• 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