洪 翠,吴奕炜,高 伟,郭谋发.基于 GrapSAGE 算法的配电网故障定位方法[J].电子测量与仪器学报,2023,37(11):236-245 |
基于 GrapSAGE 算法的配电网故障定位方法 |
Fault location method in distribution network based on GrapSAGE algorithm |
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DOI: |
中文关键词: 配电网故障定位 图学习算法 形态学黑帽运算 GSA 算法 拓扑结构变化 |
英文关键词:fault location in distribution network graph learning algorithm morphological black hat operation algorithm of GSA topology changing |
基金项目:福建省自然科学基金(2021J01633)项目资助 |
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中文摘要: |
本文提出一种基于 GraphSAGE (graph sample and aggregate)算法的配电网故障定位方法。 以对系统侧母线电压进行形
态学黑帽运算的结果启动故障定位算法;利用 GSA 模型自主挖掘网络拓扑和零序电流特征,根据节点特征和标签建立函数映
射,评估线路运行状态从而实现故障定位。 基于 PSCAD/ EMTDC 仿真平台搭建 IEEE33 节点模型,测试结果表明所提配电网故
障定位方法可行且有效。 并且配电网拓扑变化时,该方法无需重新训练模型即能获得可靠的故障定位结果,验证了方法的鲁棒
性和对拓扑变化的适应性。 |
英文摘要: |
A fault location method based on GraphSAGE (graph sample and aggregate, GSA) algorithm is proposed in this paper. The
morphological black hat operation is performed on the power-side bus voltage of the distribution network as the fault detection criterion to
start the fault location algorithm. The GSA model is used to independently mine topology and zero sequence current features, and
function mapping is established according to node features and labels to evaluate the running state of the line to achieve fault location.
Based on the PSCAD/ EMTDC simulation platform, an IEEE 33-node simulation model is constructed to acquire data resources and
validate the proposed method. Reliable fault location results are obtained by applying the proposed method. Furthermore, in distribution
networks with topological changes, the model can obtain reliable fault localization results without retraining, which verifies the robustness
and adaptability of the method to topological changes |
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