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A novel neural network approach to dynamic state estimation of generators subjected to ageing in complex power systems

conference contribution
posted on 19.10.2020, 00:00 by H Ariakia, Kianoush EmamiKianoush Emami, T Fernando
In this paper, a neural network based technique for estimating dynamic states of generators in highly complex power systems is presented. The proposed method is independent to the mathematical model of the generators and uses a nonlinear autoregressive neural network with exogenous inputs to estimate dynamic states of the generators. The proposed technique has been compared to particle filter and unscented Kalman filter based schemes previously reported in the literature. The simulation results show superiority of the proposed technique over the two other schemes when parameters of the generators alter. Parameter alterations in generators are practically occur due to environment impacts, ageing of the equipment and so on. The proposed scheme is capable of keeping its accuracy and precision even in the presence of unobservable variances in generator parameters. © 2019 IEEE.

History

Start Page

1

End Page

1

Number of Pages

7

Start Date

10/12/2019

Finish Date

12/12/2019

ISBN-13

9781728126586

Location

Perth, Australia

Publisher

IEEE

Place of Publication

Online

Peer Reviewed

Yes

Open Access

No

External Author Affiliations

University of Western Australia

Era Eligible

Yes

Name of Conference

9th International Conference on Power and Energy Systems (ICPES 2019 )