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Power system dynamic state estimation using particle filter

conference contribution
posted on 03.08.2018, 00:00 by Kianoush EmamiKianoush Emami, T Fernando, B Nener
A particle filter based power system dynamic state estimation scheme is presented in this paper. The proposed method can be considered as an alternative to the other schemes which are mostly based on the Kaiman Filter. The particle filter approach can be used to estimate the states of nonlinear systems which are subjected to both Gaussian and non-Gaussian noise. Furthermore, the presented scheme has a simple algorithm that can be easily implemented numerically. The case study considered in this paper reveals that the method has considerable accuracy and provides smooth dynamic state estimation even when the noise variance differs from a known initial value. © 2014 IEEE.

History

Editor

Fahimi B; Capolino G-A

Parent Title

Proceedings IECON 2014 - 40th Anual Conference of the IEEE Industrial Electronics Conference

Start Page

248

End Page

253

Number of Pages

6

Start Date

29/10/2014

Finish Date

01/11/2014

ISSN

1553-572X

ISBN-13

9781479940325

Location

Dallas, USA

Publisher

IEEE

Place of Publication

Piscataway, NJ

Peer Reviewed

Yes

Open Access

No

External Author Affiliations

University of Western Australia

Era Eligible

Yes

Name of Conference

40th Annual Conference of the IEEE Industrial Electronics Society (IECON 2014)