Title :
Intelligent on-line capturing method for optimal time of automatic reclosing transient fault
Author :
Chen, Shaohua ; Liu, Yuxin ; Xu, Zili
Author_Institution :
Fac. of Autom., Guangdong Univ. of Technol., China
Abstract :
Different reclosing times of automatic reclosing affect power system´s transient stability; but the problem of online capturing method for optimal time of automatic reclosing has never been solved. A new intelligent on-line method for capturing the optimal time of transient fault is presented in this paper. Based on the transient system fault information, the eigenvalue was extracted by means of wavelet transform. And in virtue of definite time criterion, the optimal reclosing time could be on-line captured by the trained ANN. Detailed simulation methods and relevant schematic figures are provided. A satisfactory performance has been found in the given simulation model.
Keywords :
artificial intelligence; eigenvalues and eigenfunctions; neural nets; power engineering computing; power system faults; power system transient stability; wavelet transforms; ANN; automatic reclosing; eigenvalue; intelligent online capturing; power system transient stability; reclosing times; transient system fault information; wavelet transform; Artificial neural networks; Data mining; Eigenvalues and eigenfunctions; Neural networks; Power system faults; Power system modeling; Power system simulation; Power system stability; Power system transients; Wavelet transforms;
Conference_Titel :
Intelligent Control and Automation, 2004. WCICA 2004. Fifth World Congress on
Print_ISBN :
0-7803-8273-0
DOI :
10.1109/WCICA.2004.1343687
