Estimation of voltage stability index for power system employing artificial neural network technique and TCSC placement

This paper proposes a scheme for online voltage stability monitoring for various load conditions using feed forward back propagation network (FFBPN). A single FFBPN with minimal number of neurons is used to estimate the line voltage stability index for various load conditions. A sequential learning...

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Bibliographic Details
Published in:Neurocomputing (Amsterdam) 2010-10, Vol.73 (16), p.3005-3011
Main Authors: Jayasankar, V., Kamaraj, N., Vanaja, N.
Format: Article
Language:English
Subjects:
Estimates
Feed forward back propagation network (FFBPN)
Line stability index
Mathematical analysis
Networks
Optimization
Placement
Position (location)
Stability
Thyristor controlled series capacitor (TCSC)
Voltage stability
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Summary:This paper proposes a scheme for online voltage stability monitoring for various load conditions using feed forward back propagation network (FFBPN). A single FFBPN with minimal number of neurons is used to estimate the line voltage stability index for various load conditions. A sequential learning strategy is used to design the FFBPN and the weights in the output layer are determined by using linear optimization. The proposed network is applied on the IEEE 14-bus and the IEEE 30-bus power system and line stability indices are calculated for different loading conditions. Based on the calculated indices, the ranking of weakest lines is done. The optimal location for placement of Thyristor controlled series capacitor (TCSC) has been identified among the weakest lines for improving the voltage stability in the power system. The proposed network can be adapted with changing operating scenario of the power system.
ISSN:0925-2312
1872-8286
DOI:10.1016/j.neucom.2010.07.006