An on-line distributed intelligent fault section estimation system for large-scale power networks

In this paper, a novel distributed intelligent system is suggested for on-line fault section estimation (FSE) of large-scale power networks. As the first step, a multi-way graph partitioning method based on weighted minimum degree reordering is proposed for effectively partitioning the original large-scale power network into desired number of connected sub-networks with quasi-balanced FSE burdens and minimum frontier elements. After partitioning, a distributed intelligent system based on Radial Basis Function Neural Network (RBF NN) and companion fuzzy system is suggested for FSE. The relevant theoretical analysis and procedure are presented in the paper. The proposed distributed intelligent FSE method has been implemented with sparse storage technique and tested on the IEEE 14, 30 and 118-bus systems, respectively. Computer simulation results show that the proposed FSE method works successfully for large-scale power networks. © 2002 Elsevier Science B.V. All rights reserved.link_to_subscribed_fulltex