• DocumentCode
    1755796
  • Title

    Optimal PMU Placement for Power System Dynamic State Estimation by Using Empirical Observability Gramian

  • Author

    Junjian Qi ; Kai Sun ; Wei Kang

  • Author_Institution
    Dept. of Electr. Eng. & Comput. Sci., Univ. of Tennessee, Knoxville, TN, USA
  • Volume
    30
  • Issue
    4
  • fYear
    2015
  • fDate
    42186
  • Firstpage
    2041
  • Lastpage
    2054
  • Abstract
    In this paper, the empirical observability Gramian calculated around the operating region of a power system is used to quantify the degree of observability of the system states under specific phasor measurement unit (PMU) placement. An optimal PMU placement method for power system dynamic state estimation is further formulated as an optimization problem which maximizes the determinant of the empirical observability Gramian and is efficiently solved by the NOMAD solver, which implements the Mesh Adaptive Direct Search algorithm. The implementation, validation, and the robustness to load fluctuations and contingencies of the proposed method are carefully discussed. The proposed method is tested on WSCC 3-machine 9-bus system and NPCC 48-machine 140-bus system by performing dynamic state estimation with square-root unscented Kalman filter. The simulation results show that the determined optimal PMU placements by the proposed method can guarantee good observability of the system states, which further leads to smaller estimation errors and larger number of convergent states for dynamic state estimation compared with random PMU placements. Under optimal PMU placements an obvious observability transition can be observed. The proposed method is also validated to be very robust to both load fluctuations and contingencies.
  • Keywords
    Kalman filters; estimation theory; nonlinear filters; observability; optimisation; phasor measurement; power system state estimation; search problems; NOMAD solver; NPCC 48-machine 140-bus system; WSCC 3-machine 9-bus system; empirical observability Gramian calculation; mesh adaptive direct search algorithm; optimal PMU placement; optimization problem; phasor measurement unit; power system dynamic state estimation; square-root unscented Kalman filter; Generators; Observability; Phasor measurement units; Power system dynamics; Rotors; State estimation; Vectors; Determinant; NOMAD; PMU placement; dynamic state estimation; empirical observability Gramian; mesh adaptive direct search; nonlinear systems; observability; observability transition; optimization; robustness; square-root unscented Kalman filter;
  • fLanguage
    English
  • Journal_Title
    Power Systems, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0885-8950
  • Type

    jour

  • DOI
    10.1109/TPWRS.2014.2356797
  • Filename
    6913022