• DocumentCode
    3656605
  • Title

    Analysis and prediction of electricity consumption using smart meter data

  • Author

    Antans Sauhats;Renata Varfolomejeva;Olegs Lmkevics;Romans Petrecenko;Maris Kunickis;Mans Balodis

  • Author_Institution
    Inst. of Power Eng., Riga Tech. Univ., Riga, Latvia
  • fYear
    2015
  • fDate
    5/1/2015 12:00:00 AM
  • Firstpage
    17
  • Lastpage
    22
  • Abstract
    This paper is considering application of smart meter data to predict electricity consumption of household consumers. The availability and amount of data is suitable for in-depth statistical analysis of electricity consumption profiles and the study of consumer´s behavior. Prediction of electricity consumption is very important for electricity traders to balance their electricity purchase and sales portfolio, as well as to prepare optimal price products (offers) for their clients. Electricity consumption data of 500 consumers divided into 6 consumers groups was analyzed. The consumption data was derived from smart meters. As the next step, modern methods of electricity consumption forecasts would be applied to predict household electricity consumption.
  • Keywords
    "Decision support systems","Nickel","Smart meters","Statistical analysis"
  • Publisher
    ieee
  • Conference_Titel
    Power Engineering, Energy and Electrical Drives (POWERENG), 2015 IEEE 5th International Conference on
  • Print_ISBN
    978-1-4673-7203-9
  • Electronic_ISBN
    2155-5532
  • Type

    conf

  • DOI
    10.1109/PowerEng.2015.7266290
  • Filename
    7266290