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Research On Accurate Fault Location Of Hybrid Multi-T Branches Line Based On Multi-End Data Fusion

Posted on:2020-10-17Degree:MasterType:Thesis
Country:ChinaCandidate:H X JiaoFull Text:PDF
GTID:2492306740971119Subject:Electrical engineering
Abstract/Summary:PDF Full Text Request
Unexpected power interruptions are often caused by faults in the transmission line.After the fault occurring,the relay protection device acts as soon as possible to avoid further development of the fault which would cause a larger accident.For safety and stability,maintenance personnel need to find the fault location in time,find out the cause of the fault,eliminate the hidden trouble,and finally restore the power supply.Traveling wave fault location technology has been widely used in the power systems in China,with the advantages of accuracy and efficiency,but is also affected by factors such as line length.However,as the urbanization process accelerates,the single overhead transmission line has gradually developed to the hybrid form of cable-overhead line.The wave impedances of overhead line and cable are different,which increases the difficulty of fault traveling wave recognition.In addition,there are lots of T branches in the distribution network,which causes the traveling wave to be deflected and reflected.And it affects the accuracy of ranging of traveling wave fault location technology.Therefore,in the hybrid multi-T branches transmission line,the traveling wave single-end method and the double-end method cannot be directly used for fault location.In order to overcome the fault location problem of traveling wave hybrid multi-T branches line in the distribution network,this paper applies the traveling wave method to the precise location of the line fault based on the principle of multi-end data fusion,and develops the prototype of the fault location system,which has a good performance.Single-phase ground faults are the most common in power systems,so this paper studies single-phase ground fault location methods based on multi-end data fusion.In order to determine the fault section,this paper first analyzes the characteristics of single-phase ground fault,and proposes to use fault transient information and particle swarm clustering algorithm to determine the fault section.Among them,the fault transient information can be divided into high frequency and low frequency information,and the combination of the two can improve the fault location accuracy.For the small current ground fault,this paper uses the particle swarm clustering method to analyze and calculate lots of fault information to obtain the fault area.The simulation experiments are carried out in the simulation software,which proves the practicability and effectiveness of the proposed method.Facing the increasing situation of hybrid lines in distribution network and the difficulty of fault location caused by multi-T branches lines,this paper proposes a fault location method based on traveling wave method for hybrid multi-T branches lines.Firstly,the specific process of fault location is introduced,including preprocessing of data,calculation of the time of the main virtual node,selection of the reference node,etc,and finally forming a closed loop.In order to verify the correctness of the proposed method,a 10 k V neutral point arc-suppression coil grounding distribution system is established in the Simulink.The simulation results show that the method is reliable and effective.Based on the above research,this paper will also develop a prototype of hybrid multi-T branches line fault location system,and introduce the prototype development from the aspects of system principle,system composition,hardware and software design.After testing the hybrid multi-T branches line fault location system,the application test is carried out in the actual distribution network.The application case shows that the prototype developed in this paper has reached the engineering application requirements and lays a good foundation for further promotion and use in the future.
Keywords/Search Tags:Hybrid lines, Traveling wave method, Multi-end data, Particle swarm clustering, Fault location
PDF Full Text Request
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