• DocumentCode
    648027
  • Title

    Improving performance of dynamic state estimators under unknown load changes

  • Author

    Rouhani, A. ; Abur, Ali

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Northeastern Univ., Boston, MA, USA
  • fYear
    2013
  • fDate
    21-25 July 2013
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    This paper investigates the use of dynamic state estimation for monitoring the transmission grid not only during pseudo steady-state but also during and following disturbances. The paper mainly considers line switching events but the developed estimator can be used under any other type of system disturbance. Unlike previous studies reported in the literature, this work takes into account changes in bus loads which are assumed to be monitored at longer intervals. Assumed variance of the system state is strategically varied to minimize the impact of this approximation on the dynamic state estimation. The well-known and documented Unscented Kalman Filter (UKF) is chosen in formulating the dynamic state estimator, due to its advantages over the commonly used Extended Kalman Filter (EKF). Simulation results will be shown to illustrate the proposed approach to handle slow load changes as well as dynamic estimation of state trajectory during line switching transients.
  • Keywords
    Kalman filters; power system measurement; power system state estimation; power system transients; power transmission faults; EKF; UKF; bus loads; dynamic state estimators; extended Kalman filter; line switching events; line switching transients; power system disturbance; transmission grid; unscented Kalman filter; Generators; Kalman filters; Mathematical model; Power system dynamics; Rotors; State estimation; Synchronization; Dynamic Loads; Dynamic State Estimation; Extended Kalman Filter (EKF); Power Systems Dynamics; Unscented Kalman Filter (UKF);
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Power and Energy Society General Meeting (PES), 2013 IEEE
  • Conference_Location
    Vancouver, BC
  • ISSN
    1944-9925
  • Type

    conf

  • DOI
    10.1109/PESMG.2013.6672584
  • Filename
    6672584