Estimation of transient stability limits using artificial neural network

Author

Yao Liangzhong ; Ni Yixin ; Zhang Buoming

Author_Institution

Dept. of Electr. Eng., Tsinghua Univ., Beijing, China

Volume

5

fYear

1993

fDate

19-21 Oct. 1993

Firstpage

87

Abstract

In this paper, the nonlinear mapping relation between the transient energy margin and the generator power at different fault clearing time was established by using the multi-layer feedforward neural network of the perceptron type, Lyapunov´s direct method based on the system dynamic equivalents was used as a fast method to obtain the training set of the artificial neural network (ANN), the transient stability power limits of the generator at different fault clearing time were estimated very quickly by ANN. The proposed approach has been tested on a practical 59-generator power system, and the results were found to be quite accurate.<>

Keywords

Lyapunov methods; backpropagation; feedforward neural nets; power system analysis computing; power system stability; power system transients; Lyapunov´s direct method; artificial neural network; fault clearing time; generator power; multi-layer feedforward neural network; nonlinear mapping relation; perceptron; power system; training set; transient energy margin; transient stability limits; Artificial neural networks; Feedforward neural networks; Multi-layer neural network; Multilayer perceptrons; Neural networks; Nonlinear dynamical systems; Power generation; Power system dynamics; Power system stability; Power system transients;

fLanguage

English

Publisher

ieee

Conference_Titel

TENCON '93. Proceedings. Computer, Communication, Control and Power Engineering.1993 IEEE Region 10 Conference on

Conference_Location

Beijing, China

Print_ISBN

0-7803-1233-3

Type

conf

DOI

10.1109/TENCON.1993.320591

Filename

320591