Commutation failure detection algorithm based on stationary wavelet and BP neural network
LI Fu-xin
Abstract：In order to solve the commutation failure detection problem in high voltage direct current transmission (HVDC) system, a commutation failure detection algorithm based on stationary wavelet analysis and BP neural network was proposed. The commutation failure signals and wavelet energy with different scales were extracted as the feature vectors through the stationary wavelet. In addition,the feature vectors were inputted into the neural network for training,and a classification model for automatic recognition was obtained. The proposed algorithm was verified with the actually collected 200 data sets. The results indicate that the proposed algorithm can effectively distinguish the commutation failure and normal signals in the HVDC system,and the average detection accuracy can reach above 95%. It is obvious that the proposed algorithm can provide the guarantee for the further precise reactive power compensation in the system.
Keywords：high voltage direct current transmission systemcommutation failurereactive power compensationstationary wavelet analysisBP neural networkwavelet energyautomatic detectiontraining
Publication Date：2018-01-01
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：5( 248-252 )