电气技术2025，Vol.26Issue(4)：7-12,19,7.
基于时序自适应方法的配电网高阻接地故障检测模型
Sequence-adaptive high impedance fault detection model
摘要
Abstract
High impedance fault(HIF)is difficult to detect because of the low fault current amplitude and they can be easily confused with switching events.Existing HIF detection methods mainly rely on fixed time-window data.However,a fixed decision time often fails to balance the accuracy and speed of HIF detection.Thus,a sequence-adaptive HIF detection model is proposed in this paper.Firstly,zero-sequence current data of the faulty feeder are processed into variable-length training set.Then,a gated recurrent unit(GRU)model is trained based on variable-length data and cost-sensitive coefficient method to construct biased models.Two GRU models with opposite propensities are combined into an evaluation model.The test results on the PSCAD/EMTDC simulation platform show that the detection accuracy rate of this proposed model can reach 99.13%,and the detection speed is improved by at least 37.52%compared to the fixed time-window method.Delayed decision-making improves the accuracy of HIF detection and reduces the risk of harm.关键词
代价敏感/时序自适应/高阻接地故障(HIF)/变分模态分解(VMD)Key words
cost-sensitive/sequence-adaptive/high impedance fault(HIF)/variational mode decomposition(VMD)引用本文复制引用
林系紊,林建新..基于时序自适应方法的配电网高阻接地故障检测模型[J].电气技术,2025,26(4):7-12,19,7.基金项目
福建省自然科学基金(2022J01113) （2022J01113）
