• DocumentCode
    740823
  • Title

    Simplified probabilistic voltage stability evaluation considering variable renewable distributed generation in distribution systems

  • Author

    Ke-yan Liu ; Wanxing Sheng ; Lijuan Hu ; Yongmei Liu ; Xiaoli Meng ; Dongli Jia

  • Author_Institution
    Power Distrib. Res. Dept., China Electr. Power Res. Inst., Beijing, China
  • Volume
    9
  • Issue
    12
  • fYear
    2015
  • Firstpage
    1464
  • Lastpage
    1473
  • Abstract
    This study investigates the evaluation of static voltage stability using a two-point estimation method (2PEM) and continuation power flow (CPF) in distribution systems. The stochastic distribution generation (DG) units have been considered with their respective probability density function (PDF). The proposed static voltage stability evaluation method first chooses several sample points to replace the PDFs using 2PEM. Then, based on each sample point, the critical static voltage stability value is calculated by CPF. On the basis of the critical values corresponding to all selected sample points, Cornish-Fisher series are used to evaluate the PDF of the critical static voltage stability, and then the static voltage stability state can be obtained. The proposed method has been tested on IEEE 33-bus, PG&E 69-bus and a real case with two stochastic DG units. Comparisons have been made with the Monte Carlo simulation and the first-order second-moment method. The results show that the proposed method has better efficiency and accuracy.
  • Keywords
    distributed power generation; load flow; power system stability; stochastic processes; 2PEM; CPF; Cornish-Fisher series; DG units; IEEE 33-bus; Monte Carlo simulation; PDF; PG&E 69-bus; continuation power flow; distribution systems; first-order second-moment method; probability density function; simplified probabilistic voltage stability evaluation; stochastic distribution generation; two-point estimation method; variable renewable distributed generation;
  • fLanguage
    English
  • Journal_Title
    Generation, Transmission & Distribution, IET
  • Publisher
    iet
  • ISSN
    1751-8687
  • Type

    jour

  • DOI
    10.1049/iet-gtd.2014.0840
  • Filename
    7224098