• DocumentCode
    132233
  • Title

    Analysis of customer profiles on an electrical distribution network

  • Author

    Akperi, Brian ; Matthews, Peter

  • Author_Institution
    Sch. of Eng. & Comput. Sci., Durham Univ., Durham, UK
  • fYear
    2014
  • fDate
    2-5 Sept. 2014
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    It has become increasingly important for electrical distribution companies to understand the drivers of demand. The maximum demand at any given substation can vary materially on an annual basis which means it is difficult to create a load related investment plan that is robust and stable. Currently, forecasts are based only on historical demand with little understanding about contributions to load profiles. In particular, the unique diversity of customers on any particular substation can affect load profile shape and future forecasts. Domestic and commercial customers can have very different behaviours generally and within these groups there is room for variation due to economic conditions and building types. This paper analyses customer types associated to substations on a distribution network by way of principal component analysis and identification of substations which deviate from the national demand trend. By examining the variance spread of this deviation, data points can be labelled in the principal component space. Groups of substations can then be categorised as having typical or atypical load profiles. This will support the need for further investigation into particular customer types and highlight the key factors of customer categorisation.
  • Keywords
    distribution networks; load (electric); principal component analysis; customer categorisation; customer profiles analysis; economic conditions; electrical distribution companies; electrical distribution network; load profiles; principal component analysis; principal component space; substations; Buildings; Educational institutions; Loading; Market research; Measurement; Principal component analysis; Substations; Clustering methods; Load modeling; Power distribution; Principal component analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Power Engineering Conference (UPEC), 2014 49th International Universities
  • Conference_Location
    Cluj-Napoca
  • Print_ISBN
    978-1-4799-6556-4
  • Type

    conf

  • DOI
    10.1109/UPEC.2014.6934624
  • Filename
    6934624