基于电流偏差2-范数的有源配电网故障距离定位

doi:10.19595/j.cnki.1000-6753.tces.L80073

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摘要分布式电源的接入将对传统配电网的故障定位算法产生影响甚至使其失效。因此,该文提出一种基于电流偏差2-范数的故障定位算法。算法首先依次对配电网各个节点注入单位电流,通过匹配系统电源出口电流变化计算值与故障前的测量值获得线性比例系数;然后,对分布式电源的电流响应值进行修正,进而对其电流变化量进行2-范数电流偏差处理;最后,以最小电流偏差的节点进行故障区域识别和故障距离定位。本算法考虑了有源配电网的非平衡特性,而且无需预判故障类型,具有广泛的适应性。通过在PSCAD/EMTDC上搭建有源配电网的仿真模型,在Matlab上进行故障数据处理,验证了该算法的有效性和准确性。

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	刘鑫
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关键词 ：分布式电源, 有源配电网, 故障区域识别, 故障距离定位

Abstract：The access of the distributed power supply will affect or even invalidate the fault location algorithm of the traditional distribution network. Therefore, this paper proposes a fault location algorithm based on current deviation 2-norm. The algorithm firstly injects a unit current into each node of the distribution network, and obtains a linear proportional coefficient by matching the calculated value of the system power outlet current change with the measured value before the fault; then, correcting the current response value of the distributed power source, and then The current variation is subjected to 2-norm current deviation processing; finally, the fault region identification and fault distance location are performed by the node with the smallest current deviation. The algorithm takes into account the non-equilibrium characteristics of the active distribution network, and does not need to predict the type of fault, and has wide adaptability. By constructing the simulation model of the active distribution network on PSCAD/EMTDC, the fault data processing is performed on Matlab, which verifies the effectiveness and accuracy of the fault location algorithm.

Key words： Distribution generation active distribution network fault area identification fault distance positioning

收稿日期: 2018-06-20 出版日期: 2020-01-02

PACS:

TM721

作者简介: 刘鑫男,1995年生,硕士研究生,研究方向为有源配电网故障定位。E-mail: 1347582743@qq.com（通信作者）滕欢女,1965年生,高级工程师,硕士研究生导师,研究方向为调度自动化及计算机处理。E-mail: 13308027191@163.com

引用本文:

刘鑫, 滕欢, 梁梦可, 滕德云. 基于电流偏差2-范数的有源配电网故障距离定位[J]. 电工技术学报, 2019, 34(zk2): 720-728. Liu Xin, Teng Huan, Liang Mengke, Teng Deyun. Fault Distance Location of Active Distribution Network Based on 2-Norm Current Deviation. Transactions of China Electrotechnical Society, 2019, 34(zk2): 720-728.

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