Topological observability: Artificial neural network application based solution for a practical power system

Author

Jain, Amit ; Balasubramanian, R. ; Tripathy, S.C.

Author_Institution

Int. Inst. of Inf. Technol., Hyderabad, India

fYear

2008

fDate

28-30 Sept. 2008

Firstpage

1

Lastpage

6

Abstract

An artificial neural network application based method for solving the topological observability problem of power systems is presented in this paper. Back-propagation and quickprop algorithms have been used for training the artificial neural networks used for present solution technique and the method has been successfully implemented on the standard 5-bus power system and on a practical 87-bus power system and the results are presented.

Keywords

artificial intelligence; backpropagation; neural nets; power engineering computing; power system state estimation; 87-bus power system; artificial neural network training; backpropagation algorithm; power system state estimation; quickprop algorithm; standard 5-bus power system; topological observability problem; Artificial neural networks; Control systems; Monitoring; Observability; Power system control; Power system modeling; Power system security; Power systems; Real time systems; State estimation; Artificial neural network; power systemsstate estimation; topological observability;

fLanguage

English

Publisher

ieee

Conference_Titel

Power Symposium, 2008. NAPS '08. 40th North American

Conference_Location

Calgary, AB

Print_ISBN

978-1-4244-4283-6

Type

conf

DOI

10.1109/NAPS.2008.5307305

Filename

5307305