Application of neural networks to direct stability analysis of power systems

Author

Klapper, D.B. ; Othman, H.A. ; Akimoto, Y. ; Tanaka, H. ; Yoshizawa, J.

Author_Institution

Dept. of Power Syst. Eng., General Electric. Co., Albany, NY, USA

fYear

1993

fDate

1993

Firstpage

382

Lastpage

386

Abstract

The feasibility of designing neural networks capable of computing the critical clearing times of power system faults is explored. Two distinct approaches are investigated, the patter recognition approach and the optimization approach. The theory of direct stability analysis of power systems is utilized is designing he input features of the pattern recognition approach, and the structure of the Hopfield optimization approach.

Keywords

Hopfield neural nets; electrical faults; optimisation; pattern recognition; power system analysis computing; power system stability; Hopfield; critical clearing times; direct stability analysis; faults; neural networks; optimization; patter recognition; power system analysis computing; Computer networks; Hopfield neural networks; Neural networks; Pattern recognition; Power engineering computing; Power system analysis computing; Power system faults; Power system simulation; Power system stability; Stability analysis;

fLanguage

English

Publisher

ieee

Conference_Titel

Neural Networks to Power Systems, 1993. ANNPS '93., Proceedings of the Second International Forum on Applications of

Conference_Location

Yokohama, Japan

Print_ISBN

0-7803-1217-1

Type

conf

DOI

10.1109/ANN.1993.264317

Filename

264317