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基于灰色关联度的配电网故障区段定位与类型识别方法 被引量:45

Grey Relational Degree Based Fault Section Location and Type Recognition Method for Distribution Network
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摘要 为了更全面准确地对配电网故障进行识别,提出了一种基于灰色关联度的配电网故障区段定位和故障类型识别方法。针对三相电流采用卡伦鲍厄相模变换得到0模、α模、β模,选择变化较为明显的模量,构造反映区段故障的综合模电流作为特征序列,再计算各区段的特征序列与参考正常区段之间的灰色关联度,与门限值比较从而确定故障区段。利用0模、α模、β模分量在故障前后的幅值畸变度,将故障初步分为单相接地、两相接地、相间短路故障三类。根据相模变换关系和不同类型故障的边界条件,选择不同的特征量进行灰色关联度计算,对计算结果分类处理,确定故障类型。IEEE 33节点配电网模型仿真实验结果验证了所提方法能够可靠准确地进行故障区段定位和故障类型识别,不受故障类型、接地电阻和故障相角的影响。 In order to identify the faults of distribution network more comprehensively and accurately,a method of fault location and fault type identification based on grey relational degree is proposed.Three-phase currents can be transformed to 0,αandβmodulus by Karrenbauer transformation.The module with more obvious change is selected,and the comprehensive module current that reflects the fault section is constructed as the feature sequence.Then,the grey correlation degree between the feature sequence of each section and the reference normal section is calculated,and the fault section is determined by comparing with the threshold value.The magnitude distortion of 0,αandβmodulus before and after faults is used to classify the faults into three categories:single-phase grounding,two-phase grounding and inter-phase short-circuit faults.According to the phase-mode transformation relationships and the boundary conditions of different types of faults,different characteristic variables are selected to calculate the grey relational degree,and the calculation results are classified to determine the type of faults.The simulation results of the IEEE 33-bus distribution network model verify that the proposed method can reliably and accurately locate the fault section and identify the fault type,and is not affected by the fault type,grounding resistance and fault phase angle.
作者 童晓阳 张绍迅 TONG Xiaoyang;ZHANG Shaoxun(School of Electrical Engineering,Southwest Jiaotong University,Chengdu 610031,China;Zhaotong Power Supply Bureau of Yunnan Power Grid Co.Ltd.,Zhaotong 657000,China)
出处 《电力系统自动化》 EI CSCD 北大核心 2019年第4期113-118,145,共7页 Automation of Electric Power Systems
基金 国家自然科学基金资助项目(51377137) 四川省科技厅重点研发项目(2017GZ0054)~~
关键词 配电网 故障定位 故障类型识别 灰色关联度 卡伦鲍厄相模变换 distribution network fault location fault type identification grey relational degree Karrenbauer phase-mode transformation
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