Distributed Model Predictive Control Employing Trajectory Sensitivities for Cascading Failures

The paper introduces a new distributed model predictive control (DMPC) method employing trajectory sensitivities for the cascading failures of the complex power system. Firstly, it predictes the trajectories of the system by trajectory sensitivities. Secondly, it uses the MPC to find out the optimiz...

Ausführliche Beschreibung

Gespeichert in:

Bibliographische Detailangaben
Hauptverfasser:	Xiaona Wang, Xusheng Wu, Xiaoguang Yang, Xiwei Zai, Chan Li, Youping Fan
Format:	Tagungsbericht
Sprache:	eng
Schlagworte:	Control systems Optimization methods Power system control Power system faults Power system modeling Power system protection Power systems Predictive control Predictive models Trajectory
Online-Zugang:	Volltext bestellen
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

container_end_page	4
container_issue
container_start_page	1
container_title
container_volume
creator	Xiaona Wang Xusheng Wu Xiaoguang Yang Xiwei Zai Chan Li Youping Fan
description	The paper introduces a new distributed model predictive control (DMPC) method employing trajectory sensitivities for the cascading failures of the complex power system. Firstly, it predictes the trajectories of the system by trajectory sensitivities. Secondly, it uses the MPC to find out the optimization control method, and activates it to eliminate the cascading failures of the large-scale power system. It simplifys the DMPC employing the trajectory sensitivities optimization control algorithms.
doi_str_mv	10.1109/APPEEC.2009.4918288
format	Conference Proceeding
fullrecord	<record><control><sourceid>ieee_6IE</sourceid><recordid>TN_cdi_ieee_primary_4918288</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><ieee_id>4918288</ieee_id><sourcerecordid>4918288</sourcerecordid><originalsourceid>FETCH-LOGICAL-i90t-7d76542e32d2f6788e612d38db37d323dc1bcfbd9f533200e5db9bad54bbafac3</originalsourceid><addsrcrecordid>eNpFUF1LAzEQjGjBtvYX9CV_4Gq-7pI8lvOqQsWCfbYkt3uScu2V5Cr033tiwWWHYWFmYJaQOWcLzpl9XG42VVUuBGN2oSw3wpgbMuFKqGGNtrf_R8HuyFjwXGfKSDsik8FkLJMFt_dkltKeDaNyoZUek8-nkPoY_LlHoG8dYEs3ESHUffhGWnbHPnYtrQ6ntruE4xfdRrfHuu_ihX7gMYVBNgATbbpIS5dqB7-ylQvtOWJ6IKPGtQlnV56S7arali_Z-v35tVyus2BZn2nQRa4ESgGiKbQxWHAB0oCXGqSQUHNfNx5sk0s5tMEcvPUOcuW9a1wtp2T-FxsQcXeK4eDiZXf9k_wB4_Ba1Q</addsrcrecordid><sourcetype>Publisher</sourcetype><iscdi>true</iscdi><recordtype>conference_proceeding</recordtype></control><display><type>conference_proceeding</type><title>Distributed Model Predictive Control Employing Trajectory Sensitivities for Cascading Failures</title><source>IEEE Electronic Library (IEL) Conference Proceedings</source><creator>Xiaona Wang ; Xusheng Wu ; Xiaoguang Yang ; Xiwei Zai ; Chan Li ; Youping Fan</creator><creatorcontrib>Xiaona Wang ; Xusheng Wu ; Xiaoguang Yang ; Xiwei Zai ; Chan Li ; Youping Fan</creatorcontrib><description>The paper introduces a new distributed model predictive control (DMPC) method employing trajectory sensitivities for the cascading failures of the complex power system. Firstly, it predictes the trajectories of the system by trajectory sensitivities. Secondly, it uses the MPC to find out the optimization control method, and activates it to eliminate the cascading failures of the large-scale power system. It simplifys the DMPC employing the trajectory sensitivities optimization control algorithms.</description><identifier>ISSN: 2157-4839</identifier><identifier>ISBN: 1424424860</identifier><identifier>ISBN: 9781424424863</identifier><identifier>EISBN: 1424424879</identifier><identifier>EISBN: 9781424424870</identifier><identifier>DOI: 10.1109/APPEEC.2009.4918288</identifier><identifier>LCCN: 2008903619</identifier><language>eng</language><publisher>IEEE</publisher><subject>Control systems ; Optimization methods ; Power system control ; Power system faults ; Power system modeling ; Power system protection ; Power systems ; Predictive control ; Predictive models ; Trajectory</subject><ispartof>2009 Asia-Pacific Power and Energy Engineering Conference, 2009, p.1-4</ispartof><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/4918288$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>309,310,780,784,789,790,2058,27925,54920</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/4918288$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Xiaona Wang</creatorcontrib><creatorcontrib>Xusheng Wu</creatorcontrib><creatorcontrib>Xiaoguang Yang</creatorcontrib><creatorcontrib>Xiwei Zai</creatorcontrib><creatorcontrib>Chan Li</creatorcontrib><creatorcontrib>Youping Fan</creatorcontrib><title>Distributed Model Predictive Control Employing Trajectory Sensitivities for Cascading Failures</title><title>2009 Asia-Pacific Power and Energy Engineering Conference</title><addtitle>APPEEC</addtitle><description>The paper introduces a new distributed model predictive control (DMPC) method employing trajectory sensitivities for the cascading failures of the complex power system. Firstly, it predictes the trajectories of the system by trajectory sensitivities. Secondly, it uses the MPC to find out the optimization control method, and activates it to eliminate the cascading failures of the large-scale power system. It simplifys the DMPC employing the trajectory sensitivities optimization control algorithms.