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Research on fault location algorithm of TPSS based on PSOA
It is extremely important to research traction power supply system (TPSS) protection technology in order to ensure the safe operation of urban rail transit. A TPSS includes rails, return cables, rail potential limiting devices, one-way conducting devices, drainage cabinets, ballast beds, and tunnel...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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PeerJ Inc.
2023
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10280258/ https://www.ncbi.nlm.nih.gov/pubmed/37346653 http://dx.doi.org/10.7717/peerj-cs.1213 |
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author | Jia, Yunqian |
author_facet | Jia, Yunqian |
author_sort | Jia, Yunqian |
collection | PubMed |
description | It is extremely important to research traction power supply system (TPSS) protection technology in order to ensure the safe operation of urban rail transit. A TPSS includes rails, return cables, rail potential limiting devices, one-way conducting devices, drainage cabinets, ballast beds, and tunnel structural reinforcements. In urban rail transit, on the basis of the dynamic characteristics of the TPSS, a fault location algorithm based on particle swarm optimization algorithm (PSOA) is developed. An evaluation of multi-point monitoring data is proposed based on fuzzy processing of the average value of polarization potential forward deviation and multi-attribute decision-making. Monitoring points and standard comparison threshold values are determined by the distribution law of stray currents. In conjunction with the actual project, the model is trained using field measured data. Based on the results, TPSSOA is able to achieve optimal discharge current control, reduce network losses and improve power quality. Moreover, the reconstruction results demonstrate the high usability of the proposed method, which will provide guidance to design the TPSS in the future. |
format | Online Article Text |
id | pubmed-10280258 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | PeerJ Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-102802582023-06-21 Research on fault location algorithm of TPSS based on PSOA Jia, Yunqian PeerJ Comput Sci Algorithms and Analysis of Algorithms It is extremely important to research traction power supply system (TPSS) protection technology in order to ensure the safe operation of urban rail transit. A TPSS includes rails, return cables, rail potential limiting devices, one-way conducting devices, drainage cabinets, ballast beds, and tunnel structural reinforcements. In urban rail transit, on the basis of the dynamic characteristics of the TPSS, a fault location algorithm based on particle swarm optimization algorithm (PSOA) is developed. An evaluation of multi-point monitoring data is proposed based on fuzzy processing of the average value of polarization potential forward deviation and multi-attribute decision-making. Monitoring points and standard comparison threshold values are determined by the distribution law of stray currents. In conjunction with the actual project, the model is trained using field measured data. Based on the results, TPSSOA is able to achieve optimal discharge current control, reduce network losses and improve power quality. Moreover, the reconstruction results demonstrate the high usability of the proposed method, which will provide guidance to design the TPSS in the future. PeerJ Inc. 2023-03-10 /pmc/articles/PMC10280258/ /pubmed/37346653 http://dx.doi.org/10.7717/peerj-cs.1213 Text en © 2023 Jia https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ Computer Science) and either DOI or URL of the article must be cited. |
spellingShingle | Algorithms and Analysis of Algorithms Jia, Yunqian Research on fault location algorithm of TPSS based on PSOA |
title | Research on fault location algorithm of TPSS based on PSOA |
title_full | Research on fault location algorithm of TPSS based on PSOA |
title_fullStr | Research on fault location algorithm of TPSS based on PSOA |
title_full_unstemmed | Research on fault location algorithm of TPSS based on PSOA |
title_short | Research on fault location algorithm of TPSS based on PSOA |
title_sort | research on fault location algorithm of tpss based on psoa |
topic | Algorithms and Analysis of Algorithms |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10280258/ https://www.ncbi.nlm.nih.gov/pubmed/37346653 http://dx.doi.org/10.7717/peerj-cs.1213 |
work_keys_str_mv | AT jiayunqian researchonfaultlocationalgorithmoftpssbasedonpsoa |