By Topic

Multi neural network based fault area estimation for high speed protective relaying

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

4 Author(s)
T. Dalstein ; Dept. of High Voltage & Power Eng., Tech. Univ. Berlin, Germany ; T. Friedrich ; B. Kulicke ; D. Sobajic

The aim of this paper is to present a new approach to fault area estimation for high-speed relaying using feedforward neural networks. The suggested framework makes use of neurocomputing technology and pattern-recognition concepts. In contrast to conventional algorithms, our neural fault area estimator (NFAE) determines the fault area directly. This approach leads to very short propagation times and reliable classification results. Important attributes of artificial neural networks (ANNs) are their ability to learn nonlinear functions and their large input error tolerance. The obtained results indicate that these characteristics still result in reliable behaviour even if nonideal (real-world) effects pertain. A comparison of classification quality with conventional algorithms by simulating certain faults on a parallel transmission line shows the approaches advanced capability for protective relaying

Published in:

IEEE Transactions on Power Delivery  (Volume:11 ,  Issue: 2 )