A support vector machine (SVM) based voltage stability classifier

Rodel D. Dosano; Hwachang Song; Byongjun Lee

A support vector machine (SVM) based voltage stability classifier

Rodel D. Dosano, Hwachang Song, Byongjun Lee

School of Electrical Engineering

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

Abstract

This paper proposes a support vector machine (SVM) based power system voltage stability classifier using local measurements of voltage and active power of load. The excellent performance of the SVM in the classification related to time-series prediction matches the real-time data of local measurement for system responses by shortterm and long-term dynamics. The methodology for automatic monitoring of the system is initiated locally, which aims to leave sufficient time to perform immediate corrective actions to stop system degradation by the effect of major disturbances. This paper explains the procedure for fast classification of long-term voltage stability using the SVM algorithm.

Original language	English
Title of host publication	Proceedings of the 7th IASTED International Conference on Power and Energy Systems
Pages	265-271
Number of pages	7
Publication status	Published - 2007
Event	7th IASTED International Conference on Power and Energy Systems - Palma de Mallorca, Spain Duration: 2007 Aug 29 → 2007 Aug 31

Publication series

Name	Proceedings of the IASTED International Conference on Energy and Power Systems

Other

Other	7th IASTED International Conference on Power and Energy Systems
Country/Territory	Spain
City	Palma de Mallorca
Period	07/8/29 → 07/8/31

Keywords

Classification
Local phasor measurement
Power system voltage stability
Real-time monitoring
Support vector machine

ASJC Scopus subject areas

Energy Engineering and Power Technology
Electrical and Electronic Engineering
Condensed Matter Physics

Cite this

A support vector machine (SVM) based voltage stability classifier. / Dosano, Rodel D.; Song, Hwachang; Lee, Byongjun.
Proceedings of the 7th IASTED International Conference on Power and Energy Systems. 2007. p. 265-271 (Proceedings of the IASTED International Conference on Energy and Power Systems).

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

Dosano, RD, Song, H & Lee, B 2007, A support vector machine (SVM) based voltage stability classifier. in Proceedings of the 7th IASTED International Conference on Power and Energy Systems. Proceedings of the IASTED International Conference on Energy and Power Systems, pp. 265-271, 7th IASTED International Conference on Power and Energy Systems, Palma de Mallorca, Spain, 07/8/29.

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abstract = "This paper proposes a support vector machine (SVM) based power system voltage stability classifier using local measurements of voltage and active power of load. The excellent performance of the SVM in the classification related to time-series prediction matches the real-time data of local measurement for system responses by shortterm and long-term dynamics. The methodology for automatic monitoring of the system is initiated locally, which aims to leave sufficient time to perform immediate corrective actions to stop system degradation by the effect of major disturbances. This paper explains the procedure for fast classification of long-term voltage stability using the SVM algorithm.",

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AB - This paper proposes a support vector machine (SVM) based power system voltage stability classifier using local measurements of voltage and active power of load. The excellent performance of the SVM in the classification related to time-series prediction matches the real-time data of local measurement for system responses by shortterm and long-term dynamics. The methodology for automatic monitoring of the system is initiated locally, which aims to leave sufficient time to perform immediate corrective actions to stop system degradation by the effect of major disturbances. This paper explains the procedure for fast classification of long-term voltage stability using the SVM algorithm.

KW - Classification

KW - Local phasor measurement

KW - Power system voltage stability

KW - Real-time monitoring

KW - Support vector machine

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M3 - Conference contribution

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SN - 9780889866898

T3 - Proceedings of the IASTED International Conference on Energy and Power Systems

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BT - Proceedings of the 7th IASTED International Conference on Power and Energy Systems

T2 - 7th IASTED International Conference on Power and Energy Systems

Y2 - 29 August 2007 through 31 August 2007

ER -

A support vector machine (SVM) based voltage stability classifier

Abstract

Publication series

Other

Keywords

ASJC Scopus subject areas

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