The improved fault location method for flexible direct current grid based on clustering and iterating algorithm
Abstract The fault location method based on the natural frequency of the fault travelling wave has outstanding superiority in high‐voltage dc system, because of high operation speed, acceptable sampling rate, and so on. However, in flexible dc grid, the natural‐frequency characteristic is quite diff...
Main Authors: | , , , , , , , |
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Format: | Article |
Language: | English |
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Wiley
2021-11-01
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Series: | IET Renewable Power Generation |
Subjects: | |
Online Access: | https://doi.org/10.1049/rpg2.12246 |
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author | Chenyang Ma Bin Li Jiawei He Ye Li Qiyang Mao Shuai Wang Guanzheng Li Zepeng Hu |
author_facet | Chenyang Ma Bin Li Jiawei He Ye Li Qiyang Mao Shuai Wang Guanzheng Li Zepeng Hu |
author_sort | Chenyang Ma |
collection | DOAJ |
description | Abstract The fault location method based on the natural frequency of the fault travelling wave has outstanding superiority in high‐voltage dc system, because of high operation speed, acceptable sampling rate, and so on. However, in flexible dc grid, the natural‐frequency characteristic is quite different from that in conventional high‐voltage dc system, meaning the existing fault location method cannot be directly used. This paper analyses the distance‐frequency characteristics in different stages of fault period (from fault occurrence to fault isolation) in flexible dc grid, to find a suitable stage for fault location. On the basis of this, the improved fault location method based on clustering and iterating algorithms is proposed. Compared with the traditional method which directly uses the multiple signal classification algorithm to estimate the natural frequency for fault location, the proposed method can effectively eliminate the large error caused by signal dimension fluctuation and false spectrum peak of multiple signal classification algorithm. Finally, simulation cases are carried out to prove the feasibility and superiority of the proposed method. |
first_indexed | 2024-04-11T10:01:29Z |
format | Article |
id | doaj.art-22731fbad6ac46d9938d3ff60e1f3132 |
institution | Directory Open Access Journal |
issn | 1752-1416 1752-1424 |
language | English |
last_indexed | 2024-04-11T10:01:29Z |
publishDate | 2021-11-01 |
publisher | Wiley |
record_format | Article |
series | IET Renewable Power Generation |
spelling | doaj.art-22731fbad6ac46d9938d3ff60e1f31322022-12-22T04:30:25ZengWileyIET Renewable Power Generation1752-14161752-14242021-11-0115153577358710.1049/rpg2.12246The improved fault location method for flexible direct current grid based on clustering and iterating algorithmChenyang Ma0Bin Li1Jiawei He2Ye Li3Qiyang Mao4Shuai Wang5Guanzheng Li6Zepeng Hu7Key Laboratory of Smart Grid of Ministry of Education, Tianjin University Tianjin ChinaKey Laboratory of Smart Grid of Ministry of Education, Tianjin University Tianjin ChinaKey Laboratory of Smart Grid of Ministry of Education, Tianjin University Tianjin ChinaKey Laboratory of Smart Grid of Ministry of Education, Tianjin University Tianjin ChinaKey Laboratory of Smart Grid of Ministry of Education, Tianjin University Tianjin ChinaKey Laboratory of Smart Grid of Ministry of Education, Tianjin University Tianjin ChinaKey Laboratory of Smart Grid of Ministry of Education, Tianjin University Tianjin ChinaKey Laboratory of Smart Grid of Ministry of Education, Tianjin University Tianjin ChinaAbstract The fault location method based on the natural frequency of the fault travelling wave has outstanding superiority in high‐voltage dc system, because of high operation speed, acceptable sampling rate, and so on. However, in flexible dc grid, the natural‐frequency characteristic is quite different from that in conventional high‐voltage dc system, meaning the existing fault location method cannot be directly used. This paper analyses the distance‐frequency characteristics in different stages of fault period (from fault occurrence to fault isolation) in flexible dc grid, to find a suitable stage for fault location. On the basis of this, the improved fault location method based on clustering and iterating algorithms is proposed. Compared with the traditional method which directly uses the multiple signal classification algorithm to estimate the natural frequency for fault location, the proposed method can effectively eliminate the large error caused by signal dimension fluctuation and false spectrum peak of multiple signal classification algorithm. Finally, simulation cases are carried out to prove the feasibility and superiority of the proposed method.https://doi.org/10.1049/rpg2.12246Inspection and quality controlSignal processing and detectionInterpolation and function approximation (numerical analysis)Digital signal processingInterpolation and function approximation (numerical analysis) |
spellingShingle | Chenyang Ma Bin Li Jiawei He Ye Li Qiyang Mao Shuai Wang Guanzheng Li Zepeng Hu The improved fault location method for flexible direct current grid based on clustering and iterating algorithm IET Renewable Power Generation Inspection and quality control Signal processing and detection Interpolation and function approximation (numerical analysis) Digital signal processing Interpolation and function approximation (numerical analysis) |
title | The improved fault location method for flexible direct current grid based on clustering and iterating algorithm |
title_full | The improved fault location method for flexible direct current grid based on clustering and iterating algorithm |
title_fullStr | The improved fault location method for flexible direct current grid based on clustering and iterating algorithm |
title_full_unstemmed | The improved fault location method for flexible direct current grid based on clustering and iterating algorithm |
title_short | The improved fault location method for flexible direct current grid based on clustering and iterating algorithm |
title_sort | improved fault location method for flexible direct current grid based on clustering and iterating algorithm |
topic | Inspection and quality control Signal processing and detection Interpolation and function approximation (numerical analysis) Digital signal processing Interpolation and function approximation (numerical analysis) |
url | https://doi.org/10.1049/rpg2.12246 |
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