Distribution Network Topology Identification Considering Nonsynchronous Multi-Prosumer Data Measurement

Accurate topology is the basis of fine management and safe operation of distribution network. With the development of distributed generation, more and more users participate in the distribution network, which makes the flow direction of distribution network more complex and brings some difficulties...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:IEEE access 2022, Vol.10, p.72785-72793
Hauptverfasser: Zhang, Lizong, Zhang, Fengming, Li, Xiaolei, Wang, Chunlei, Chen, Taotao, Wang, Qingqing, Hu, Huilin
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page 72793
container_issue
container_start_page 72785
container_title IEEE access
container_volume 10
creator Zhang, Lizong
Zhang, Fengming
Li, Xiaolei
Wang, Chunlei
Chen, Taotao
Wang, Qingqing
Hu, Huilin
description Accurate topology is the basis of fine management and safe operation of distribution network. With the development of distributed generation, more and more users participate in the distribution network, which makes the flow direction of distribution network more complex and brings some difficulties to the topology identification of distribution network. The existing distribution network topology identification methods lack of multi period measurement data, and the utilization rate of multi-user data is low, which leads to the low accuracy of distribution network topology identification. To solve this problem, a distribution network topology identification method based on multi-user fusion data is proposed. Firstly, the existing distribution network measurement system is analyzed, and the data and characteristics that can be collected in the actual project are obtained. Then, according to the characteristics of different data sampling frequency and accuracy, multi-user data fusion is carried out, and a PMU based multi-user data time scale alignment method and a pseudo measurement generation method based on linear extrapolation are proposed. Finally, an optimization model of distribution network topology identification based on multi-user and multi period fusion data is proposed. By minimizing the error between the measured value and the estimated value in several time periods, the model realizes the identification of distribution network topology. Simulation results show that the method is correct and effective.
doi_str_mv 10.1109/ACCESS.2021.3052993
format Article
fullrecord <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_journals_2689806517</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><ieee_id>9328870</ieee_id><doaj_id>oai_doaj_org_article_6cf0b53ff790419ea8d6306bf9a197fb</doaj_id><sourcerecordid>2689806517</sourcerecordid><originalsourceid>FETCH-LOGICAL-c408t-2826e084ab7ce193157da78acb941f0add45a8b9c687a53c1dbacadb1761a5363</originalsourceid><addsrcrecordid>eNpNUclO5DAQjUaMNAj4Ai6ROKex48TLEQVmaKlZJJizVd4a93THPbYj1H-PIQhRl1rfqyq9qjrHaIExEpdXw3Dz9LRoUYsXBPWtEORHddxiKhrSE3r0Lf5VnaW0QcV4KfXsuFpf-5SjV1P2YazvbX4N8V_9HPZhG9aHemnsmL3zGj76QxiTNzb6cV3fl_gw6pcYxjCl-m7aZt88xpCmnY31NWSo7yykKdpd4TitfjrYJnv26U-qv79vnofbZvXwZzlcrRrdIZ6blrfUIt6BYtpiQXDPDDAOWokOOwTGdD1wJTTlDHqisVGgwSjMKC45JSfVcuY1ATZyH_0O4kEG8PKjEOJaQsxeb62k2iHVE-eYQB0WFrihBFHlBGDBnCpcFzPXPob_k01ZbsIUx3K-bCkXHNEeszJF5ildfk_Ruq-tGMl3geQskHwXSH4KVFDnM8pba78QgrScM0TeAJhSjtA</addsrcrecordid><sourcetype>Open Website</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2689806517</pqid></control><display><type>article</type><title>Distribution Network Topology Identification Considering Nonsynchronous Multi-Prosumer Data Measurement</title><source>IEEE Open Access Journals</source><source>DOAJ Directory of Open Access Journals</source><source>Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals</source><creator>Zhang, Lizong ; Zhang, Fengming ; Li, Xiaolei ; Wang, Chunlei ; Chen, Taotao ; Wang, Qingqing ; Hu, Huilin</creator><creatorcontrib>Zhang, Lizong ; Zhang, Fengming ; Li, Xiaolei ; Wang, Chunlei ; Chen, Taotao ; Wang, Qingqing ; Hu, Huilin</creatorcontrib><description>Accurate topology is the basis of fine management and safe operation of distribution network. With the development of distributed generation, more and more users participate in the distribution