Neural network approximation: application to peak switching overvoltage determination in power systems

Author

Aourid, Mohamed ; DO, Xuan-Dai

Author_Institution

Dept. d´´Inf. et de Recherche Oper., Montreal Univ., Que., Canada

Volume

1

fYear

1995

fDate

Nov/Dec 1995

Firstpage

200

Abstract

Based on approximation theory for multivariable functions, especially by neural network, determination of peak switching overvoltage by power systems has been described. A one hidden layer network trained by the backpropagation has been used to determine the number of hidden units, some heuristics are employed. The effectiveness and the accuracy of our approach are shown by comparing our results with that obtained by using the Electromagnetic Transient Program (EMTP)

Keywords

backpropagation; function approximation; neural nets; overvoltage; power system analysis computing; power system transients; transient analysis; HV transmission lines; backpropagation; heuristics; hidden units; multivariable function approximation; neural network; peak switching overvoltage; power systems; Approximation methods; Artificial neural networks; Backpropagation; EMTP; Intelligent networks; Neural networks; Power system dynamics; Power system faults; Power system interconnection; Power system modeling; Power system security; Power system transients; Voltage control;

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.1995.488093

Filename

488093