基于微型同步相量测量单元的配电网单相接地故障定位
摘要:准确定位配电网的故障对于提高供电的可靠性和减少连续停电所造成的损失有着重要的意义，微型同步相量测量单元(micro-phasor measurement units，μPMU)的应用，为配电网故障准确定位提供更多的信息。为此，提出了一种基于μPMU信息的极限梯度提升和基于遗传算法的支持向量机的配电网单相接地故障定位方法。首先，通过μPMU提供的零序电流方向判断故障区段；然后，依据端电压电流正序向量和实际故障距离的特征集训练组合算法测距模型；最后，用组合算法故障定位器对验证集的故障定位。通过Matlab/Simulink仿真，证明该方法能够有效定位故障，承受过渡电阻、故障类型和噪声的影响，与传统的机器学习方法比较，组合模型定位方法的定位精度更高。
Abstract：Accurate fault location of distribution network is of great significance to improve the reliability of power supply and reduce the loss caused by continuous power outage. The application of micro-phasor measurement units(μPMU) in distribution network provides more information for accurate fault location. Therefore, a distribution network single-phase grounding fault location method based on the extreme gradient boosting (XGBoost) of μPMU information and the support vector unit model based on genetic algorithm (SVM-GA) is proposed. Firstly, the fault section is judged by the zero-sequence current direction provided by μPMUS. Then, based on the positive sequence vector of terminal voltage and current and the feature set of actual fault distance, the combined algorithm distance model is trained. Finally, the combined algorithm fault locator is used to locate the fault of the verification set. Through Matlab/Simulink, it is proved that this method can effectively locate the fault and can withstand the influence of transition resistance. Compared with the commonly used method, the positioning accuracy of the combined positioning method is higher.
标题：基于微型同步相量测量单元的配电网单相接地故障定位
title:Distribution Network Single-Phase Grounding Fault Location Based on Micro-Phasor Measurement Units
作者：曹 赟, 姚 方, 文福拴
authors:CAO Yun, YAO Fang, WEN Fushuang
关键词：配电网,故障定位,微型同步相量测量单元(μPMU),极限梯度提升,遗传算法,支持向量机,
keywords:distribution network,fault location,micro-phasor measurement units(μPMU),extreme gradient boosting,genetic algorithm,support vector machine,
发表日期：2022-04-08
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