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基于电位系数矩阵的同塔双回直流输电线路故障选线方法

梁远升 王钢 李海锋 武霁阳

电力系统自动化Issue(3):97-102,6.
电力系统自动化Issue(3):97-102,6.DOI:10.7500/AEPS20150518009

基于电位系数矩阵的同塔双回直流输电线路故障选线方法

Fault Line Selection Scheme of Double HVDC Transmission Lines on Same Tower Based on Potential Coefficient Matrix

梁远升 1王钢 1李海锋 1武霁阳1

作者信息

  • 1. 华南理工大学电力学院,广东省广州市 510640
  • 折叠

摘要

Abstract

Centering on the fault analysis and fault line selection scheme for the double HVDC transmission lines on same tower,based on the electrostatic coupling theory,according to the detailed parameters of lines and tower,considering the effects of overhead ground wire and the filter capacitors,a calculation method of the potential coefficient matrix is presented for the double HVDC transmission lines.Then the interline electrostatic unbalanced coupling effect is transformed into mode voltage variation by the phase-mode transformation. Based on the mode voltage variation, considering the different characteristics of ground-mode and line-mode quantum,by the definition of mode voltage variation ratio,this paper proposes a fault feature quantitative analysis scheme of double HVDC transmission lines on same tower to eliminate the influence of transition resistance.Based on the fault case of each mode voltage variation characteristics,a fault line selection method of the double HVDC transmission lines on same tower is proposed.Finally,the PSCAD/EMTDC is used to construct the double HVDC transmission lines on same tower to verify the correctness of the proposed method through all-round fault simulations. The results show that the proposed method is capable of accurately selecting a variety of complicated fault types unaffected by the fault transition resistance.

关键词

同塔双回直流输电线路/故障分析/故障选线/电位系数矩阵

Key words

double HVDC transmission lines on same tower/fault analysis/fault selection/potential coefficient matrix

引用本文复制引用

梁远升,王钢,李海锋,武霁阳..基于电位系数矩阵的同塔双回直流输电线路故障选线方法[J].电力系统自动化,2016,(3):97-102,6.

基金项目

国家自然科学基金资助项目(51307065,51577072) (51307065,51577072)

中央高校基本科研业务费专项资金资助项目(2013ZZ028)。This work is supported by National Natural Science Foundation of China (No.51307065, No.51577072), and Fundamental Research Funds for the Central Universities (No.2013ZZ028) (2013ZZ028)

电力系统自动化

OA北大核心CSCDCSTPCD

1000-1026

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