network, which makes the flow direction of distribution network more complex and brings some difficulties to the topology identification of distribution network. The existing distribution network topology identification methods lack of multi period measurement data, and the utilization rate of multi-user data is low, which leads to the low accuracy of distribution network topology identification. To solve this problem, a distribution network topology identification method based on multi-user fusion data is proposed. Firstly, the existing distribution network measurement system is analyzed, and the data and characteristics that can be collected in the actual project are obtained. Then, according to the characteristics of different data sampling frequency and accuracy, multi-user data fusion is carried out, and a PMU based multi-user data time scale alignment method and a pseudo measurement generation method based on linear extrapolation are proposed. Finally, an optimization model of distribution network topology identification based on multi-user and multi period fusion data is proposed. By minimizing the error between the measured value and the estimated value in several time periods, the model realizes the identification of distribution network topology. Simulation results show that the method is correct and effective.</description><identifier>ISSN: 2169-3536</identifier><identifier>EISSN: 2169-3536</identifier><identifier>DOI: 10.1109/ACCESS.2021.3052993</identifier><identifier>CODEN: IAECCG</identifier><language>eng</language><publisher>Piscataway: IEEE</publisher><subject>Data integration ; Data sampling ; Distributed generation ; Distribution network ; Distribution networks ; Error analysis ; Identification ; Identification methods ; multi-prosumer data ; Network topologies ; Network topology ; nonsynchronous measurement ; Optimization models ; Phasor measurement units ; Power measurement ; prosumer group ; Time measurement ; Topology ; topology identification ; Voltage measurement</subject><ispartof>IEEE access, 2022, Vol.10, p.72785-72793</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2022</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c408t-2826e084ab7ce193157da78acb941f0add45a8b9c687a53c1dbacadb1761a5363</citedby><cites>FETCH-LOGICAL-c408t-2826e084ab7ce193157da78acb941f0add45a8b9c687a53c1dbacadb1761a5363</cites><orcidid>0000-0002-8013-4636 ; 0000-0003-0250-3712</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/9328870$$EHTML$$P50$$Gieee$$Hfree_for_read</linktohtml><link.rule.ids>314,780,784,864,2100,4022,27632,27922,27923,27924,54932</link.rule.ids></links><search><creatorcontrib>Zhang, Lizong</creatorcontrib><creatorcontrib>Zhang, Fengming</creatorcontrib><creatorcontrib>Li, Xiaolei</creatorcontrib><creatorcontrib>Wang, Chunlei</creatorcontrib><creatorcontrib>Chen, Taotao</creatorcontrib><creatorcontrib>Wang, Qingqing</creatorcontrib><creatorcontrib>Hu, Huilin</creatorcontrib><title>Distribution Network Topology Identification Considering Nonsynchronous Multi-Prosumer Data Measurement</title><title>IEEE access</title><addtitle>Access</addtitle><description>Accurate topology is the basis of fine management and safe operation of distribution network. With the development of distributed generation, more and more users participate in the distribution network, which makes the flow direction of distribution network more complex and brings some difficulties to the topology identification of distribution network. The existing distribution network topology identification methods lack of multi period measurement data, and the utilization rate of multi-user data is low, which leads to the low accuracy of distribution network topology identification. To solve this problem, a distribution network topology identification method based on multi-user fusion data is proposed. Firstly, the existing distribution network measurement system is analyzed, and the data and characteristics that can be collected in the actual project are obtained. Then, according to the characteristics of different data sampling frequency and accuracy, multi-user data fusion is carried out, and a PMU based multi-user data time scale alignment method and a pseudo measurement generation method based on linear extrapolation are proposed. Finally, an optimization model of distribution network topology identification based on multi-user and multi period fusion data is proposed. By minimizing the error between the measured value and the estimated value in several time periods, the model realizes the identification of distribution network topology. Simulation results show that the method is correct and effective.