The distribution line is an important part of a power system. How to quickly eliminate faults is of great significance to improve the power supply reliability. Based on electromagnetic time-reversal (EMTR), this article proposes a fault location estimation algorithm calculated by the finite-difference time-domain (FDTD) method to solve two problems. One is the calculation efficiency of the fault current based method in the EMTR, and the other is the fault location accuracy of the EMTR-based method when the measurement device has a low sampling rate in the direct time. We first derived the FDTD updated equation of the node voltage, which is at the discontinuous point of the lossless single conductor transmission line. The algorithm obtains the fault current at any transverse branch of the distribution line through one-time simulation, which improves the calculation efficiency. Furthermore, considering the sampling rate of the transient signals, we analyzed the impact of the spectrum range of the transient signal, the interval of the guessed fault location, the length of the time-reversal window, the fault impedance, and the length of the line. The results showed that when the transient signal is measured at a high sampling rate (10 MHz), the proposed algorithm can be used to locate the fault with a minimum time-reversal window of 1 ms. When the sampling rate is as low as 100 kHz, the proposed algorithm can achieve accurate fault location estimation compared to the algorithm in the other time-domain electromagnetic transient simulation. The error of the proposed location algorithm is less than 100 m.

中文翻译：

---

基于时域有限差分电磁时间反演法的配电线路故障定位估计算法


配电线路是电力系统的重要组成部分。如何快速排除故障对于提高供电可靠性具有重要意义。本文提出一种基于电磁时间反演（EMTR）的时域有限差分（FDTD）方法计算的故障定位估计算法来解决两个问题。一是EMTR中基于故障电流的方法的计算效率，二是测量装置在直接时间内采样率较低时基于EMTR的方法的故障定位精度。我们首先推导出节点电压的FDTD更新方程，该节点电压位于无损单导体传输线的不连续点。该算法通过一次性仿真获得配电线路任意横向支路的故障电流，提高了计算效率。此外，考虑暂态信号的采样率，分析了暂态信号的频谱范围、猜测故障位置的间隔、时间反转窗口的长度、故障阻抗以及时间反转窗口长度的影响。线。结果表明，当以高采样率（10 MHz）测量瞬态信号时，所提算法可以在最小时间反转窗口为1 ms的情况下定位故障。当采样率低至100 kHz时，与其他时域电磁暂态仿真中的算法相比，该算法可以实现准确的故障定位估计。所提出的定位算法的误差小于100 m。