Ferroresonance Fault Identification Based On HHT Transform And Multi Scale Permutation Entropy Algorithm

Single phase grounding is the most common fault type in neutral ungrounded distribution network system.Before single-phase grounding fault occurs,it is often accompanied by arc grounding fault.After single-phase grounding fault disappears,it is easy to trigger ferromagnetic resonance fault.These three kinds of fault characteristics are similar,but the treatment methods are different,especially if ferromagnetic resonance fault is not handled in time,it will cause the consequences of fuse burning or transformer damage,which seriously affects the stable operation and power supply reliability of power system.Identifying the ferroresonance fault and distinguishing it from single-phase grounding fault and arc grounding fault in time can provide an important basis for taking corresponding suppression measures in time.For this reason,on the basis of reading a large number of references at home and abroad,a ferroresonance fault identification method based on HHT transform and multi-scale permutation entropy algorithm is proposed.The main research work is as follows:Firstly,on the basis of analyzing the fault mechanism of single-phase grounding,arc grounding and ferroresonance,the above three kinds of faults are simulated.On the basis of the fault waveform data obtained from simulation,combined with the fault characteristics and non-stationary signal eigenvalue extraction method,a ferroresonance fault identification method based on HHT transform and multi-scale permutation entropy algorithm is proposed.Secondly,EMD is used to decompose the fault neutral voltage data,and the endpoint effect problem in EMD decomposition is dealt with by image symmetry extension method.Then,all IMF components are transformed by Hilbert transform to obtain Hilbert Huang spectrum and Hilbert marginal energy spectrum.According to the frequency spectrum characteristics of the signal,the fault of high frequency resonance and frequency division resonance is preliminarily identified;On this basis,the IMF component with the highest correlation coefficient with the original signal is selected by correlation coefficient method for multi-scale permutation entropy analysis..According to the complexity and regularity of the signal,the fundamental frequency resonance,arc grounding and single-phase grounding fault signals are further distinguished.On this basis,the ferromagnetic resonance fault is accurately identified.Finally,combined with the actual parameters of a 110 kV Substation in Bazhou,Xinjiang,a simulation model is built.After simulating the above three kinds of faults under various working conditions,a large number of fault data are obtained.The proposed fault identification method is applied to distinguish ferromagnetic resonance faults.After verifying the effectiveness of the method,the feasibility of the identification method under the condition of uncertain influencing factors is analyzed.Compared with the wavelet energy spectrum identification method,it shows the superiority of the proposed method.