Estimating dynamic model parameters for adaptive protection and control in power system

Ariff, M. A. M. and Pal, B. C. and Singh, Abhinav Kumar (2014) Estimating dynamic model parameters for adaptive protection and control in power system. IEEE Transactions on Power Systems, 30 (2). pp. 829-839. ISSN 0885-8950

Full content URL: http://dx.doi.org/10.1109/TPWRS.2014.2331317

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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:Measurement-based, parameters estimation, phasor measurement units, power system dynamic model, synchrophasors, unscented Kalman filter, dynamic model parameter estimation, power system adaptive protection, power system control, power system transient stability, inertia constant, direct axis transient reactance, real time, UKF, phasor measurement unit, PMU, power swing relays, 16-machine 68-bus system, Power system dynamics, Noise, Vectors, Mathematical model, Generators, Parameter estimation
Subjects:H Engineering > H660 Control Systems
H Engineering > H631 Electrical Power Generation
H Engineering > H630 Electrical Power
H Engineering > H310 Dynamics
Divisions:College of Science > School of Engineering
ID Code:28762
Deposited On:27 Sep 2017 13:52

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