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基于相关矩阵和动态集合覆盖的配电网故障诊断方法 被引量:2

Dependency matrix and dynamic set-covering based fault diagnosis method for power distribution networks
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摘要 作为电力网络中直接向用户供电的关键环节,配电网的工作状态直接影响电力用户的用电质量和用电体验。为解决配电网故障线路区段的定位问题,提出了一种基于相关矩阵和动态集合覆盖的配电网故障诊断方法。根据配电网拓扑建立故障电流信息和故障线路区段相关矩阵,引入隐马尔科夫模型刻画每条线路区段随时间变化的状态序列;基于每个时间周期上馈线终端单元上报的故障电流信息集合,建立动态集合覆盖的配电网故障诊断模型,使用维特比译码求解满足集合覆盖条件的线路区段工作状态序列,实现对配电网的在线故障定位。通过仿真实例验证了基于相关矩阵和动态集合覆盖的配电网故障诊断方法的定位准确性和稳定性。 As a key part of the power network that directly supplies power to users,the working states of the power distribution networks influence the power quality and experience of users directly.In order to solve the problem of localizing the faulty sections in the power distribution networks,we propose a dependency matrix and dynamic set-covering based fault diagnosis method in this paper.Firstly,we establish the dependency matrix between the fault current information and the faulty sections according to the topology of the power distribution network.Then,the hidden Markov model is introduced to describe the state sequence of each section over time.Based on the set of fault current information reported by the feeder terminal unit,we establish a dynamic set-covering based fault diagnosis model and use Viterbi Decoding to obtain the state sequence of each section that satisfies the covering constraints and realize the online faulty section localization in power distribution networks.Finally,simulation results validate the accuracy and stability of the proposed dependency matrix and dynamic set-covering based fault diagnosis method.
作者 夏炳森 李翠 林文钦 王威丽 XIA Bingsen;LI Cui;LIN Wenqing;WANG Weili(Economic Technology Research Institute,State Grid Fujian Electric Power Company,Fuzhou 350012,P.R.China;School of Communications and Information Engineering,Chongqing University of Posts and Telecommunications,Chongqing 400065,P.R.China)
出处 《重庆邮电大学学报(自然科学版)》 CSCD 北大核心 2022年第3期535-542,共8页 Journal of Chongqing University of Posts and Telecommunications(Natural Science Edition)
基金 国家自然科学基金(61571073)。
关键词 配电网 故障诊断 动态集合覆盖 隐马尔可夫模型 power distribution networks fault diagnosis dynamic set-covering hidden Markov model
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