Voltage stability estimation and prediction using neural network

C. A. Belhadj; H. Al-Duwaish; M. H. Shwehdi; A. S. Farag

doi:10.1109/ICPST.1998.729330

Voltage stability estimation and prediction using neural network

C. A. Belhadj
, H. Al-Duwaish
, M. H. Shwehdi
, A. S. Farag

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

5 Scopus citations

Abstract

This paper proposes a neural network-based method for on-line voltage stability estimation, prediction and monitoring at each power system load bus. The training of the radial basis function neural network (RBFNN) was accomplished by using load flow voltage magnitude and phase as input information, and fast indicators of voltage stability information covering the whole power system and evaluated at each individual bus as output layer information. The generalization capability of the designed networks under a large number of random operation conditions and for several power systems has been tested. Fast performance, accurate evaluation and good prediction for the voltage stability margin have been obtained. Results of tests conducted on standard IEEE 14-bus test system are presented and discussed.

Original language	English
Title of host publication	POWERCON 1998 - 1998 International Conference on Power System Technology, Proceedings
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	1464-1467
Number of pages	4
ISBN (Electronic)	0780347544, 9780780347540
DOIs	https://doi.org/10.1109/ICPST.1998.729330
State	Published - 1998

Publication series

Name	POWERCON 1998 - 1998 International Conference on Power System Technology, Proceedings
Volume	2

Bibliographical note

Publisher Copyright:
© 1998 IEEE.

ASJC Scopus subject areas

Energy Engineering and Power Technology
Control and Systems Engineering
Electrical and Electronic Engineering
Control and Optimization

Access to Document

10.1109/ICPST.1998.729330

Cite this

Belhadj, C. A., Al-Duwaish, H., Shwehdi, M. H., & Farag, A. S. (1998). Voltage stability estimation and prediction using neural network. In POWERCON 1998 - 1998 International Conference on Power System Technology, Proceedings (pp. 1464-1467). (POWERCON 1998 - 1998 International Conference on Power System Technology, Proceedings; Vol. 2). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICPST.1998.729330

Belhadj, C. A. ; Al-Duwaish, H. ; Shwehdi, M. H. et al. / Voltage stability estimation and prediction using neural network. POWERCON 1998 - 1998 International Conference on Power System Technology, Proceedings. Institute of Electrical and Electronics Engineers Inc., 1998. pp. 1464-1467 (POWERCON 1998 - 1998 International Conference on Power System Technology, Proceedings).

@inproceedings{4bd48bcf3d1148e5b3dd018a808453f4,

title = "Voltage stability estimation and prediction using neural network",

abstract = "This paper proposes a neural network-based method for on-line voltage stability estimation, prediction and monitoring at each power system load bus. The training of the radial basis function neural network (RBFNN) was accomplished by using load flow voltage magnitude and phase as input information, and fast indicators of voltage stability information covering the whole power system and evaluated at each individual bus as output layer information. The generalization capability of the designed networks under a large number of random operation conditions and for several power systems has been tested. Fast performance, accurate evaluation and good prediction for the voltage stability margin have been obtained. Results of tests conducted on standard IEEE 14-bus test system are presented and discussed.",

author = "Belhadj, \{C. A.\} and H. Al-Duwaish and Shwehdi, \{M. H.\} and Farag, \{A. S.\}",

note = "Publisher Copyright: {\textcopyright} 1998 IEEE.",

year = "1998",

doi = "10.1109/ICPST.1998.729330",

language = "English",

series = "POWERCON 1998 - 1998 International Conference on Power System Technology, Proceedings",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "1464--1467",

booktitle = "POWERCON 1998 - 1998 International Conference on Power System Technology, Proceedings",

address = "United States",

}

Belhadj, CA, Al-Duwaish, H, Shwehdi, MH & Farag, AS 1998, Voltage stability estimation and prediction using neural network. in POWERCON 1998 - 1998 International Conference on Power System Technology, Proceedings. POWERCON 1998 - 1998 International Conference on Power System Technology, Proceedings, vol. 2, Institute of Electrical and Electronics Engineers Inc., pp. 1464-1467. https://doi.org/10.1109/ICPST.1998.729330

Voltage stability estimation and prediction using neural network. / Belhadj, C. A.; Al-Duwaish, H.; Shwehdi, M. H. et al.
POWERCON 1998 - 1998 International Conference on Power System Technology, Proceedings. Institute of Electrical and Electronics Engineers Inc., 1998. p. 1464-1467 (POWERCON 1998 - 1998 International Conference on Power System Technology, Proceedings; Vol. 2).

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

TY - GEN

T1 - Voltage stability estimation and prediction using neural network

AU - Belhadj, C. A.

AU - Al-Duwaish, H.

AU - Shwehdi, M. H.

AU - Farag, A. S.

PY - 1998

Y1 - 1998

N2 - This paper proposes a neural network-based method for on-line voltage stability estimation, prediction and monitoring at each power system load bus. The training of the radial basis function neural network (RBFNN) was accomplished by using load flow voltage magnitude and phase as input information, and fast indicators of voltage stability information covering the whole power system and evaluated at each individual bus as output layer information. The generalization capability of the designed networks under a large number of random operation conditions and for several power systems has been tested. Fast performance, accurate evaluation and good prediction for the voltage stability margin have been obtained. Results of tests conducted on standard IEEE 14-bus test system are presented and discussed.

AB - This paper proposes a neural network-based method for on-line voltage stability estimation, prediction and monitoring at each power system load bus. The training of the radial basis function neural network (RBFNN) was accomplished by using load flow voltage magnitude and phase as input information, and fast indicators of voltage stability information covering the whole power system and evaluated at each individual bus as output layer information. The generalization capability of the designed networks under a large number of random operation conditions and for several power systems has been tested. Fast performance, accurate evaluation and good prediction for the voltage stability margin have been obtained. Results of tests conducted on standard IEEE 14-bus test system are presented and discussed.

UR - https://www.scopus.com/pages/publications/76549087998

U2 - 10.1109/ICPST.1998.729330

DO - 10.1109/ICPST.1998.729330

M3 - Conference contribution

AN - SCOPUS:76549087998

T3 - POWERCON 1998 - 1998 International Conference on Power System Technology, Proceedings

SP - 1464

EP - 1467

BT - POWERCON 1998 - 1998 International Conference on Power System Technology, Proceedings

PB - Institute of Electrical and Electronics Engineers Inc.

ER -

Belhadj CA, Al-Duwaish H, Shwehdi MH, Farag AS. Voltage stability estimation and prediction using neural network. In POWERCON 1998 - 1998 International Conference on Power System Technology, Proceedings. Institute of Electrical and Electronics Engineers Inc. 1998. p. 1464-1467. (POWERCON 1998 - 1998 International Conference on Power System Technology, Proceedings). doi: 10.1109/ICPST.1998.729330

Voltage stability estimation and prediction using neural network

Abstract

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Bibliographical note

ASJC Scopus subject areas

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