</description><subject>Control systems</subject><subject>Optimization methods</subject><subject>Power system control</subject><subject>Power system faults</subject><subject>Power system modeling</subject><subject>Power system protection</subject><subject>Power systems</subject><subject>Predictive control</subject><subject>Predictive models</subject><subject>Trajectory</subject><issn>2157-4839</issn><isbn>1424424860</isbn><isbn>9781424424863</isbn><isbn>1424424879</isbn><isbn>9781424424870</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2009</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNpFUF1LAzEQjGjBtvYX9CV_4Gq-7pI8lvOqQsWCfbYkt3uScu2V5Cr033tiwWWHYWFmYJaQOWcLzpl9XG42VVUuBGN2oSw3wpgbMuFKqGGNtrf_R8HuyFjwXGfKSDsik8FkLJMFt_dkltKeDaNyoZUek8-nkPoY_LlHoG8dYEs3ESHUffhGWnbHPnYtrQ6ntruE4xfdRrfHuu_ihX7gMYVBNgATbbpIS5dqB7-ylQvtOWJ6IKPGtQlnV56S7arali_Z-v35tVyus2BZn2nQRa4ESgGiKbQxWHAB0oCXGqSQUHNfNx5sk0s5tMEcvPUOcuW9a1wtp2T-FxsQcXeK4eDiZXf9k_wB4_Ba1Q</recordid><startdate>200903</startdate><enddate>200903</enddate><creator>Xiaona Wang</creator><creator>Xusheng Wu</creator><creator>Xiaoguang Yang</creator><creator>Xiwei Zai</creator><creator>Chan Li</creator><creator>Youping Fan</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>200903</creationdate><title>Distributed Model Predictive Control Employing Trajectory Sensitivities for Cascading Failures</title><author>Xiaona Wang ; Xusheng Wu ; Xiaoguang Yang ; Xiwei Zai ; Chan Li ; Youping Fan</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i90t-7d76542e32d2f6788e612d38db37d323dc1bcfbd9f533200e5db9bad54bbafac3</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2009</creationdate><topic>Control systems</topic><topic>Optimization methods</topic><topic>Power system control</topic><topic>Power system faults</topic><topic>Power system modeling</topic><topic>Power system protection</topic><topic>Power systems</topic><topic>Predictive control</topic><topic>Predictive models</topic><topic>Trajectory</topic><toplevel>online_resources</toplevel><creatorcontrib>Xiaona Wang</creatorcontrib><creatorcontrib>Xusheng Wu</creatorcontrib><creatorcontrib>Xiaoguang Yang</creatorcontrib><creatorcontrib>Xiwei Zai</creatorcontrib><creatorcontrib>Chan Li</creatorcontrib><creatorcontrib>Youping Fan</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Electronic Library (IEL)</collection><collection>IEEE Proceedings Order Plans (POP All) 1998-Present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Xiaona Wang</au><au>Xusheng Wu</au><au>Xiaoguang Yang</au><au>Xiwei Zai</au><au>Chan Li</au><au>Youping Fan</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Distributed Model Predictive Control Employing Trajectory Sensitivities for Cascading Failures</atitle><btitle>2009 Asia-Pacific Power and Energy Engineering Conference</btitle><stitle>APPEEC</stitle><date>2009-03</date><risdate>2009</risdate><spage>1</spage><epage>4</epage><pages>1-4</pages><issn>2157-4839</issn><isbn>1424424860</isbn><isbn>9781424424863</isbn><eisbn>1424424879</eisbn><eisbn>9781424424870</eisbn><abstract>The paper introduces a new distributed model predictive control (DMPC) method employing trajectory sensitivities for the cascading failures of the complex power system. Firstly, it predictes the trajectories of the system by trajectory sensitivities. Secondly, it uses the MPC to find out the optimization control method, and activates it to eliminate the cascading failures of the large-scale power system. It simplifys the DMPC employing the trajectory sensitivities optimization control algorithms.</abstract><pub>IEEE</pub><doi>10.1109/APPEEC.2009.4918288</doi><tpages>4</tpages></addata></record>
fulltext	fulltext_linktorsrc
identifier	ISSN: 2157-4839
ispartof	2009 Asia-Pacific Power and Energy Engineering Conference, 2009, p.1-4
issn	2157-4839
language	eng
recordid	cdi_ieee_primary_4918288
source	IEEE Electronic Library (IEL) Conference Proceedings
subjects	Control systems Optimization methods Power system control Power system faults Power system modeling Power system protection Power systems Predictive control Predictive models Trajectory
title	Distributed Model Predictive Control Employing Trajectory Sensitivities for Cascading Failures
url	https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-06T19%3A14%3A26IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-ieee_6IE&rft_val_fmt=info:ofi/fmt:kev:mtx:book&rft.genre=proceeding&rft.atitle=Distributed%20Model%20Predictive%20Control%20Employing%20Trajectory%20Sensitivities%20for%20Cascading%20Failures&rft.btitle=2009%20Asia-Pacific%20Power%20and%20Energy%20Engineering%20Conference&rft.au=Xiaona%20Wang&rft.date=2009-03&rft.spage=1&rft.epage=4&rft.pages=1-4&rft.issn=2157-4839&rft.isbn=1424424860&rft.isbn_list=9781424424863&rft_id=info:doi/10.1109/APPEEC.2009.4918288&rft_dat=%3Cieee_6IE%3E4918288%3C/ieee_6IE%3E%3Curl%3E%3C/url%3E&rft.eisbn=1424424879&rft.eisbn_list=9781424424870&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_id=info:pmid/&rft_ieee_id=4918288&rfr_iscdi=true