Transient stability assessment: an artificial neural network approach

Author

Sing, Lau Buon ; Po, Wong Kit

Author_Institution

Sarawak Electr. Supply Corp., Malaysia

Volume

2

fYear

1995

fDate

Nov/Dec 1995

Firstpage

702

Abstract

A general artificial neural network (ANN) approach for constructing multilayered feedforward networks (MFNs) is developed based on formulated ANN principles and methodologies. The general ANN approach is applied to develop a proposed ANN system for fault type identification, fault location and critical clearing time estimations in the context of power system transient stability assessment. Three schemes are also formulated to validate the general ANN approach and the developed ANN system

Keywords

fault diagnosis; fault location; feedforward neural nets; multilayer perceptrons; power system stability; power system transients; artificial neural network; critical clearing time estimations; fault location; fault type identification; multilayered feedforward networks; power system transient stability assessment; Artificial neural networks; Australia; Fault diagnosis; Fault location; Power system analysis computing; Power system faults; Power system modeling; Power system stability; Power system transients; Supervised learning;

fLanguage

English

Publisher

ieee

Conference_Titel

Neural Networks, 1995. Proceedings., IEEE International Conference on

Conference_Location

Perth, WA

Print_ISBN

0-7803-2768-3

Type

conf

DOI

10.1109/ICNN.1995.487502

Filename

487502