When high-impedance faults(HIFs)occur in resonant grounded distribution networks,the current that flows is extremely weak,and the noise interference caused by the distribution network operation and the sampling error ...When high-impedance faults(HIFs)occur in resonant grounded distribution networks,the current that flows is extremely weak,and the noise interference caused by the distribution network operation and the sampling error of the measurement devices further masks the fault characteristics.Consequently,locating a fault section with high sensitivity is difficult.Unlike existing technologies,this study presents a novel fault feature identification framework that addresses this issue.The framework includes three key steps:(1)utilizing the variable mode decomposition(VMD)method to denoise the fault transient zero-sequence current(TZSC);(2)employing a manifold learning algorithm based on t-distributed stochastic neighbor embedding(t-SNE)to further reduce the redundant information of the TZSC after denoising and to visualize fault information in high-dimensional 2D space;and(3)classifying the signal of each measurement point based on the fuzzy clustering method and combining the network topology structure to determine the fault section location.Numerical simulations and field testing confirm that the proposed method accurately detects the fault location,even under the influence of strong noise interference.展开更多
线缆混合输电线路故障时将出现更加复杂的行波折反射现象,对于故障测距带来不小的难度。为解决此类问题,根据电缆与架空线各自的结构、特性的不同,在输电线路上安装分布式的行波检测装置将线路分成若干区间。应用皮尔逊相关系数的相关...线缆混合输电线路故障时将出现更加复杂的行波折反射现象,对于故障测距带来不小的难度。为解决此类问题,根据电缆与架空线各自的结构、特性的不同,在输电线路上安装分布式的行波检测装置将线路分成若干区间。应用皮尔逊相关系数的相关性原理,确定故障发生的区间。通过详细的公式推导,抵消掉波速对测距精度的影响,利用第二个SVD(singular value decomposition)分量标定出信号奇异点的脉冲模极大值,推导出分区间不含波速的混合线路故障定位算法。通过PSCAD仿真及MATLAB数据处理结果表明,与常规的单双端测距法应用于线缆组成的混合输电线路相比,可进一步提高测距精度。展开更多
基金supported in part by the Science and Technology Program of State Grid Corporation of China(No.5108-202218280A-2-75-XG)the Fundamental Research Funds for the Central Universities(No.B200203129)the Postgraduate Research and Practice Innovation Program of Jiangsu Province(No.KYCX20_0432)。
文摘When high-impedance faults(HIFs)occur in resonant grounded distribution networks,the current that flows is extremely weak,and the noise interference caused by the distribution network operation and the sampling error of the measurement devices further masks the fault characteristics.Consequently,locating a fault section with high sensitivity is difficult.Unlike existing technologies,this study presents a novel fault feature identification framework that addresses this issue.The framework includes three key steps:(1)utilizing the variable mode decomposition(VMD)method to denoise the fault transient zero-sequence current(TZSC);(2)employing a manifold learning algorithm based on t-distributed stochastic neighbor embedding(t-SNE)to further reduce the redundant information of the TZSC after denoising and to visualize fault information in high-dimensional 2D space;and(3)classifying the signal of each measurement point based on the fuzzy clustering method and combining the network topology structure to determine the fault section location.Numerical simulations and field testing confirm that the proposed method accurately detects the fault location,even under the influence of strong noise interference.
文摘线缆混合输电线路故障时将出现更加复杂的行波折反射现象,对于故障测距带来不小的难度。为解决此类问题,根据电缆与架空线各自的结构、特性的不同,在输电线路上安装分布式的行波检测装置将线路分成若干区间。应用皮尔逊相关系数的相关性原理,确定故障发生的区间。通过详细的公式推导,抵消掉波速对测距精度的影响,利用第二个SVD(singular value decomposition)分量标定出信号奇异点的脉冲模极大值,推导出分区间不含波速的混合线路故障定位算法。通过PSCAD仿真及MATLAB数据处理结果表明,与常规的单双端测距法应用于线缆组成的混合输电线路相比,可进一步提高测距精度。
