Title :
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
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;
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
DOI :
10.1109/TENCON.1993.320591
