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Faulty Feeder Detection Based on Fundamental Component Shift and Multiple-Transient-Feature Fusion in Distribution Networks

机译:基于基础组件移位和分配网络的多瞬态特征融合的故障馈线检测

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摘要

When a single-phase-to-ground (SPG) fault occurs in a distribution network, the current is weak, and the fault conditions are complex; the existing fault detection technologies do not show reliable performance. Unlike the existing detection methods, we introduced a fundamental component shift and multiple-transient-feature fusion method in this article. To remove the fundamental component (FC) that contained in the transient zero-sequence current (TZSC), Hilbert transform was used to calculate the analytic signal of TZSC. Then, the shift factor was introduced to remove the FC such that all the transient features can be kept. Second, three typical transient features indexes were calculated. Then, the multiple evidence estimation method was used to fuse the transient features indexes. Finally, selected the feeder with the maximum fault degree as the faulty feeder. To verify the accuracy and extensive applicability of the proposed method, developed the sample radial distribution network model with different fault conditions, arc fault model, and the modified IEEE-34-node test system with power electronics generator and wind energy conversion systems, the proposed method shows good performance.
机译:当在配送网络中发生单相到地(SPG)故障时,电流较弱,故障情况很复杂;现有的故障检测技术没有显示可靠的性能。与现有的检测方法不同,我们在本文中引入了基本的组件移位和多瞬态特征融合方法。为了删除包含在瞬态零序电流(TZSC)中的基本组件(FC),使用Hilbert变换来计算TZSC的分析信号。然后,引入换档因子以移除Fc,使得可以保持所有瞬态特征。其次,计算了三种典型的瞬态特征指标。然后,使用多个证据估计方法熔断瞬态特征索引。最后,选择具有最大故障程度的馈线作为故障送纸器。为了验证所提出的方法的准确性和广泛适用性,开发了具有不同故障条件,电弧故障模型和具有电力电子发电机和风能转换系统的改进IEEE-34节点测试系统的示例径向分布网络模型,提出方法显示出良好的性能。

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