Energy function based neural networks UPFC for transient stability enhancement of network-preserving power systems

Chia Chi Chu; Hung Chi Tsai

doi:10.1109/ISCAS.2010.5537013

Energy function based neural networks UPFC for transient stability enhancement of network-preserving power systems

Chia Chi Chu^*
, Hung Chi Tsai

^*Corresponding author for this work

National Tsing Hua University
Chang Gung University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

3 Scopus citations

Abstract

An energy function based unified power flow controller (UPFC) is developed for improving transient stability of network-preserving power systems. In order to consider model uncertainties, we also propose a forward neural networks controller to deal with such model uncertainties. This controller can be treated as neural network approximations of energy function control actions and provides online learning ability. Simulations on two power systems demonstrate that the proposed control strategy is very effective for suppressing power swing even under severe system conditions.

Original language	English
Title of host publication	ISCAS 2010 - 2010 IEEE International Symposium on Circuits and Systems
Subtitle of host publication	Nano-Bio Circuit Fabrics and Systems
Pages	2766-2769
Number of pages	4
DOIs	https://doi.org/10.1109/ISCAS.2010.5537013
State	Published - 2010
Externally published	Yes
Event	2010 IEEE International Symposium on Circuits and Systems: Nano-Bio Circuit Fabrics and Systems, ISCAS 2010 - Paris, France Duration: 30 05 2010 → 02 06 2010

Publication series

Name	ISCAS 2010 - 2010 IEEE International Symposium on Circuits and Systems: Nano-Bio Circuit Fabrics and Systems

Conference

Conference	2010 IEEE International Symposium on Circuits and Systems: Nano-Bio Circuit Fabrics and Systems, ISCAS 2010
Country/Territory	France
City	Paris
Period	30/05/10 → 02/06/10

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10.1109/ISCAS.2010.5537013

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Chu, C. C., & Tsai, H. C. (2010). Energy function based neural networks UPFC for transient stability enhancement of network-preserving power systems. In ISCAS 2010 - 2010 IEEE International Symposium on Circuits and Systems: Nano-Bio Circuit Fabrics and Systems (pp. 2766-2769). Article 5537013 (ISCAS 2010 - 2010 IEEE International Symposium on Circuits and Systems: Nano-Bio Circuit Fabrics and Systems). https://doi.org/10.1109/ISCAS.2010.5537013

Chu, Chia Chi ; Tsai, Hung Chi. / Energy function based neural networks UPFC for transient stability enhancement of network-preserving power systems. ISCAS 2010 - 2010 IEEE International Symposium on Circuits and Systems: Nano-Bio Circuit Fabrics and Systems. 2010. pp. 2766-2769 (ISCAS 2010 - 2010 IEEE International Symposium on Circuits and Systems: Nano-Bio Circuit Fabrics and Systems).

@inproceedings{1b1a657d6e2d492cb27f952957a828af,

title = "Energy function based neural networks UPFC for transient stability enhancement of network-preserving power systems",

abstract = "An energy function based unified power flow controller (UPFC) is developed for improving transient stability of network-preserving power systems. In order to consider model uncertainties, we also propose a forward neural networks controller to deal with such model uncertainties. This controller can be treated as neural network approximations of energy function control actions and provides online learning ability. Simulations on two power systems demonstrate that the proposed control strategy is very effective for suppressing power swing even under severe system conditions.",

author = "Chu, \{Chia Chi\} and Tsai, \{Hung Chi\}",

year = "2010",

doi = "10.1109/ISCAS.2010.5537013",

language = "英语",

isbn = "9781424453085",

series = "ISCAS 2010 - 2010 IEEE International Symposium on Circuits and Systems: Nano-Bio Circuit Fabrics and Systems",

pages = "2766--2769",

booktitle = "ISCAS 2010 - 2010 IEEE International Symposium on Circuits and Systems",

note = "2010 IEEE International Symposium on Circuits and Systems: Nano-Bio Circuit Fabrics and Systems, ISCAS 2010 ; Conference date: 30-05-2010 Through 02-06-2010",

}

Chu, CC & Tsai, HC 2010, Energy function based neural networks UPFC for transient stability enhancement of network-preserving power systems. in ISCAS 2010 - 2010 IEEE International Symposium on Circuits and Systems: Nano-Bio Circuit Fabrics and Systems., 5537013, ISCAS 2010 - 2010 IEEE International Symposium on Circuits and Systems: Nano-Bio Circuit Fabrics and Systems, pp. 2766-2769, 2010 IEEE International Symposium on Circuits and Systems: Nano-Bio Circuit Fabrics and Systems, ISCAS 2010, Paris, France, 30/05/10. https://doi.org/10.1109/ISCAS.2010.5537013

Energy function based neural networks UPFC for transient stability enhancement of network-preserving power systems. / Chu, Chia Chi; Tsai, Hung Chi.
ISCAS 2010 - 2010 IEEE International Symposium on Circuits and Systems: Nano-Bio Circuit Fabrics and Systems. 2010. p. 2766-2769 5537013 (ISCAS 2010 - 2010 IEEE International Symposium on Circuits and Systems: Nano-Bio Circuit Fabrics and Systems).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Energy function based neural networks UPFC for transient stability enhancement of network-preserving power systems

AU - Chu, Chia Chi

AU - Tsai, Hung Chi

PY - 2010

Y1 - 2010

N2 - An energy function based unified power flow controller (UPFC) is developed for improving transient stability of network-preserving power systems. In order to consider model uncertainties, we also propose a forward neural networks controller to deal with such model uncertainties. This controller can be treated as neural network approximations of energy function control actions and provides online learning ability. Simulations on two power systems demonstrate that the proposed control strategy is very effective for suppressing power swing even under severe system conditions.

AB - An energy function based unified power flow controller (UPFC) is developed for improving transient stability of network-preserving power systems. In order to consider model uncertainties, we also propose a forward neural networks controller to deal with such model uncertainties. This controller can be treated as neural network approximations of energy function control actions and provides online learning ability. Simulations on two power systems demonstrate that the proposed control strategy is very effective for suppressing power swing even under severe system conditions.

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DO - 10.1109/ISCAS.2010.5537013

M3 - 会议稿件

AN - SCOPUS:77955986433

SN - 9781424453085

T3 - ISCAS 2010 - 2010 IEEE International Symposium on Circuits and Systems: Nano-Bio Circuit Fabrics and Systems

SP - 2766

EP - 2769

BT - ISCAS 2010 - 2010 IEEE International Symposium on Circuits and Systems

T2 - 2010 IEEE International Symposium on Circuits and Systems: Nano-Bio Circuit Fabrics and Systems, ISCAS 2010

Y2 - 30 May 2010 through 2 June 2010

ER -

Chu CC, Tsai HC. Energy function based neural networks UPFC for transient stability enhancement of network-preserving power systems. In ISCAS 2010 - 2010 IEEE International Symposium on Circuits and Systems: Nano-Bio Circuit Fabrics and Systems. 2010. p. 2766-2769. 5537013. (ISCAS 2010 - 2010 IEEE International Symposium on Circuits and Systems: Nano-Bio Circuit Fabrics and Systems). doi: 10.1109/ISCAS.2010.5537013

Energy function based neural networks UPFC for transient stability enhancement of network-preserving power systems

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