Detection and Localization of Series Arc Faults in DC Microgrids Using Kalman Filter
Detection and Localization of Series Arc Faults in DC Microgrids Using Kalman Filter
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DOI：
10.1109/jestpe.2020.2987491
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发表时间：
2020-04
影响因子：
5.5
通讯作者：
K. Gajula;L. Herrera
中科院分区：
文献类型：
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作者：
K. Gajula;L. Herrera
数据中心网络在广泛的应用中越来越受欢迎。然而，在检测和定位高阻抗串联电弧故障方面存在困难，这是减缓直流网络/微电网广泛部署的主要挑战。本文介绍了一种基于卡尔曼滤波（KF）的直流微电网运行监测算法，该算法通过估计线路导纳来检测/定位串联电弧故障。该算法利用配电网中各节点的电压和电流样本来估计线路导纳。通过确定这些值，可以在故障发生后快速隔离故障部分并重新配置网络。由于高阻抗串联电弧故障所引起的扰动几乎遍及整个微电网，因此采用KF算法对电网中的故障线进行精确检测。给出了仿真和控制的硬件在环（CHIL）结果，证明了实现的可行性。
DC networks are becoming more popular in a wide range of applications. However, the difficulty in detecting and localizing a high-impedance series arc fault presents, a major challenge slowing the wider deployment of dc networks/microgrids. In this article, a Kalman filter (KF)-based algorithm to monitor the operation of a dc microgrid by estimating the line admittances and consequently detecting/localizing series arc faults is introduced. The proposed algorithm uses the voltage and current samples from the nodes in the distribution network to estimate the line admittances. By determining these values, it is possible to quickly isolate the faulted section and reconfigure the network after a fault occurs. Since the disturbance caused by a high-impedance series arc fault spreads across almost the entire microgrid, the KF algorithm is structured to detect the faulted line in the grid with precision. Simulation and control hardware-in-the-loop (CHIL) results are presented, demonstrating the feasibility of implementation.