Power Quality Analysis Technology Research And Realization

This paper is focusing on detection and classification of power quality disturbances. A comparison study on various available detection and classification approaches is presented first.This paper presents a Support Vector Machine (SVM) method for classification of dynamic power quality disturbances. The types of concerned disturbances include voltage sags, swells, interruptions, switching transients, flickers and harmonics. It is assumed that the analyzed waveforms generated in MATLAB are available in sampled form. Fourier transform and wavelet analysis are utilized to obtain unique features for the waveforms. A SVM classifier system is designed for making a decision regarding the type of the disturbance. Simulation studies are presented to verify the accuracy of the proposed approach, and the proposed approach is also reported to show the advantages of the proposed approach. The analysis of important parameters influencing the classification results is made too.A power quality detection system is designed based on Atmegal6. The hardware system composes of the data detecting, communication subsystem and so on. The paper discusses the measuring algorithm for sags, swells and interruptions, and the single_phase average voltage is used to measure sags, swells and interruptions. The general power quality such as harmonics, active power and so on is measured too through C programming.