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
Link To Document :
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