LIU ZHIYUAN, ZHANG SHENXI, WEI PENG, et al. Study on Fault Warning of AC Filter at Converter Station Based on RBF Neural Network. [J]. Power capacitor & reactive power compensation, 2018, 39(4): 12-17.
LIU ZHIYUAN, ZHANG SHENXI, WEI PENG, et al. Study on Fault Warning of AC Filter at Converter Station Based on RBF Neural Network. [J]. Power capacitor & reactive power compensation, 2018, 39(4): 12-17. DOI: 10.14044/j.1674-1757.pcrpc.2018.04.003.
Study on Fault Warning of AC Filter at Converter Station Based on RBF Neural Network
AC filter in converter station is an important part of HVDC transmission system and the occurrence of tripping will affect directly the transmission power of the DC transmission system. In this paper
a kind of healthy status of AC filter which is on-line identified by the opening and closing current of AC filter circuit breaker is proposed. Firstly
both time and frequency domain feature of the opening and closing current of AC filter breaker is defined. On this basis
the fault warning of AC filter is achieved by the artificial intelligence method based on radial neural network. It is shown by the actual result of certain converter station that the method has high fault warning accuracy
can give warning before expansion or negative influence due to abnormality of the AC filter
and remind related people to check and deal with the defects on time so to reduce the occurrence of abnormal tripping of the AC filter.