Fault section location of active distribution network based on multi-layer model

MA Long; MA Jie; YANG Hao; SHI Zhitong; QIU Yucheng

doi:10.3969/j.issn.1672-3643.2024.04.006

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Fault section location of active distribution network based on multi-layer model

更新时间：2026-06-27

- Fault section location of active distribution network based on multi-layer model
- Ningxia Electric Power Issue 4, (2024)
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- DOI：10.3969/j.issn.1672-3643.2024.04.006
  CLC：
- Online First：19 September 2024，
  
  Published：2024
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MA Long, MA Jie, YANG Hao, et al. Fault section location of active distribution network based on multi-layer model[J]. Ningxia Electric Power, 2024, (4).
DOI：

MA Long, MA Jie, YANG Hao, et al. Fault section location of active distribution network based on multi-layer model[J]. Ningxia Electric Power, 2024, (4). DOI： 10.3969/j.issn.1672-3643.2024.04.006.

摘要

为应对大规模分布式电源(distributed generation，DG)并网给配电网故障定位带来的新挑战，提出了基于自适应免疫算法的有源配电网故障区段定位方法。基于自适应免疫算法进行故障区段定位，有效降低了在故障信息失真情况下传统免疫算法易陷入局部最优解的概率。首先，引入一种非线性自适应交叉变异算子改进策略，建立适用于分布式电源接入的自适应免疫算法函数计算模型，然后基于该算法对各节点馈线终端装置（feeder terminal unit，FTU）遥信信息进行处理，以快速准确地定位故障区段。基于MATLAB对含DG的IEEE 33节点配电网进行仿真验证，结果显示该方法显著提高了故障定位的速度和精度。

Abstract

To address the new challenges brought by large-scale distributed generation (DG) grid connection to fault location in distribution networks

an active distribution network fault section localization method based on adaptive immune algorithm is proposed. Based on adaptive immune algorithm for fault segment localization

it effectively reduces the probability of traditional immune algorithms falling into local optimal solutions in the case of distorted fault information. Firstly

an innovative nonlinear adaptive cross mutation operator improvement strategy is introduced to establish an adaptive immune algorithm function calculation model suitable for distributed power generation access. Then

based on this algorithm

the remote signal information of each feeder terminal unit (FTU) node is processed to quickly and accurately locate the fault section. Based on MATLAB

simulation tests were conducted on an IEEE 33 node distribution network with DG

and the test results showed that this method significantly improved the speed and accuracy of fault localization.

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