Harmonic/Interharmonics Detection Based On Windowed Interpolation And Complex Modulation Refinement

In the current situation of global energy interconnection,power electronic equipment,fluctuating power sources,and non-linear loads are heavily used in power systems,which can cause serious power quality pollution problems.There are not only integral harmonic components in the power system,but also non-integer harmonics,ie,interharmonics.Interharmonics have the same hazards as harmonics,and can also cause system voltage fluctuations and flicker.The effective control of harmonics and inter-harmonics is an important guarantee for the safe operation of power systems.However,the accurate detection of harmonics and interharmonics is the precondition of governance.Therefore,it is necessary to explore the detection algorithms of harmonics and interharmonics.The Fourier transform is the most commonly used harmonic and interharmonic detection method.The biggest problem of the Fourier transform algorithm is that due to the unpredictable and fluctuating nature of the signal,it is very difficult to sample it synchronously,thus resulting in spectrum leakage and barrier effects.The windowing function can effectively suppress the spectral leakage,and the interpolation can effectively solve the fence effect phenomenon.However,there is a contradiction problem in the existing windowed interpolation Fourier transform.The windowing interpolation algorithm with higher precision has a larger amount of calculation,and the less accurate windowing interpolation has a smaller amount of calculation.Based on this problem,this paper proposes a method of three-term 3rd-order Nuttall window bispectral interpolation.Compared with other window function interpolation methods,this algorithm has the advantages of higher detection accuracy and less computational cost.Can be used as an effective method to solve the spectrum leakage and barrier effect detection methods.Window interpolation algorithm is generally constrained by the frequency resolution.When there is a dense spectral component in the signal,due to the severe leakage of interharmonics caused by the fundamental wave or harmonic wave,inter-harmonic detection will cause larger errors.In this paper,the improved complex modulation and refinement method with high frequency resolution is used as a detection method for dense spectral signal components.Improved Complex Modulation Bandpass Filter Complex Modulation Refinement Analysis By constructing a complex analytic bandpass filter,sampling densely spectral regions,sampling low-pass filtering,frequency shifting,and FFT spectral analysis to obtain accurate dense spectral signal components.Compared with the conventional complex modulation refinement,the frequency shift and reanalysis bandpass filtering of the signal is first avoided,which avoids a complex frequency adjustment process and helps reduce the amount of work.Through theoretical analysis,according to the maximum spectral line of the signal and the phase characteristic of the submaximal spectral line,it can be judged whether there is spectral interference in each component of the signal,ie,whether there is a dense spectrum.Finally,this paper proposes an analysis method that combines windowing interpolation and complex modulation and refinement spectrum algorithm.The method determines whether there is interference in the peak spectrum of the main lobe based on the phase characteristics between adjacent spectral lines in the main lobe of the windowed signal.If there is main-lobe interference,the complex modulation and refinement is performed within a certain frequency range where the maximum spectral line is the center frequency,and the harmonic and interharmonic parameters closer to each other in the frequency band are obtained.If there is no main-lobe interference,the harmonics and inter-harmonics parameters at this frequency band are directly obtained through windowed interpolation.Repeat the above steps to obtain other harmonics and interharmonic components of the signal.Finally,The simlation error results of the example verify the feasibility and effectiveness of the method.