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
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