文章摘要
基于特征选择与TCED的UHVDC输电线路故障判定方法
Fault Diagnosis Method of Ultra-high Voltage Direct Current TransmissionSystem Based on Mother Wavelet Selection and Matching and Transient Current Energy Difference
投稿时间:2019-12-27  修订日期:2020-02-23
DOI:
中文关键词: 母小波选择匹配  暂态电流能量差  故障诊断  特高压多端直流输电  PSCAD/EMTDC
英文关键词: Wavelet transform  Transient current energy difference  Fault diagnosis  UHV multi terminal DC transmission  PSCAD / EMTDC
基金项目:本论文由以下项目资助:国家重点研发计划资助项目(2017YFB0902800)
作者单位E-mail
丁津津 国网安徽省电力有限公司电力科学研究院 jslcnt7000@163.com 
汤汉松 江苏凌创电气自动化股份有限公司  
高博 国网安徽省电力有限公司电力科学研究院  
张峰 国网安徽省电力有限公司电力科学研究院  
李远松 国网安徽省电力有限公司电力科学研究院  
孙辉 国网安徽省电力有限公司电力科学研究院  
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中文摘要:
      针对特高压多端直流输电系统存在的故障范围广、保护动作易误动等问题,提出了基于母小波选择匹配与暂态电流能量差的特高压多端直流系统故障诊断方法。首先,采用离散小波变换对暂态故障电流进行特征分析,并基于皮尔逊积矩相关系数的母小波选择进行故障匹配。然后,利用故障两侧电流能量差的特性判别故障方向,通过各换流站故障方向信息确定故障区域。最后,建立了四端特高压直流输电系统的PSCAD/EMTDC仿真模型,根据故障位置、电阻、距离等关键参数判断所提方法的性能。实验结果表明,所提方法能准确判识故障方向并进行故障诊断,在区分电力系统暂态扰动与直流故障方面是有效的,并且提高了故障诊断的准确率以及缩短了检测时间。
英文摘要:
      In view of the problems existing in ultra-high voltage multi terminal direct current (DC) transmission system, such as the wide fault range, the easy malfunction of protection actions, etc, a fault diagnosis method based on wavelet transform and transient current energy difference is proposed. Firstly, the wavelet transform is used to analyze the fault current, and a mother wavelet selection method based on the pearson product-moment correlation coefficient is proposed. Then, the fault direction is determined by the characteristics of the current energy difference between two sides of the fault, and then the fault area is determined by the fault direction information of each converter station. Finally, the PSCAD / EMTDC simulation model of four terminal ultra-high voltage (UHV) direct current transmission system is established, and the performance of the proposed method is judged according to the key parameters such as fault location, resistance and distance. The experimental results show that the proposed method can accurately identify the fault direction and carry out fault diagnosis. It is effective in distinguishing power system transient disturbance from DC fault, and improves the accuracy of fault diagnosis and shortens the detection time.
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