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conference paper

Neural network applications in power systems

Germond, A. J.  
•
Niebur, D.
1993
PSCC. Eleventh Power Systems Computation Conference. Tutorial Session Proceedings

The first part of the presentation is a brief survey of the neural network models and their use in power systems, based on an analysis of more than 200 publications. The second part discusses the applications in static security assessment, with supervised and unsupervised neural network models. An example of static security assessment with the Kohonen classifier is developed: the Kohonen network is trained with vectors representing simulated states of the power system, with or without contingencies. The Kohonen map is used to assess unknown power system states in real time. The two approaches, supervised and unsupervised, are compared and finally, the perspective of industrial implementation is evaluated

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Type
conference paper
Author(s)
Germond, A. J.  
Niebur, D.
Date Issued

1993

Published in
PSCC. Eleventh Power Systems Computation Conference. Tutorial Session Proceedings
Start page

61

End page

70

Subjects

power system analysis computing

•

power system security

•

self-organising feature maps

•

unsupervised learning

•

neural network applications

•

power systems

•

static security assessment

•

unsupervised neural network models

•

supervised neural network models

•

Kohonen classifier

•

Kohonen network training

•

Kohonen map

•

unknown power system states

•

real time

Editorial or Peer reviewed

REVIEWED

Written at

EPFL

EPFL units
LRE  
SCI-STI-FR  
Available on Infoscience
April 4, 2007
Use this identifier to reference this record
https://infoscience.epfl.ch/handle/20.500.14299/4382
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