Research On The Method Of Selecting The Fault Line For Small Current Single-phase Grounding

In the power system,according to the different neutral point grounding methods,it is divided into small current grounding and large current grounding.In our country,the low-current grounding method is used in most of the low-voltage power distribution networks.Among them,the low-current grounding system can be divided into a neutral point ungrounded system,a neutral point grounded system through the arc suppression coil,and a neutral point grounded system through a large resistance.my country mainly adopts the first two methods mentioned above.The proportion of single-phase grounding faults in the overall faults of small current grounding systems is as high as 80%.However,when a ground fault occurs,there are many external interference factors and the amplitude of the fault current is relatively small,which brings great difficulties to the fault line selection.Therefore,it is of great significance to study a line selection method with high accuracy and strong applicability.Through analysis,it can be seen that it is no longer applicable and accurate to judge whether a line has a fault based on a single fault feature.Therefore,starting from the transient,steady state and other waveform characteristics of the zero sequence current before and after the line fault occurs,this paper proposes a new method of small current grounding fault line selection based on the combination of principal component analysis and support vector machine.This article first conducts a theoretical analysis of the neutral point through arc suppression coil grounding system and neutral point ungrounded system that are mainly used in our country,and understands the changes of the respective electrical quantities in the two systems when a single-phase ground fault occurs;using Matlab/Simulink The toolbox builds a system simulation model.By simulating a variety of common faults and comparing them with the theoretical analysis results,the accuracy of the model is verified and fault data is obtained at the same time to provide data support for the line selection algorithm.Then,the idea of controlled variable method is adopted and the information is used.The noise ratio and the root mean square error are used as the denoising quality evaluation indicators,and finally the dB8 wavelet is selected as the wavelet basis function,and the number of decomposition layers is 6 to denoise the noisy line signal.Principal component analysis is used to extract the features of the denoised signal,and finally the 4 groups of fault features with the strongest characterization ability are determined.Finally,the least squares support vector machine is used to establish the fault line classification model,and the improved fruit fly algorithm is used to optimize the model parameters.The experimental results show that the algorithm is not affected by the grounding method,and the fault line selection accuracy rate reaches more than 92%.In order to verify the validity and applicability of the algorithm,an ungrounded system fault simulation circuit was built in the laboratory,and the algorithm was tested by collecting fault data in the simulation circuit.The following conclusions are drawn from the test results:The algorithm in this paper fully combines the characteristics of both steady-state and transient periods,and can identify bus and feeder faults.It is not affected by fault distance,grounding angle,transition resistance,noise,and grounding method,which verifies the effectiveness and applicability of the method.