DocumentCode
2728307
Title
A novel approach for ringdown detection using extended Kalman filter
Author
Yazdanian, Masoud ; Mehrizi-Sani, Ali ; Mojiri, Mohsen
Author_Institution
Sch. of Electr. Eng. & Comput. Sci., Washington State Univ., Pullman, WA, USA
fYear
2013
fDate
10-13 Nov. 2013
Firstpage
3270
Lastpage
3274
Abstract
Estimation of electromechanical modes has attracted attention during past few decades because the estimation of these modes provides vital information about the stability of the power system. In this paper, a new state-space model is developed for online detection of a ringdown signal using extended Kalman filter (EKF). The proposed model not only can estimate constant parameters, but it can also track time-varying parameters. Simulation results demonstrate the desirable performance of the proposed method for ringdown parameter estimation.
Keywords
Kalman filters; power system stability; power system state estimation; EKF; electromechanical oscillations; extended Kalman filter; ringdown parameter estimation; ringdown signal online detection; time-varying parameters; Damping; Estimation; Frequency estimation; Kalman filters; Mathematical model; Noise; State-space methods; Extended Kalman filter; power system modes identification; ringdown detection;
fLanguage
English
Publisher
ieee
Conference_Titel
Industrial Electronics Society, IECON 2013 - 39th Annual Conference of the IEEE
Conference_Location
Vienna
ISSN
1553-572X
Type
conf
DOI
10.1109/IECON.2013.6699652
Filename
6699652
Link To Document