By Topic

A novel approach to detection high impedance faults using artificial neural 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
$31 $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

1 Author(s)
Khorashadi-Zadeh, H. ; EE Dept., Univ. of Birjand, Iran

This paper presents a new approach to detection of high impedance faults in distribution systems using artificial neural networks. The proposed neural network was trained by data from simulation of a distribution system under different fault conditions, and tested by data with different conditions. Details of the design procedure and the results of performance studies with the proposed method are given in the paper. Performance studies results show that the proposed algorithm is very good performance in detecting a high impedance fault with nonlinear arcing resistance. It is clearly shown that with this integrated approach, the accuracy in detection fault is significantly improved over other techniques based on a conventional algorithm.

Published in:

Universities Power Engineering Conference, 2004. UPEC 2004. 39th International  (Volume:1 )

Date of Conference:

8-8 Sept. 2004