By Topic

Performance estimation techniques for power system dynamic stability using least squares, Kalman filtering and genetic algorithms

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

1 Author(s)
Feilat, E.A. ; Dept. of Electr. & Comput. Eng., Mississippi State Univ., MS, USA

This paper presents performance comparison of three optimal estimation techniques for on-line assessment of power system dynamic stability of single-machine infinite-bus system. The stability assessment approach is based on estimating the synchronizing and damping torque coefficients of the synchronous machine using three optimum estimation techniques including least squares (LS), Kalman filtering (KF) and genetic algorithms (GA). The coefficients are estimated from time responses of the changes in the rotor angle, rotor speed, and electromagnetic torque. The performances of the above three optimal estimation techniques were examined. Compared with the LS and GA techniques, the paper shows that KF technique offers several advantages. This includes significant reduction in computing time and storage needed for the estimation of the synchronizing and damping torque coefficients besides its robustness in dealing with noisy measurements. Thus, KF approach results in a remarkable reduction in the computational complexity associated with this problem and hence allow for on-line implementation needed for continuous monitoring of the dynamic stability indices. On the other hand, though GA gives accurate results in comparison with LS and KF. However, it was found that the calculation by GA are very time consuming rendering it unsuitable for on-line application

Published in:

Southeastcon 2000. Proceedings of the IEEE

Date of Conference: