Assessment of voltage security in a multi-bus power system using artificial neural network and voltage stability indicators
Joint Authors
Kabir
Chakraborty
Chakrabarti, Shami
Abhijit, Abhinandan De
Source
Issue
Vol. 6, Issue 4 (31 Dec. 2010), pp.517-529, 13 p.
Publisher
Publication Date
2010-12-31
Country of Publication
Algeria
No. of Pages
13
Main Subjects
Abstract EN
In this paper, a new methodology has been proposed for monitoring and assessment of statu voltage stability margins using a unique technique combining artificial neural network (ANN^ and linear voltage stability indicator (LVSi).
A technique for equivalencing of a multi-bus powel system to a two bus radial system has been developed and LVSI has been used as the underlying tool for evaluation of voltage stability margins in a standard SO bus power network.
ANN basei pattern recognition engine has been combined with LVSI to predict voltage security of tht system under various operating conditions.
The proposed technique gives excellent prediction a voltage security under all operating conditions including multiple contingencies.
American Psychological Association (APA)
Kabir& Chakraborty& Abhijit, Abhinandan De& Chakrabarti, Shami. 2010. Assessment of voltage security in a multi-bus power system using artificial neural network and voltage stability indicators. Journal of Electrical Systems،Vol. 6, no. 4, pp.517-529.
https://search.emarefa.net/detail/BIM-252340
Modern Language Association (MLA)
Kabir…[et al.]. Assessment of voltage security in a multi-bus power system using artificial neural network and voltage stability indicators. Journal of Electrical Systems Vol. 6, no. 4 (Dec. 2010), pp.517-529.
https://search.emarefa.net/detail/BIM-252340
American Medical Association (AMA)
Kabir& Chakraborty& Abhijit, Abhinandan De& Chakrabarti, Shami. Assessment of voltage security in a multi-bus power system using artificial neural network and voltage stability indicators. Journal of Electrical Systems. 2010. Vol. 6, no. 4, pp.517-529.
https://search.emarefa.net/detail/BIM-252340
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references : p. 528-529
Record ID
BIM-252340