• DocumentCode
    2578356
  • Title

    Load modelling and voltage stability analysis by neural networks

  • Author

    Chen, D. ; Mohler, R.

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Oregon State Univ., Corvallis, OR, USA
  • Volume
    2
  • fYear
    1997
  • fDate
    4-6 Jun 1997
  • Firstpage
    1086
  • Abstract
    Voltage stability analysis is very important for predicting the potential voltage instability. Load modelling plays a key role in voltage stability assessment. In this paper, several kinds of neural networks are applied for load modelling. Loading patterns are classified through Kohonen self-organization mapping. Furthermore, this paper presents the strategies to insert the neural network load model into static and dynamic voltage stability analysis. The proposed methods are tested either on the IEEE 14-bus system or real data
  • Keywords
    load (electric); power system analysis computing; power system stability; self-organising feature maps; IEEE 14-bus system; Kohonen self-organization mapping; dynamic voltage stability analysis; load modelling; loading patterns; neural networks; static voltage stability analysis; Feedforward neural networks; Feedforward systems; Function approximation; Load modeling; Neural networks; Power system modeling; Stability analysis; Steady-state; System testing; Voltage;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    American Control Conference, 1997. Proceedings of the 1997
  • Conference_Location
    Albuquerque, NM
  • ISSN
    0743-1619
  • Print_ISBN
    0-7803-3832-4
  • Type

    conf

  • DOI
    10.1109/ACC.1997.609700
  • Filename
    609700