• DocumentCode
    645719
  • Title

    Distributed implementation of an augmented state dynamic estimator

  • Author

    Rouhani, A. ; Abur, Ali

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Northeastern Univ., Boston, MA, USA
  • fYear
    2013
  • fDate
    22-24 Sept. 2013
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    Load models are commonly approximated by fixed impedance type loads when formulating dynamic simulations. This is an acceptable approximation when using dynamic simulation for a specific initial operating condition and the study runs for a brief period typically to check system stability. When implementing an on-line dynamic estimator such assumptions may not be viable due to the load dynamics which are not typically known. Another difficulty is related to the sheer size of the problem when a large scale system is considered with several generators. This paper addresses these problems by extending the state vector to include network variables, thus eliminating the need to model loads and also by implementing a distributed yet synchronized solution algorithm that facilities simultaneous solutions by multiple areas. Previously studied Unscented Kalman Filter (UKF) is used and the proposed method is tested on the New-England 37-bus system.
  • Keywords
    Kalman filters; nonlinear filters; power system state estimation; New-England 37-bus system; UKF; augmented state dynamic estimator; state vector; synchronized solution algorithm; unscented Kalman filter; Generators; Mathematical model; Power system dynamics; Rotors; State estimation; Synchronization; Vectors; Dynamic Loads; Dynamic State Estimation; Kalman filter; Power Systems Dynamics; Unscented Kalman Filter (UKF);
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    North American Power Symposium (NAPS), 2013
  • Conference_Location
    Manhattan, KS
  • Type

    conf

  • DOI
    10.1109/NAPS.2013.6666869
  • Filename
    6666869