• DocumentCode
    3390204
  • Title

    Statistical Quantification of Voltage Violations in Distribution Network with Small Wind Turbines

  • Author

    Long, Chao ; Farrag, Mohamed Emad ; Zhou, Chengke

  • Author_Institution
    Sch. of Eng. & Built Environ., Glasgow Caledonian Univ., Glasgow, UK
  • fYear
    2012
  • fDate
    27-29 March 2012
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    This paper develops a statistical methodology to identify the probabilities of when and where the voltage violations occurring in residential, industrial and commercial areas respectively with cumulative penetration of SWTs. The proposed methodology is applied to a typical U.K. distribution network model, and results indicate that industrial and commercial weekends have the highest probabilities of voltage violations, and voltage violations are more likely to occur on residential weekdays and weekends than that of industrial and commercial weekdays.
  • Keywords
    distribution networks; statistical analysis; wind turbines; SWTs; commercial area; industrial area; residential area; small wind turbine; statistical quantification; typical UK distribution network model; voltage violation; Load modeling; Probabilistic logic; Production; Time series analysis; Voltage control; Wind speed; Wind turbines;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Power and Energy Engineering Conference (APPEEC), 2012 Asia-Pacific
  • Conference_Location
    Shanghai
  • ISSN
    2157-4839
  • Print_ISBN
    978-1-4577-0545-8
  • Type

    conf

  • DOI
    10.1109/APPEEC.2012.6307216
  • Filename
    6307216