Proceedings of the 2007 International Conference on Intelligent Systems and Knowledge Engineering (ISKE 2007)

Transient Stability Assessment of Power System Based on Support Vector Machine

Authors
Shengyong Ye1, Yongkang Zheng, Qingquan Qian
1School of Electrical Engineering, Southwest Jiaotong Univers
Corresponding Author
Shengyong Ye
Available Online October 2007.
DOI
https://doi.org/10.2991/iske.2007.143How to use a DOI?
Keywords
Transient stability assessment, Support vector machines, Single machine attributes.
Abstract

Machine learning methods are promising tools to transient stability assessment (TSA) of power system. Support vector machine (SVM) is used to assess the transient stability of power system after faults occur on transmission lines. Single machine attributes were studied as inputs of the SVM classifier. Experimental results in IEEE 50-generator test system showed that, attributes of single machine with small inertia coefficient are effective in TSA, and the SVM classifier with RBF kernel using these single machine attributes achieved satisfying classification accuracy.

Copyright
© 2007, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2007 International Conference on Intelligent Systems and Knowledge Engineering (ISKE 2007)
Series
Advances in Intelligent Systems Research
Publication Date
October 2007
ISBN
978-90-78677-04-8
ISSN
1951-6851
DOI
https://doi.org/10.2991/iske.2007.143How to use a DOI?
Copyright
© 2007, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Shengyong Ye
AU  - Yongkang Zheng
AU  - Qingquan Qian
PY  - 2007/10
DA  - 2007/10
TI  - Transient Stability Assessment of Power System Based on Support Vector Machine
BT  - Proceedings of the 2007 International Conference on Intelligent Systems and Knowledge Engineering (ISKE 2007)
PB  - Atlantis Press
SP  - 837
EP  - 841
SN  - 1951-6851
UR  - https://doi.org/10.2991/iske.2007.143
DO  - https://doi.org/10.2991/iske.2007.143
ID  - Ye2007/10
ER  -