Title :
Estimating Dynamic Model Parameters for Adaptive Protection and Control in Power System
Author :
Ariff, M.A.M. ; Pal, B.C. ; Singh, A.K.
Author_Institution :
Dept. of Electr. & Electron. Eng., Imperial Coll. London, London, UK
Abstract :
This paper presents a new approach in estimating important parameters of power system transient stability model such as inertia constant H and direct axis transient reactance xd´ in real time. It uses a variation of unscented Kalman filter (UKF) on the phasor measurement unit (PMU) data. The accurate estimation of these parameters is very important for assessing the stability and tuning the adaptive protection system on power swing relays. The effectiveness of the method is demonstrated in a simulated data from 16-machine 68-bus system model. The paper also presents the performance comparison between the UKF and EKF method in estimating the parameters. The robustness of method is further validated in the presence of noise that is likely to be in the PMU data in reality.
Keywords :
Kalman filters; nonlinear filters; parameter estimation; phasor measurement; power filters; power system protection; power system transient stability; 16-machine 68-bus system; PMU; UKF; direct axis transient reactance; dynamic model parameter estimation; inertia constant; phasor measurement unit; power swing relays; power system adaptive protection; power system control; power system transient stability; real time; unscented Kalman filter; Generators; Mathematical model; Noise; Parameter estimation; Phasor measurement units; Power system dynamics; Vectors; Measurement-based; parameters estimation; phasor measurement units; power system dynamic model; synchrophasors; unscented Kalman filter;
Journal_Title :
Power Systems, IEEE Transactions on
DOI :
10.1109/TPWRS.2014.2331317