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基于改进K聚类多判据融合的柔性直流配电网单极故障选线

陈新岗 曾慧敏 马志鹏 张知先 李松 张文轩

电力系统保护与控制2025,Vol.53Issue(9):49-59,11.
电力系统保护与控制2025,Vol.53Issue(9):49-59,11.DOI:10.19783/j.cnki.pspc.240551

基于改进K聚类多判据融合的柔性直流配电网单极故障选线

Single-pole fault line selection in flexible DC distribution networks based on improved K-means multi-criterion fusion

陈新岗 1曾慧敏 2马志鹏 2张知先 2李松 3张文轩2

作者信息

  • 1. 重庆理工大学电气与电子工程学院,重庆 400054||重庆市能源互联网工程技术研究中心,重庆 400054
  • 2. 重庆理工大学电气与电子工程学院,重庆 400054
  • 3. 重庆理工大学机械工程学院,重庆 400054
  • 折叠

摘要

Abstract

In flexible DC distribution networks with low-current grounding mode,single-pole-to-ground faults exhibit weak fault characteristics,making fault identification challenging.To enhance fault detection capability,this paper proposes a single-pole fault line selection scheme for flexible DC distribution networks based on K-means++multi-criterion fusion.First,modulus decomposition of electrical quantities during line faults is carried out,and the characteristics of zero-mode current,zero-mode voltage and zero-mode power for both normal and faulty lines are obtained.Then,according to the differences in the Spearman correlation of zero-mode current,the cosine of the angle between zero-mode current and voltage,and the absolute value of the zero-mode power integral,three fault line selection criteria are constructed.Finally,the K-means++algorithm is used to analyze the results of the three criteria for each line,enabling accurate identification of the fault line.Simulations in PSCAD show that the proposed method has strong resistance to transition resistance,noise interference,and communication delay,significantly improving the accuracy and reliability of single-pole-to-ground fault line selection.

关键词

柔性直流配电网/单极接地故障/K-means++/故障选线

Key words

flexible DC distribution network/single-pole-to-ground fault/K-means++/fault line selection

引用本文复制引用

陈新岗,曾慧敏,马志鹏,张知先,李松,张文轩..基于改进K聚类多判据融合的柔性直流配电网单极故障选线[J].电力系统保护与控制,2025,53(9):49-59,11.

基金项目

重庆市自然科学基金项目资助(CSTB2023NSCQ-MSX0337) (CSTB2023NSCQ-MSX0337)

重庆市教育委员会科学技术研究项目资助(KJZD-K202101103) (KJZD-K202101103)

重庆理工大学研究生教育高质量发展项目资助(gzlcx20233148)This work is supported by the Natural Science Foundation of Chongqing(No.CSTB2023NSCQ-MSX0337). (gzlcx20233148)

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