Denoising autoencoder based topology identification in distribution systems with missing measurements

In distribution systems, the loss of existing real measurements and the stochastic penetration levels of renewable energy sources (RES) are the major issues while identifying the correct topology. The frequent switching and control actions of RES can lead to many topology changes. The loss of existi...

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Veröffentlicht in:	International journal of electrical power & energy systems Jg. 154; S. 109464
Hauptverfasser:	Raghuvamsi, Y., Teeparthi, Kiran, Kosana, Vishalteja
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier Ltd 01.12.2023
Schlagworte:	Denoising autoencoder Huber-loss function Line current sensors Missing data Temporal convolutional network (TCN) Topology identification Huber-loss function Missing data Denoising autoencoder Line current sensors Temporal convolutional network (TCN) Topology identification
ISSN:	0142-0615
Online-Zugang:	Volltext
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