The autotransformer(AT)neutral current ratio method is widely used for fault location in the AT traction power network.With the development of high-speed electrified railways,a large number of data show that the relat...The autotransformer(AT)neutral current ratio method is widely used for fault location in the AT traction power network.With the development of high-speed electrified railways,a large number of data show that the relation between the AT neutral current ratio and the distance from the beginning of the fault AT section to the fault point(Q-L relation)is mostly nonlinear.Therefore,the linear Q-L relation in the traditional fault location method always leads to large errors.To solve this problem,a large number of load-related current data that can be used to describe the Q-L relation are obtained through the load test of the electric multiple unit(EMU).Thus,an improved fault location method based on the back propagation(BP)neural network is proposed in this paper.On this basis,a comparison between the improved method and the traditional method shows that the maximum absolute error and the average absolute error of the improved method are 0.651 km and 0.334 km lower than those of the traditional method,respectively,which demonstrates that the improved method can effectively eliminate the influence of nonlinear factors and greatly improve the accuracy of fault location for the AT traction power network.Finally,combined with a shortcircuit test,the accuracy of the improved method is verified.展开更多
基金supported by the National Key Research and Development Program of China(No.2021YFB2601500)the Natural Science Foundation of Sichuan Province(No.2022NSFSC0405)。
文摘The autotransformer(AT)neutral current ratio method is widely used for fault location in the AT traction power network.With the development of high-speed electrified railways,a large number of data show that the relation between the AT neutral current ratio and the distance from the beginning of the fault AT section to the fault point(Q-L relation)is mostly nonlinear.Therefore,the linear Q-L relation in the traditional fault location method always leads to large errors.To solve this problem,a large number of load-related current data that can be used to describe the Q-L relation are obtained through the load test of the electric multiple unit(EMU).Thus,an improved fault location method based on the back propagation(BP)neural network is proposed in this paper.On this basis,a comparison between the improved method and the traditional method shows that the maximum absolute error and the average absolute error of the improved method are 0.651 km and 0.334 km lower than those of the traditional method,respectively,which demonstrates that the improved method can effectively eliminate the influence of nonlinear factors and greatly improve the accuracy of fault location for the AT traction power network.Finally,combined with a shortcircuit test,the accuracy of the improved method is verified.
文摘针对高速铁路出现牵引网网压低频振荡导致多个动车所的多台动车组牵引封锁现象,首先建立动车组线侧脉冲整流器状态空间模型;其次对动车组整流器设计了一阶非线性自抗扰控制器(active disturbance rejection control,ADRC)来替换传统的基于线性比例-积分(proportional integral,PI)控制器的瞬态电流控制策略(transient current control strategy,TCCS);随后从设置过渡过程,计算扩张状态观测器等方面展开,将外界扰动和系统内部扰动归算为总扰动,并给出相应的动态非线性补偿;最后,在Matlab/Simulink平台上搭建基于传统PI控制器和基于ADRC控制器的TCCS的双重化整流器模型,对比分析后得出ADRC控制具有更强的鲁棒性结论。为进一步验证ADRC控制效果,还将该仿真模型接入牵引网系统链式仿真模型中,发现该控制策略在具有较强鲁棒性和对参数不敏感性的同时,对牵引网网压低频振荡过电压有着较好的抑制效果。
