Design of an artificial neural network for fast line flow contingency ranking

A three-layer perceptron artificial neural network with back propagation learning technique is designed for line flow contingency ranking. Two new indices - a severity index and a margin index for line flow - are defined. A regression-based correlation technique is used to select training parameters for the neural network. The proposed method has been tested on the IEEE 118-bus test system. Results show that the contingency rankings by the proposed method are comparable to results obtained by the classical performance index method. An advantage of the proposed method is its applicability in the control centre environment. Copyright (C) 1996 Published by Elsevier Science Ltd.