[1]陈 霄,居 荣.基于KNN算法的配电网单相接地故障选线研究[J].南京师范大学学报(工程技术版),2020,20(03):027-31.[doi:10.3969/j.issn.1672-1292.2020.03.005]
 School of NARI Electrical and Automation,Nanjing Normal University,Nanjing 00,et al.Research on Single Phase to Ground Fault Line Selection ofDistribution Network Based on KNN Algorithm[J].Journal of Nanjing Normal University(Engineering and Technology),2020,20(03):027-31.[doi:10.3969/j.issn.1672-1292.2020.03.005]
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基于KNN算法的配电网单相接地故障选线研究
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南京师范大学学报(工程技术版)[ISSN:1006-6977/CN:61-1281/TN]

卷:
20卷
期数:
2020年03期
页码:
027-31
栏目:
电气工程
出版日期:
2020-09-15

文章信息/Info

Title:
Research on Single Phase to Ground Fault Line Selection ofDistribution Network Based on KNN Algorithm
文章编号:
1672-1292(2020)03-0027-05
作者:
陈 霄居 荣
南京师范大学南瑞电气与自动化学院,江苏 南京 210023
Author(s):
School of NARI Electrical and AutomationNanjing Normal UniversityNanjing 210023China
Single phase to ground fault line selection is a difficult problem in the field of distribution network. In view of the poor applicability and low line selection accuracy of traditional fault line selection schemes that use a single criterion,this paper proposes a single phase to ground fault line selection method based on K-nearest-neighbor(KNN)algorithm combined with multi-source information fusion,which selects the fault feature quantity for the fault data processing and combines the KNN algorithm to select the fault line. The simulation study of the calculation example shows that the line selection method can obtain higher accuracy and significantly reduce the line selection time compared with the logistic regression algorithm(LoR)and the back propagation neural network algorithm(BP),and that it has a better application prospect.
关键词:
小波分析K近邻(K-nearest-neighborKNN)算法故障选线小电流接地系统
分类号:
TM773
DOI:
10.3969/j.issn.1672-1292.2020.03.005
文献标志码:
A
摘要:
小电流接地系统单相接地故障选线是配电网领域的一个难题,针对传统的采用单一判据的故障选线方案适用性差、选线精度低的问题,提出了一种基于K近邻(K-nearest-neighbor,KNN)算法的多源信息融合的单相接地故障选线方法,通过对故障数据处理选取故障特征量,结合KNN算法进行故障线路选线. 算例仿真研究表明,该选线方法与逻辑回归算法、BP神经网络算法相比,在获得较高的准确率的同时可缩短选线时间,具有较好的应用前景.
Abstract:
wavelet analysis,K-nearest-neighbor(KNN)algorithm,fault line selection,small current grounding system

参考文献/References:

[1] 张利. 中性点非有效接地系统单相接地故障定位方法的研究[D]. 北京:华北电力大学,2009.
[2]郭清滔,吴田. 小电流接地系统故障选线方法综述[J]. 电力系统保护与控制,2010,38(2):146-152.
[3]唐金锐,尹项根,张哲,等. 配电网故障自动定位技术研究综述[J]. 电力自动化设备,2013,33(5):7-13.
[4]刘东,张弘,王建春. 主动配电网技术研究现状综述[J]. 电力工程技术,2017,36(4):2-7,20.
[5]孟润泉,米建军. 五次谐波检测原理及其在矿井高压电网单相接地保护中的应用[J]. 工矿自动化,2004(3):10-13.
[6]牟龙华. 零序电流有功分量方向接地选线保护原理[J]. 电网技术,1999,23(9):60-62.
[7]舒凡娣,谢嘉晟,廖晓娇,等. 结合粒子群算法和穷举法的配电网故障诊断方法[J]. 智慧电力,2019,47(1):94-99.
[8]侯隽朗. 基于BP神经网络多判据小电流接地系统单相故障选线研究[D]. 太原:山西大学,2018.
[9]张海欣. 小电流接地系统单相接地故障多判据融合选线方法研究[D]. 秦皇岛:燕山大学,2019.
[10]林中鹏. 基于改进蜂群算法优化神经网络的小电流接地故障选线[D]. 青岛:山东科技大学,2018.
[11]WEI X X,YANG D C. An adaptive fault line selection method based on wavelet packet comprehensive singular value for small current grounding system[C]//2015 5th International Conference on Electric Utility Deregulation and Restructuring and Power Technologies. Changsha,China:IEEE,2015:1110-1114.
[12]杨慧敏,崔江,张卓然,等. 基于改进支持向量机的故障诊断方法[J]. 电工技术学报,2014,29(增刊1):164-169.

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备注/Memo

备注/Memo:
收稿日期:2020-05-16.
通讯作者:居荣,教授,研究方向:继电保护技术、新能源控制技术及微电网控制. E-mail:jurong@njnu.edu.cn
更新日期/Last Update: 2020-09-15