Method And Realization Of Interharmonics Detection In Power System

Fast Fourier transform(FFT)is the most commonly used method of interharmonics analysis,however,the direct use of FFT for interharmonics detection will produce spectrum leakage and fence effect,and the detection precision is low.In order to solve the influence of spectrum leakage on interharmonics detection,it is necessary to use a good window function to truncate the signal.This paper first analyzes the common window functions,studies the spectrum characteristics of different window functions,discusses the selection principles of window functions,and then analyzes the frequency domain characteristics of Five Maximum-sidelobe-decay(MSD)window.The results show that five MSD windows have better frequency domain characteristics than the common window functions.In order to further improve the sidelobe performance of the window function,the self convolution of the window function is carried out in this paper.The characteristics of five MSD self convolution windows are studied.The results show that with the increase of the convolution order,the sidelobe characteristics of the window function are getting better and better,but the width of the main lobe is also increasing.In order to give consideration to the width of the main lobe,Finally,five MSD two order self convolution windows are used as sampling windows to suppress the spectrum leakage of sampling signals.In order to reduce the impact of the fence effect on the interharmonics detection,the frequency domain interpolation is used to correct the error.Based on the analysis of the characteristics of spectral lines after windowing,the six spectral line interpolation algorithm is discussed.Combined with five MSD two order self convolution windows,five MSD two order self convolution six spectral line interpolation algorithm is presented,which is called five item six spectral line interpolation algorithm.And compared with the fast Fourier transform.Five item six spectral line interpolation algorithms are used to detect the interharmonic signals.First,the calculation accuracy of the algorithm itself is verified.Secondly,the algorithm is compared with other commonly used interpolation algorithms.Thirdly,the detection performance of the algorithm under the condition of noise,with a more dense interharmonic signal and the change of basic frequency is tested.The simulation results show that compared with other commonly used window interpolation algorithm,this algorithm has higher calculation accuracy;can meet the accuracy requirements in the presence of noise signal;when the interharmonics frequency distribution of dense,still accurate identification of interharmonics,and with the increase of the length of the sampling sequence,the accuracy of the identification of interharmonics is greatly improved;When the frequency of the fundamental wave changes,the effect of the algorithm itself is very small.The embedded development platform is set up,the design of the software framework is completed,and the development of the embedded user interface is completed.