• DocumentCode
    732178
  • Title

    Statistical treatment for trend detection and analyzing of electrical load using programming language R

  • Author

    Keka, Ilir ; Cico, Betim

  • Author_Institution
    Fac. of Contemporary Sci. & Technol. (CST), South East Eur. Univ. (SEEU), Tetovo, Macedonia
  • fYear
    2015
  • fDate
    14-18 June 2015
  • Firstpage
    216
  • Lastpage
    219
  • Abstract
    The data collected based on the electricity stream in a PowerSystem could be very useful information for electricity companies. This information is related to the electrical demand of the customers. The aim of this paper is to analyze and to detect the trend of electrical load consume from the customers in an area. This is achieved using the statistical approach on the data collected from the meter reading devices. In this paper is given an overview of the features of electricity and also are calculated some statistical parameters. The statistical treatment is done in the electrical data based on R language.
  • Keywords
    customer services; demand side management; high level languages; power system analysis computing; statistical analysis; PowerSystem; electrical demand; electrical load; electricity companies; electricity stream; programming language R; statistical treatment; trend detection; Embedded computing; Gaussian distribution; Graphics; Histograms; Market research; Power systems; Standards; Electrical Load; R Language; Statistic; Trend Detection;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Embedded Computing (MECO), 2015 4th Mediterranean Conference on
  • Conference_Location
    Budva
  • Print_ISBN
    978-1-4799-8999-7
  • Type

    conf

  • DOI
    10.1109/MECO.2015.7181906
  • Filename
    7181906