The University of Southampton
University of Southampton Institutional Repository

Decentralized nonlinear control for power systems using normal forms and detailed models

Decentralized nonlinear control for power systems using normal forms and detailed models
Decentralized nonlinear control for power systems using normal forms and detailed models

This paper proposes a decentralized method for nonlinear control of oscillatory dynamics in power systems. The method is applicable for ensuring both transient stability and small-signal stability. The method uses an optimal control law, which has been derived in the general framework of nonlinear control using normal forms. The model used to derive the control law is the detailed subtransient model of synchronous machines, as recommended by the IEEE. Minimal approximations have been made in either the derivation or the application of the control law. The developed method also requires the application of the dynamic state estimation technique. As the employed control and estimation schemes only need local measurements, the method remains completely decentralized. The method has been demonstrated as an effective tool to prevent blackouts by simulating a major disturbance in a benchmark power system model and its subsequent control using the proposed method.

Decentralized, dynamic state estimation, feedback linearization, lie derivative, nonlinear control, normal form, optimal control, subtransient model, unscented Kalman filtering
0885-8950
1160-1172
Singh, Abhinav Kumar
6df7029f-21e3-4a06-b5f7-da46f35fc8d3
Pal, Bikash C.
c062978e-53eb-4d5d-ace8-746ccafa5fb0
Singh, Abhinav Kumar
6df7029f-21e3-4a06-b5f7-da46f35fc8d3
Pal, Bikash C.
c062978e-53eb-4d5d-ace8-746ccafa5fb0

Singh, Abhinav Kumar and Pal, Bikash C. (2018) Decentralized nonlinear control for power systems using normal forms and detailed models. IEEE Transactions on Power Systems, 33 (2), 1160-1172. (doi:10.1109/TPWRS.2017.2724022).

Record type: Article

Abstract

This paper proposes a decentralized method for nonlinear control of oscillatory dynamics in power systems. The method is applicable for ensuring both transient stability and small-signal stability. The method uses an optimal control law, which has been derived in the general framework of nonlinear control using normal forms. The model used to derive the control law is the detailed subtransient model of synchronous machines, as recommended by the IEEE. Minimal approximations have been made in either the derivation or the application of the control law. The developed method also requires the application of the dynamic state estimation technique. As the employed control and estimation schemes only need local measurements, the method remains completely decentralized. The method has been demonstrated as an effective tool to prevent blackouts by simulating a major disturbance in a benchmark power system model and its subsequent control using the proposed method.

Text
08000585 - Version of Record
Available under License Creative Commons Attribution.
Download (1MB)

More information

Accepted/In Press date: 2 July 2017
e-pub ahead of print date: 3 August 2017
Published date: 1 March 2018
Keywords: Decentralized, dynamic state estimation, feedback linearization, lie derivative, nonlinear control, normal form, optimal control, subtransient model, unscented Kalman filtering

Identifiers

Local EPrints ID: 430936
URI: http://eprints.soton.ac.uk/id/eprint/430936
ISSN: 0885-8950
PURE UUID: 08057cc5-5f35-4d50-b18d-ee00775176fd
ORCID for Abhinav Kumar Singh: ORCID iD orcid.org/0000-0003-3376-6435

Catalogue record

Date deposited: 17 May 2019 16:30
Last modified: 18 Mar 2024 03:52

Export record

Altmetrics

Contributors

Author: Abhinav Kumar Singh ORCID iD
Author: Bikash C. Pal

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×