Post-fault prediction of transient instabilities using stacked sparse autoencoder

•A fast and robust method is proposed for transient stability assessment.•Stacked sparse autoencoder is used as a stability classification algorithm.•The measurements from the fault-on time period are adopted as inputs.•The method is tested on WSCC test system and on the Turkish power system.•The ro...

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Vydané v:	Electric power systems research Ročník 164; s. 243 - 252
Hlavní autori:	Mahdi, Mohammed, Genc, V.M. Istemihan
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Amsterdam Elsevier B.V 01.11.2018 Elsevier Science Ltd
Predmet:	Deep learning Electricity distribution Fault diagnosis Measuring instruments Monitoring systems Multilayer perceptrons Phasor measurement units Power reliability Prediction Predictions Situational awareness Sparse autoencoder Stability Transient stability Wide area measurements Deep learning Phasor measurement units Sparse autoencoder Transient stability Wide area measurements Prediction
ISSN:	0378-7796, 1873-2046
On-line prístup:	Získať plný text
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