• DocumentCode
    685317
  • Title

    Regional electricity load profile subclasses for distribution network planning

  • Author

    Booysen, J. ; Dekenah, Marcus

  • Author_Institution
    Enerweb-Demand Intell. Group, Johannesburg, South Africa
  • fYear
    2013
  • fDate
    20-21 Aug. 2013
  • Firstpage
    1
  • Lastpage
    8
  • Abstract
    Distribution electricity network planning needs consolidated regional and national views of predicted future loads. A power utility established load forecasting tool requires load profile data that will be used in calculating coincidence factors between loads of different classes and sub-classes as per economic activity and geospatial location. Regional industrial and commercial electricity load profile subclass models were developed for planning using clustering, geospatial significance testing and a BIC (Bayesian information criterion) technique to trade-off regional subclass complexity with overall profile model accuracy.
  • Keywords
    Bayes methods; load forecasting; power distribution planning; BIC; Bayesian information criterion technique; clustering; commercial electricity load profile subclass models; distribution electricity network planning; geospatial location; geospatial significance testing; load forecasting tool; power utility; regional electricity load profile subclass model; Animals; Biological system modeling; Complexity theory; Economics; Electricity; Shape; Testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Industrial and Commercial Use of Energy Conference (ICUE), 2013 Proceedings of the 10th
  • Conference_Location
    Cape Town
  • ISSN
    2166-0581
  • Print_ISBN
    978-0-9922041-3-6
  • Type

    conf

  • Filename
    6761637