• DocumentCode
    154318
  • Title

    Dispersed filters for power system state estimation

  • Author

    Kozierski, Piotr ; Lis, Marcin ; Owczarkowski, Adam ; Horla, Dariusz

  • Author_Institution
    Fac. of Electr. Eng., Poznan Univ. of Technol., Poznan, Poland
  • fYear
    2014
  • fDate
    2-5 Sept. 2014
  • Firstpage
    129
  • Lastpage
    133
  • Abstract
    The article proposes an approach to power system state estimation allowing the division of the network into smaller parts and performing calculations for each part at the same time. The latter can be implemented in parallel, but the main aim has been to propose a method for dispersed calculations, i.e. calculations that may be performed on computing units located at various points of the whole power system. In the paper, there are 3 algorithms for which dispersed versions have been proposed: Extended Kalman Filter, Particle Filter and Extended Kalman Particle Filter. As a result of the simulations, it has been verified that the Dispersed Particle Filter works better than simple Particle Filter. In two other cases, distributed algorithms work worse, but for the Extended Kalman Filter degradation in the estimation quality is not significant.
  • Keywords
    Kalman filters; nonlinear filters; particle filtering (numerical methods); power system state estimation; computing units; dispersed calculations; dispersed particle filter; distributed algorithms; extended Kalman particle filter; network division; power system state estimation; Filtering algorithms; Kalman filters; Particle filters; Power measurement; Power systems; State estimation; dispersed filters; particle filter; power system; state estimation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Methods and Models in Automation and Robotics (MMAR), 2014 19th International Conference On
  • Conference_Location
    Miedzyzdroje
  • Print_ISBN
    978-1-4799-5082-9
  • Type

    conf

  • DOI
    10.1109/MMAR.2014.6957337
  • Filename
    6957337