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State estimation of doubly fed induction generator wind turbine in complex power systems

journal contribution
posted on 13.09.2018, 00:00 by S Yu, Kianoush EmamiKianoush Emami, T Fernando, HHC Iu, KP Wong
This paper presents a general framework for the doubly fed induction generator connected to a complex power system in order to facilitate the dynamic estimation of its states using noisy PMU measurements. State estimation considering the whole power system with the occurrence of electric faults is performed using the Unscented Kalman Filter (UKF) with a bad data detection scheme. Such a state estimation scheme for a DFIG is important because not all dynamic states of a DFIG are easily measurable. Furthermore, the proposed state estimation technique is decentralized and the network topology of the entire power system is taken into consideration in the estimation process. In order to enhance the error tolerance and self-correction of the power system, bad data detection technique is implemented. A performance comparison with Extended Kalman Filter (EKF) is also discussed. © 1969-2012 IEEE.

History

Volume

31

Issue

6

Start Page

4935

End Page

4944

Number of Pages

10

eISSN

1558-0679

ISSN

0885-8950

Publisher

IEEE, USA

Peer Reviewed

Yes

Open Access

No

External Author Affiliations

University of Western Australia

Era Eligible

Yes

Journal

IEEE Transactions on Power Systems