A pattern recognition approach for data estimation and debugging in power systems

Author

Alves da Silva, Alexandre P. ; Quintana, V.H. ; Pang, G.K.H.

Author_Institution

Dept. of Electr. Eng., Catholic Univ. of Rio de Janeiro, Brazil

Volume

18

Issue

1

fYear

1993

Firstpage

7

Lastpage

15

Abstract

The authors extend their previous work (1990, 1991) on solving data acquisition and processing problems in power systems. The proposed methodology applies pattern analysis techniques to solve the network configuration, observability analysis and bad-data processing problems. Further associative memory models are investigated for the solution of the observability analysis and bad-data processing tasks. Special emphasis has been put on pattern analysis tools suitable for massively parallel implementations, such as artificial neural network models. Test results have been obtained for the IEEE 24- and 118-bus test systems.

Keywords

content-addressable storage; neural nets; observability; pattern recognition; power system analysis computing; state estimation; IEEE 118-bus test systems; IEEE 24-bus test systems; artificial neural network models; associative memory models; bad-data processing tasks; data estimation; debugging; observability analysis; pattern recognition; power systems; state estimation; Associative memory; Encoding; Estimation; Noise; Observability; Training; Voltage measurement;

fLanguage

English

Journal_Title

Electrical and Computer Engineering, Canadian Journal of

Publisher

ieee

ISSN

0840-8688

Type

jour

DOI

10.1109/CJECE.1993.6591632

Filename

6591632