• DocumentCode
    1159609
  • Title

    Online Synchronous Machine Parameter Extraction From Small-Signal Injection Techniques

  • Author

    Huang, Jing ; Corzine, Keith A. ; Belkhayat, Mohamed

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Missouri Univ. of Sci. & Technol., Rolla, MO
  • Volume
    24
  • Issue
    1
  • fYear
    2009
  • fDate
    3/1/2009 12:00:00 AM
  • Firstpage
    43
  • Lastpage
    51
  • Abstract
    This paper proposes using a novel line-to-line voltage perturbation as a technique for online measurement of synchronous machine parameters. The perturbation is created by a chopper circuit connected between two phases of the machine. Using this method, it is possible to obtain the full set of four complex small-signal impedances of the synchronous machine d-q model over a wide frequency range. Typically, two chopper switching frequencies are needed to obtain one data point. However, it is shown herein that, due to the symmetry of the machine equations, only one chopper switching frequency is needed to obtain the information. A 3.7-kW machine system is simulated, and then constructed for validation of the impedance measurement technique. A genetic algorithm is then used to obtain IEEE standard model parameters from the d -q impedances. The resulting parameters are shown to be similar to those obtained by a series of tests involving synchronous reactance measurements and a standstill frequency response.
  • Keywords
    choppers (circuits); genetic algorithms; machine control; parameter estimation; synchronous machines; IEEE standard model parameters; chopper circuit; genetic algorithm; impedance measurement; line-to-line voltage perturbation; online measurement; online synchronous machine parameter extraction; small-signal injection techniques; standstill frequency response; synchronous machine d-q model; synchronous reactance measurements; Generator; genetic algorithm (GA); impedance; motor; online measurement; parameter; synchronous machine;
  • fLanguage
    English
  • Journal_Title
    Energy Conversion, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0885-8969
  • Type

    jour

  • DOI
    10.1109/TEC.2008.2008953
  • Filename
    4783111