By Topic

High speed transmission system directional protection using an Elman network

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

2 Author(s)
M. Sanaye-Pasand ; Dept. of Electr. & Comput. Eng., Calgary Univ., Alta., Canada ; O. P. Malik

Detection of the direction of a fault on a transmission line is essential to the proper performance of a power system. It would be desirable to develop a high speed and accurate approach to determine the fault direction for different power system conditions. To classify forward and backward faults on a given line, a neural network's abilities in pattern recognition and classification could be considered as a solution. To demonstrate the applicability of this solution, neural network technique is employed and a novel Elman recurrent network is designed and trained. Details of the design procedure and the results of performance studies with the proposed network are given and analysed in the paper. System simulation studies show that the proposed approach is able to detect the direction of a fault on a transmission line rapidly and correctly. It is suitable to realize a very fast transmission line directional comparison protection scheme

Published in:

IEEE Transactions on Power Delivery  (Volume:13 ,  Issue: 4 )