• DocumentCode
    1633702
  • Title

    Dynamic load modelling of electric locomotive for power quality assessment of utilities

  • Author

    Shaobing, Y. ; Mingli, W.

  • Author_Institution
    Beijing Jiaotong Univ., Beijing, China
  • fYear
    2010
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    The AC 25 kV electric railways with DC drive locomotives are one of the main harmonic pollution sources of electric power grids in China. To assess the power quality of the railway supply networks needs to model not only the fundamental currents of the trains but also their harmonic contents. It is difficult to simulate accurately the dynamic current waveforms of an electric locomotive running on real lines because there are too many random or uncontrolled factors that can intervene the working state of the main power circuit of the locomotive. This paper presents a modelling method which can be used to imitate the probabilistic property of the current waveform and can be embedded in the train simulator. This method is based on statistical analysis of a large amount of measured data of locomotive currents that were acquired on actual railway line. A computer program has been developed for the 8K locomotive, a kind of widely used locomotives for freight services in China. The program has been applied to assess the power quality of railway power supply utilities, which shows that this modelling method can give a very realistic result from the statistics point of view and has a fast speed in the simulation.
  • Keywords
    electric locomotives; power grids; power supply quality; statistical analysis; China; DC drive locomotives; dynamic load modelling; electric locomotives; electric power grids; electric railways; power harmonics; power quality assessment; statistical analysis; Electric locomotives; harmonics; load modelling; power quality; probabilistic model;
  • fLanguage
    English
  • Publisher
    iet
  • Conference_Titel
    Railway Traction Systems (RTS 2010), IET Conference on
  • Conference_Location
    Birmingham
  • Type

    conf

  • DOI
    10.1049/ic.2010.0016
  • Filename
    5552131