The Detection And Identification Of Power Quality Based On Wavelet Transform

As a result of the development of economy, the power quality to which is paid attention by more and more users and electric power department is not only the deviation of voltage and frequency from the rating value, but also include the phenomenon of oscillation and pulse.So, it is necessarily to detect and identify the power quality. Based on this, this paper studied the methods of the detection and identification of power quality.Firstly, in order to save the storage space and the transmission time of data, it is necessarily to compress the data of power quality. According to characteristic of the transient disturbance data of power quality which frequency is very high, this paper put forward that the method based on optional wavelet packet apply to the compression of transient disturbance data of power quality. Finally, by comparing with the method based on the wavelet, we can draw the conclusion that the distortion rate of former is lower when the compression rate of the both is approximately same. Secondly, this paper used the theory of wavelet transform modulus maxima to realize the detection of power quality. Finally, the improved method of self-Organizing Feature Map (SOFM) was put forward to identify the kind of power quality. By the simulation of MATLAB. these methods are verified to be feasible.