• DocumentCode
    2275166
  • Title

    A novel approach for improving voltage stability margin by sensitivity analysis of Neural Network

  • Author

    Aghamohammadi, M.R. ; Hashemi, S. ; Ghazizadeh, M.S.

  • Author_Institution
    Dept. of Electr. Eng., Power & Water Univ. of Technol., Tehran, Iran
  • fYear
    2010
  • fDate
    27-29 Oct. 2010
  • Firstpage
    280
  • Lastpage
    286
  • Abstract
    This paper presents a new approach for estimating and improving voltage stability margin from phase and magnitude profiles of bus voltages using sensitivity analysis of Voltage Stability Assessment Neural Network (VSANN). Voltage profile contains useful information about system stability margin including the effect of load-generation pattern, line outage and reactive power compensation, so it is adopted as the input pattern of VSANN. In fact, VSANN approximates the functional relationship between VSM and the voltage profile. The sensitivity analysis of VSM with respect to reactive power compensation extracted from information stored in the weighting factor of VSANN is the most dominant feature of the proposed approach. Sensitivity of VSM helps one to select the most effective buses for reactive power compensation aimed to enhance VSM. The proposed approach has been implemented in IEEE 39-bus test system with promising results showing its effectiveness and applicability.
  • Keywords
    neural nets; power engineering computing; power system security; power system stability; reactive power; sensitivity analysis; IEEE 39-bus test system; VSANN; VSM; bus voltages; line outage; load-generation pattern; power system security; reactive power compensation; sensitivity analysis; voltage stability assessment neural network; voltage stability margin; Feature Extraction; Neural Networks; Sensitivity Analysis; Voltage security margin;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    IPEC, 2010 Conference Proceedings
  • Conference_Location
    Singapore
  • ISSN
    1947-1262
  • Print_ISBN
    978-1-4244-7399-1
  • Type

    conf

  • DOI
    10.1109/IPECON.2010.5697145
  • Filename
    5697145