Study On Detection And Recognition Of Power Quality Disturance

Electrical energy is the broadest used energy in modern society. Its application level isa main development symbol of a country. With the advancement of science andtechnology and the popularization of power electronic, computer and informationtechnology, higher request is proposed about power quality. More attentions are paid topower quality disturbance by power unit and consumers. Detecting and discerning powerquality is the premise of adopting appropriate measures to improve power quality andreduce the influences brought by disturbances.This paper aims at power quality disturbances, has done researches on power qualitydisturbance detecting and discerning. Some improvements have been achieved.IEC flicker meter has been achieved by coding, it could accurately detect the flickervalue when the frequency of amplitude modulation wave is between0.5Hz to35Hz.This paper proposed a method of windowed interpolation FFT, which could reducethe influence to signal spectrum caused by spectrum leakage, and with the help ofinterpolation, the basic parameters of various harmonics could be correctly measured. Areasonable result has been gotten in measuring voltage unbalance.This paper proposed a new method of frequency correction and applied it into linearKalman filter to measure voltage sag. Simulation results show that even in the case offrequency offset, harmonics and noise, this method can also exactly detect the voltagesag characteristics (sag amplitude, starting and ending time and angle jump), has strongrobustness.This paper proposed a method combines S transform with time-domain method, andthe tree based on simple rules, to identify eight categories power quality disturbances.This method is easy to add new type of power quality disturbance to the system, andavoid complex training process of artificial intelligence methods and classification errorcaused by the lack of training samples. Feature extraction method based on S transformhas the ability of anti-noise and high recognition rate. S transform could achieve fastcomputing by using Fourier transform, which could reduce the feature extraction time,has huge application space in real-time monitoring and identification.