Research On Single-phase High-resistance Grounding Fault Identification In Small Current Grounding System

The change of electric quantity is not obvious when the single-phase high-impedance grounding fault occurs in the low-current grounding system.If the fault is not dealt with in time,it will cause large area blackout,fire,electric shock and other serious accidents.Therefore,it is of great practical significance to identify the single-phase high-impedance grounding fault accurately.In practical power network,the current signals of high impedance grounding faults are often accompanied by various noises,which have great interference to the extraction of fault features.At the same time,the process of single-phase high-impedance grounding fault is complex,and the electrical amplitude and distortion characteristics under different conditions show certain differences,which is difficult to identify.Aiming at the above problems,this thesis studies the identification method of single-phase high impedance grounding fault for low current grounding system.The typical characteristics of single-phase high impedance grounding fault are summarized,and the influence of different fault conditions on the characteristics of high impedance grounding fault is analyzed.The measured zero-sequence current of high-impedance grounding fault is compared with the zero-sequence current of low-impedance grounding fault,and the typical characteristics of single-phase high-impedance grounding fault in time-frequency domain are summarized.Based on the PSCAD/EMTDC platform,a small current grounding system model was built.Different high-impedance grounding fault models were compared,and the high-impedance grounding fault model which best reflected the characteristics of high-impedance grounding fault was selected.Based on this model,the zero-sequence current of single-phase high-impedance grounding fault under different fault occurrence conditions is simulated,which lays a foundation for the subsequent denoising and identification work.In this thesis,the conventional denoising methods of power signal are compared.Aiming at the disadvantages of the traditional wavelet filtering method,such as complex operation and poor effect in the strong noise environment,the generalized mathematical morphological denoising algorithm is optimized by using the improved least mean square algorithm based on the traditional mathematical morphological alternating hybrid filter.Aiming at the inaccuracy of traditional empirical method in selecting structural elements,a cyclic algorithm based on RMSE evaluation criteria was designed.The denoising effects of different denoising methods are compared by taking different sinusoidal signal mixing and high impedance fault zero-sequence current mixing signals as examples respectively,and the effectiveness of the denoising method in this thesis is verified.Based on the support vector machine(SVM),the parameters were optimized by the improved quantum particle swarm optimization(QPSO-SVM),and the single-phase high impedance grounding fault identification model was constructed based on the improved QPSO-SVM.Aiming at the shortcomings of the traditional parameter optimization method of SVM,such as slow speed and low precision,the quantum particle swarm optimization algorithm(QPSO)was improved by introducing the α-value nonlinear asynchronous decline strategy,and the improved QPSO was used to optimize the parameters of SVM.The simulation of single-phase high impedance grounding fault and other faults and working conditions is carried out,and the recognition results of the proposed algorithm are compared with those of other algorithms to verify the effectiveness of the proposed method.The design idea and process of the single-phase high-impedance grounding fault identification method based on LMS-MM and improved QPSO-SVM are presented.Taking the measured fault zero-sequence current of a 10 kV ungrounded system in Z City,S Province as an example,the effectiveness of the single-phase high-impedance grounding fault identification method presented in this thesis is verified based on the identification accuracy and sensitivity.The results show that the proposed method based on LMS-MM and the improved QPSO-SVM can effectively identify the single-phase high-impedance grounding fault in the actual fault samples.