Research On Disturbance Analysis And Feature Recognition Of Hybrid Power Quality

In recent years,with the extensive application of nonlinear devices in the power grid,there are lots of transient disturbance signals in the power grid.These disturbance signals will not only pollute the power quality,but also cause a lot of economic losses.At the same time,many precision instruments have put forward higher requirements for the stability and reliability of the power quality.In order to solve this problem,it is necessary to analyze and study the disturbance in the power grid.Based on this,the common single power quality disturbance signal and mixed disturbance signal are analyzed and studied in this paper.(1)the wavelet threshold de-noising of the power quality disturbance signal is carried out.First,6 kinds of single power quality disturbances and 6 kinds of hybrid power quality disturbance signals are analyzed in detail.On this basis,the characteristics of the power quality disturbance signal are analyzed and simulated by MATLAB modeling.The d B4 small wave base is used to de-noise the disturbance signal and the threshold of wavelet de-noising is determined by the mini-max criterion.Comparison of wavelet hard threshold and soft threshold de-noising signal waveform and the signal-to-noise ratio of the size,the results show that the hard threshold de-noising method in de-noising effect on transient oscillation than the soft threshold de-noising method to enhance the signal-to-noise ratio close to 2%,in other signal de-noising,the effect of hard threshold and soft threshold method are same.(2)the time frequency analysis of power quality disturbance signals is carried out by using S transform.The single power quality disturbance signal and the mixed power quality disturbance signal are analyzed,and the amplitude spectrum,the sum of the absolute value of the S matrix column,the phase diagram and spectrum diagram of the signal are obtained.The two order derivative of sum of absolute value of S moment array can be used to locate transient disturbance signals.The analysis results show that the method can effectively locate and disturb transient disturbance signals.(3)the signal of power quality disturbance is identified.Based on the analysis of power quality disturbance signals,the value of the absolute value of the signal extraction and the difference spectrum,peak number,phase diagram of the skewness,amplitude characteristics,amplitude spectrum and phase diagram of the kurtosis kurtosis,S matrix and the absolute value of the kurtosis of 7 to table sign the original signal feature quantity.Then the decision tree classification threshold is determined by the optimal threshold principle,and the decision tree algorithm is used to classify and identify the disturbance.The experimental results show that the method has high classification accuracy and good noise immunity.When the SNR is 20 d B,the recognition rate of the algorithm can reach more than 92%,which can effectively identify the power quality disturbance signal.