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突变量与形态学相结合的配电网故障时刻检测方法 被引量:8

A fault time detection method in a distribution network based on a sudden change of current and mathematical morphology
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摘要 在配网应用中,以故障时刻为同步基准的差动保护需要精准地检测故障发生时刻。而常见的相电流突变量故障时刻检测方法的误差受故障发生时刻、分布式电源故障特性等因素的影响较大,会给差动保护带来较大的同步误差。为此,提出了适用于配电网故障时刻自同步原理的精确故障时刻检测方法。首先以传统相电流突变量检测算法为基础选取数据窗,然后对窗内数据应用改进多分辨形态梯度算子进行处理,得到凸显波形突变情况的梯度信号。之后利用该梯度信号的极值点位置提取故障发生时刻。最后PSCAD仿真以及现场试验数据验证结果表明,该方法检测精度高、稳定性好,可有效减小因故障时刻检测而产生的同步误差。 Differential protection based on fault time self-synchronization principle requires to detect fault time accurately in distribution network.However,the error in the conventional phase current sudden-change-based fault time detection method is greatly affected by the fault occurrence time,distributed power generation fault characteristics and other factors.These can cause a large synchronization error in the differential protection.Therefore,an accurate fault time detection method is proposed,one which is suitable for the fault time self-synchronization principle in a distribution network.First,a data window is selected based on a conventional phase current sudden-change detection algorithm,and then an improved multi-resolution morphological gradient operator is used to process the data to obtain the gradient signal.This highlights the waveform mutation.Then the fault time is extracted through extreme point positions of the gradient signal.Finally,PSCAD simulation and field test data show that this method has high detection accuracy and good stability,and can effectively reduce the synchronization error caused by fault time detection.
作者 张运驰 高厚磊 袁通 向岷江 ZHANG Yunchi;GAO Houlei;YUAN Tong;XIANG Minjiang(School of Electrical Engineering,Shandong University,Jinan 250061,China;State Grid Jinan Power Supply Company,Jinan 250012,China)
出处 《电力系统保护与控制》 EI CSCD 北大核心 2022年第12期54-62,共9页 Power System Protection and Control
基金 国家电网公司总部科技项目资助(5100-202055018A-0-0-00) 山东电力公司科技项目资助(5206011900DG)。
关键词 配网差动保护 自同步原理 同步误差 故障时刻检测 改进多分辨形态梯度 distribution network differential protection self-synchronization principle synchronization error fault time detection improved multi-resolution morphological gradient
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