• DocumentCode
    2446166
  • Title

    High frequency fault location method for transmission lines based on artificial neural network and genetic algorithm using current signals only

  • Author

    Aggarwal, Raj K. ; Blond, S.L. ; Beaumont, Phil ; Baber, G. ; Kawano, Fumio ; Miura, Shun

  • Author_Institution
    University of Bath, United kingdom
  • fYear
    2012
  • fDate
    23-26 April 2012
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    The present transmission systems are rapidly changing principally due to an increasing demand for better utilisation of existing lines resulting in lower transient stability limits, and also due to an increase in the complexity of the networks with small-scale distributed generation being connected into the existing networks. The current protection/fault location techniques are not conducive to such networks. This paper investigates a novel fault location method based on current signals only and utilising Artificial Intelligence technology. Importantly, the robustness and sensitivity of the technique developed is presented through an extensive series of studies and results when applied to complex power networks.
  • Keywords
    Artificial neural networks; Fault location; Genetic algorithms; Power transmission lines; Resistance; Transient analysis; artificial neural networks; fault current signals; fault location; genetic algorithm; transmission lines;
  • fLanguage
    English
  • Publisher
    iet
  • Conference_Titel
    Developments in Power Systems Protection, 2012. DPSP 2012. 11th International Conference on
  • Conference_Location
    Birmingham, UK
  • Print_ISBN
    978-1-84919-620-8
  • Type

    conf

  • DOI
    10.1049/cp.2012.0041
  • Filename
    6227527