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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Bibliographic Details
Published in:	Electric power systems research Vol. 164; pp. 243 - 252
Main Authors:	Mahdi, Mohammed, Genc, V.M. Istemihan
Format:	Journal Article
Language:	English
Published:	Amsterdam Elsevier B.V 01.11.2018 Elsevier Science Ltd
Subjects:	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
Online Access:	Get full text
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