model for customer classification and load profiling in distribution systems. The consumer classification in consumption classes characterized by typical load profiles is made using information provided by Smart Meters. For determination of the consumption classes, every customer is characterized by the following primary information: daily (monthly) energy consumption, minimum and maximum loads. The proposed model was tested using household consumers from a rural area. The results demonstrate the ability of the methodology to efficiently used in distribution systems when information about the supplied customers is very poor (based only the data provided by classic meters).
Keywords :
customer services; load management; power distribution economics; smart meters; consumption classes determination; customer classification; daily energy consumption; distribution systems; load profiling; maximum loads; minimum loads; self-organization based integrated model; smart meters; Companies; Databases; Energy consumption; Load modeling; Neurons; Smart meters; Customer classification; distribution systems; load profiling; self-organization; smart meters;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Network Applications in Electrical Engineering (NEUREL), 2014 12th Symposium on
Conference_Location :
Belgrade
Print_ISBN :
978-1-4799-5887-0
Type :
conf
DOI :
10.1109/NEUREL.2014.7011464
Filename :
7011464
Link To Document :
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