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Please use this identifier to cite or link to this item:
http://hdl.handle.net/2080/396
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| DC Field | Value | Language |
|---|
| contributor.author | Dash, P K | - |
| contributor.author | Samantaray, S R | - |
| contributor.author | Panda, G | - |
| date.accessioned | 2007-01-08T10:27:31Z | - |
| date.available | 2007-01-08T10:27:31Z | - |
| date.issued | 2007 | - |
| identifier.citation | IEEE Transactions on Power Delivery, Vol 22, No 1, P 67-73 | en |
| identifier.uri | http://hdl.handle.net/2080/396 | - |
| description | Copyright for this article belongs to IEEE | en |
| description.abstract | Distance protection of flexible ac transmission lines,
including the thyristor-controlled series compensator (TCSC),
static synchronous compensator, and static var compensator has
been a very challenging task. This paper presents a new approach
for the protection of TCSC line using a support vector machine
(SVM). The proposed method uses postfault current samples for
half cycle (ten samples) from the inception of the fault and firing
angle as inputs to the SVM. Three SVMs are trained to provide
fault classification, ground detection, and section identification,
respectively, for the line using TCSC. The SVMs are trained with
polynomial kernel and Gaussian kernel with different parameter
values to get the most optimized classifier. The proposed method
converges very fast with fewer numbers of training samples compared
to neural-network and neuro-fuzzy systems which indicates
fastness and accuracy of the proposed method for protection of
the transmission line with TCSC | en |
| format.extent | 606788 bytes | - |
| format.mimetype | application/pdf | - |
| language.iso | en | - |
| publisher | IEEE | en |
| subject | Distance protection | en |
| subject | flexible ac transmission | en |
| subject | support vector machine | en |
| subject | thyristor-controlled | en |
| title | Fault Classification and Section Identification of an Advanced Series-Compensated Transmission Line Using Support Vector Machine | en |
| type | Article | en |
| Appears in Collections: | Journal Articles
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Files in This Item:
| File |
Description |
Size | Format |
|---|
| paper_samantary.pdf | | 592Kb | Adobe PDF | View/Open |
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