Research On Detection Method Of Transient Power Quality Disturbance Signal

In recent years,the power quality problems caused by the power sector and the user’s attention,in modern society has gradually become the most widely used and indispensable energy.Due to the extensive use of a large number of precision instruments and power electronic devices,the power quality of the power grid is deteriorating day by day,will inevitably cause the decline of power quality.Analysis and study of power quality disturbance signal has gradually become the main research topic of modern power system,which has important research significance.First of all,this paper summarizes the domestic and international research on power quality detection.The concept and classification of power quality are described from different angles.The characteristics of power quality disturbance signal are analyzed and summarized,and the mathematical model of disturbance signal and the corresponding waveform are given.The basic principles of Fourier transform,short-time Fourier transform and wavelet transform are analyzed deeply.The application of this method in power quality analysis is explored and compared.Secondly,in the practical engineering application,because of the interference of external factors,the detected signals usually contain noise.When wavelet denoising is used,the original signal and noise signal are closer to each other in a few areas.It is easy to mistakely regard some of the details of the original signal as a noise signal to remove.In order to better preserve the useful information of the original signal,this paper proposes an improved denoising algorithm based on coefficient transformation.The simulation results of MATLAB show that the algorithm can remove the noise and reproduce the original signal better.Thirdly,because the wavelet transform has good time-frequency localization characteristics,and according to the transient power quality signal,the signal singularity can be reflected by the wavelet transform modulus maxima.In this paper,we propose a dynamic window mode maximum perturbation localization algorithm based on wavelet transform.In order to solve the problem that there is no obvious mutation point and zero crossing detection in the detection of signal mutation point,the algorithm is improved.The feasibility of the proposed method is proved by the simulation experiments of single and complex disturbances.Finally,the S transform method is used to detect the disturbance signal.We can extract the starting and ending time of the disturbance signal,the amplitude of the disturbance and thefrequency characteristic from the S transform result matrix.Draw the square sum mean curve of the column vector,maximum curve of the column vector and the square sum mean curve of the row vector of the S transform modulus matrix.Through the three-dimensional network diagram and three kinds of curves,we can clearly see the disturbance characteristics of the signal and detect the time,amplitude and frequency of the signal.The advantage of S transform in transient power quality disturbance detection is confirmed.