</description><subject>Data integration</subject><subject>Data sampling</subject><subject>Distributed generation</subject><subject>Distribution network</subject><subject>Distribution networks</subject><subject>Error analysis</subject><subject>Identification</subject><subject>Identification methods</subject><subject>multi-prosumer data</subject><subject>Network topologies</subject><subject>Network topology</subject><subject>nonsynchronous measurement</subject><subject>Optimization models</subject><subject>Phasor measurement units</subject><subject>Power measurement</subject><subject>prosumer group</subject><subject>Time measurement</subject><subject>Topology</subject><subject>topology identification</subject><subject>Voltage measurement</subject><issn>2169-3536</issn><issn>2169-3536</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><sourceid>ESBDL</sourceid><sourceid>RIE</sourceid><sourceid>DOA</sourceid><recordid>eNpNUclO5DAQjUaMNAj4Ai6ROKex48TLEQVmaKlZJJizVd4a93THPbYj1H-PIQhRl1rfqyq9qjrHaIExEpdXw3Dz9LRoUYsXBPWtEORHddxiKhrSE3r0Lf5VnaW0QcV4KfXsuFpf-5SjV1P2YazvbX4N8V_9HPZhG9aHemnsmL3zGj76QxiTNzb6cV3fl_gw6pcYxjCl-m7aZt88xpCmnY31NWSo7yykKdpd4TitfjrYJnv26U-qv79vnofbZvXwZzlcrRrdIZ6blrfUIt6BYtpiQXDPDDAOWokOOwTGdD1wJTTlDHqisVGgwSjMKC45JSfVcuY1ATZyH_0O4kEG8PKjEOJaQsxeb62k2iHVE-eYQB0WFrihBFHlBGDBnCpcFzPXPob_k01ZbsIUx3K-bCkXHNEeszJF5ildfk_Ruq-tGMl3geQskHwXSH4KVFDnM8pba78QgrScM0TeAJhSjtA</recordid><startdate>2022</startdate><enddate>2022</enddate><creator>Zhang, Lizong</creator><creator>Zhang, Fengming</creator><creator>Li, Xiaolei</creator><creator>Wang, Chunlei</creator><creator>Chen, Taotao</creator><creator>Wang, Qingqing</creator><creator>Hu, Huilin</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. (IEEE)</general><scope>97E</scope><scope>ESBDL</scope><scope>RIA</scope><scope>RIE</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>7SP</scope><scope>7SR</scope><scope>8BQ</scope><scope>8FD</scope><scope>JG9</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><scope>DOA</scope><orcidid>https://orcid.org/0000-0002-8013-4636</orcidid><orcidid>https://orcid.org/0000-0003-0250-3712</orcidid></search><sort><creationdate>2022</creationdate><title>Distribution Network Topology Identification Considering Nonsynchronous Multi-Prosumer Data Measurement</title><author>Zhang, Lizong ; Zhang, Fengming ; Li, Xiaolei ; Wang, Chunlei ; Chen, Taotao ; Wang, Qingqing ; Hu, Huilin</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c408t-2826e084ab7ce193157da78acb941f0add45a8b9c687a53c1dbacadb1761a5363</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Data integration</topic><topic>Data sampling</topic><topic>Distributed generation</topic><topic>Distribution network</topic><topic>Distribution networks</topic><topic>Error analysis</topic><topic>Identification</topic><topic>Identification methods</topic><topic>multi-prosumer data</topic><topic>Network topologies</topic><topic>Network topology</topic><topic>nonsynchronous measurement</topic><topic>Optimization models</topic><topic>Phasor measurement units</topic><topic>Power measurement</topic><topic>prosumer group</topic><topic>Time measurement</topic><topic>Topology</topic><topic>topology identification</topic><topic>Voltage measurement</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Zhang, Lizong</creatorcontrib><creatorcontrib>Zhang, Fengming</creatorcontrib><creatorcontrib>Li, Xiaolei</creatorcontrib><creatorcontrib>Wang, Chunlei</creatorcontrib><creatorcontrib>Chen, Taotao</creatorcontrib><creatorcontrib>Wang, Qingqing</creatorcontrib><creatorcontrib>Hu, Huilin</creatorcontrib><collection>IEEE All-Society Periodicals Package (ASPP) 2005-present</collection><collection>IEEE Open Access Journals</collection><collection>IEEE All-Society Periodicals Package (ASPP) 1998-Present</collection><collection>IEEE Electronic Library (IEL)</collection><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Electronics &amp; Communications Abstracts</collection><collection>Engineered Materials Abstracts</collection><collection>METADEX</collection><collection>Technology Research Database</collection><collection>Materials Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts – Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>IEEE access</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Zhang, Lizong</au><au>Zhang, Fengming</au><au>Li, Xiaolei</au><au>Wang, Chunlei</au><au>Chen, Taotao</au><au>Wang, Qingqing</au><au>Hu, Huilin</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Distribution Network Topology Identification Considering Nonsynchronous Multi-Prosumer Data Measurement</atitle><jtitle>IEEE access</jtitle><stitle>Access</stitle><date>2022</date><risdate>2022</risdate><volume>10</volume><spage>72785</spage><epage>72793</epage><pages>72785-72793</pages><issn>2169-3536</issn><eissn>2169-3536</eissn><coden>IAECCG</coden><abstract>Accurate topology is the basis of fine management and safe operation of distribution network. With the development of distributed generation, more and more users participate in the distribution network, which makes the flow direction of distribution network more complex and brings some difficulties to the topology identification of distribution network. The existing distribution network topology identification methods lack of multi period measurement data, and the utilization rate of multi-user data is low, which leads to the low accuracy of distribution network topology identification. To solve this problem, a distribution network topology identification method based on multi-user fusion data is proposed. Firstly, the existing distribution network measurement system is analyzed, and the data and characteristics that can be collected in the actual project are obtained. Then, according to the characteristics of different data sampling frequency and accuracy, multi-user data fusion is carried out, and a PMU based multi-user data time scale alignment method and a pseudo measurement generation method based on linear extrapolation are proposed. Finally, an optimization model of distribution network topology identification based on multi-user and multi period fusion data is proposed. By minimizing the error between the measured value and the estimated value in several time periods, the model realizes the identification of distribution network topology. Simulation results show that the method is correct and effective.</abstract><cop>Piscataway</cop><pub>IEEE</pub><doi>10.1109/ACCESS.2021.3052993</doi><tpages>9</tpages><orcidid>https://orcid.org/0000-0002-8013-4636</orcidid><orcidid>https://orcid.org/0000-0003-0250-3712</orcidid><oa>free_for_read</oa></addata></record>
fulltext fulltext
identifier ISSN: 2169-3536
ispartof IEEE access, 2022, Vol.10, p.72785-72793
issn 2169-3536
2169-3536
language eng
recordid cdi_proquest_journals_2689806517
source IEEE Open Access Journals; DOAJ Directory of Open Access Journals; Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals
subjects Data integration
Data sampling
Distributed generation
Distribution network
Distribution networks
Error analysis
Identification
Identification methods
multi-prosumer data
Network topologies
Network topology
nonsynchronous measurement
Optimization models
Phasor measurement units
Power measurement
prosumer group
Time measurement
Topology
topology identification
Voltage measurement
title Distribution Network Topology Identification Considering Nonsynchronous Multi-Prosumer Data Measurement
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-12T14%3A38%3A36IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Distribution%20Network%20Topology%20Identification%20Considering%20Nonsynchronous%20Multi-Prosumer%20Data%20Measurement&rft.jtitle=IEEE%20access&rft.au=Zhang,%20Lizong&rft.date=2022&rft.volume=10&rft.spage=72785&rft.epage=72793&rft.pages=72785-72793&rft.issn=2169-3536&rft.eissn=2169-3536&rft.coden=IAECCG&rft_id=info:doi/10.1109/ACCESS.2021.3052993&rft_dat=%3Cproquest_cross%3E2689806517%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2689806517&rft_id=info:pmid/&rft_ieee_id=9328870&rft_doaj_id=oai_doaj_org_article_6cf0b53ff790419ea8d6306bf9a197fb&rfr_iscdi=true