Title :
On-line identification of coherent generators using multilayer feedforward neural networks
Author_Institution :
Dept. of Electr. Eng., South China Univ. of Technol., Guangzhou, China
Abstract :
This paper describes a new method for online identification of coherent generators based on multilayer feedforward neural networks. The principle of the approach,the structure of neural networks and the new learning algorithm are interpreted. Results are described for a 6-machine system and the method is shown to be good at accuracy and speed for power system dynamic equivalents
Keywords :
electric generators; feedforward neural nets; identification; multilayer perceptrons; coherent generators; learning algorithm; multilayer feedforward neural networks; online identification; Aggregates; Fault diagnosis; Feedforward neural networks; Multi-layer neural network; Neural networks; Neurons; Power system dynamics; Power system modeling; Power system stability; Power system transients;
Conference_Titel :
Industrial Technology, 1994., Proceedings of the IEEE International Conference on
Conference_Location :
Guangzhou
Print_ISBN :
0-7803-1978-8
DOI :
10.1109/ICIT.1994.467028
