摘要：This paper presents a comparative study for performing automated power quality diagnosis using rule base classifier (RBC) and support vector regression (SVR) to identify the causes of short duration voltage disturbances such as voltage sag and swell. In the proposed power quality diagnosis method, a time frequency analysis technique called the S-transform was used to analyse and extract features of voltage disturbances recorded from the power quality monitoring system. The RBC and SVR which are intelligent techniques were then used to identify whether the voltage disturbances were caused by permanent, non-permanent transient or incipient faults. Test results proved that the RBC performed better than the SVR in diagnosing the causes of short duration voltage disturbances.
关键词：Power quality diagnosis; support vector regression; s-transform
