Evaluation Study On The Effect Of Urban Rail Stray Current On DC Bias Of Power Transformer

In recent years,the transformer DC bias problem caused by urban rail stray currents has appeared in many areas.With the rapid development of urban rail transit,the stray currents generated by urban rail transit operations have also appeared networked,persistent,and superimposed.With the increasing trend,the DC bias of the main power transformer caused by the stray current will be further exacerbated.However,the DC bias of the transformer caused by the stray current is an emerging problem in recent years.Such studies are few and in-depth.Therefore,the contradiction between the increasingly serious DC bias of the main transformer and the corresponding research is becoming increasingly prominent.In this context,this paper expands the modeling and analysis of the DC bias of the transformer in the regional power grid,uses the simulation results to achieve the fitting calculation of the neutral point current and the excitation current characteristic,and expands the urban rail stray current to the power Study on the evaluation of the influence of DC bias of the transformer.Firstly,this paper discuss the specific influence mechanism of urban rail stray current on the DC bias of the main power transformer.On this basis,the main transformer simulation model under the regional power grid is built based on the actual topology and parameters of a certain regional power grid,focusing on the realization of 500 k V autotransformer,hybrid Modeling work such as scattered current injection sources,and the comparison between the measured data and the simulation results verify the accuracy of the simulation model.And through the simulation results,it is clear that the main transformer neutral point current value is closely related to the excitation current distortion.Then,based on the characteristic analysis of the excitation current of the main transformer,the four characteristic quantities of the maximum and minimum values of the waveform,the DC component,and the total harmonic distortion rate are selected,and the neutral current of the main transformer is used as the input.The characteristic quantity of the excitation current is the output.Based on the BP neural network,curve fitting research is carried out and the training sample is used to optimize the neural network.The test sample and the measured data verify that the fitting model has a good fitting effect under actual working conditions.Also laid the foundation for follow-up research.Finally,the four characteristic quantities of the maximum and minimum values of the excitation current waveform,the DC component,and the total harmonic distortion rate are also selected as the state index quantities,and the improved analytic hierarchy process is used to determine the weight coefficients of the state index quantities of the main transformer excitation current.The inverter is divided into different operating states under the influence of DC bias,and the threshold values of different status indicators in each operating state are determined and degraded.The gray cloud model is used to finally determine the membership of each state and realize the DC bias of the transformer.Combined with the impact assessment and fitting calculation work,the impact assessment of the DC bias of the main transformer using the neutral point current as the evaluation index is realized.The verification shows that it has strong practicability and high practical use value.This paper studies the DC bias of the transformer under the influence of DC bias.Based on the research content of this paper,the status assessment of the main transformer under the influence of DC bias is realized.The evaluation results can be used for the DC bias of the grid operation and maintenance departments.The management of magnetic problems provides theoretical reference and technical guidance,and is also of great significance to the stable and reliable operation of the AC power grid.