A Model Predictive Control Based Generator Start-Up Optimization Strategy for Restoration With Microgrids as Black-Start Resources
Microgrids (MGs) can operate in an islanded mode and serve as black-start resources for power system restoration (PSR). In this work, a model predictive control (MPC) based generator start-up optimization strategy for PSR is proposed utilizing MGs as black-start resources. First, the generator start...
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Veröffentlicht in: | IEEE transactions on power systems 2018-11, Vol.33 (6), p.7189-7203 |
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creator | Zhao, Yuxuan Lin, Zhenzhi Ding, Yi Liu, Yilu Sun, Lei Yan, Yong |
description | Microgrids (MGs) can operate in an islanded mode and serve as black-start resources for power system restoration (PSR). In this work, a model predictive control (MPC) based generator start-up optimization strategy for PSR is proposed utilizing MGs as black-start resources. First, the generator start-up sequence (GSUS) optimization is formulated as a mixed integer linear programming. Then, the uncertainties of MG black-start resources (MBSRs) are modeled by discretizing the probability distribution of the forecast errors, and representative scenarios for MBSRs extracted by formulating the probability mass transportation problem. Third, the generator start-up optimization strategy considering MBSRs is proposed utilizing the MPC technique, in which the optimization objective is to maximize the energy capability of the power systems and minimize the load curtailment of the MGs in each looking-ahead interval. Simulations on the IEEE 118 bus system with MGs and Zhejiang provincial power system in China verify that the proposed strategy for PSR can successfully restore the power system and effectively determine the optimal GSUS. |
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(ORNL), Oak Ridge, TN (United States)</creatorcontrib><description>Microgrids (MGs) can operate in an islanded mode and serve as black-start resources for power system restoration (PSR). In this work, a model predictive control (MPC) based generator start-up optimization strategy for PSR is proposed utilizing MGs as black-start resources. First, the generator start-up sequence (GSUS) optimization is formulated as a mixed integer linear programming. Then, the uncertainties of MG black-start resources (MBSRs) are modeled by discretizing the probability distribution of the forecast errors, and representative scenarios for MBSRs extracted by formulating the probability mass transportation problem. Third, the generator start-up optimization strategy considering MBSRs is proposed utilizing the MPC technique, in which the optimization objective is to maximize the energy capability of the power systems and minimize the load curtailment of the MGs in each looking-ahead interval. Simulations on the IEEE 118 bus system with MGs and Zhejiang provincial power system in China verify that the proposed strategy for PSR can successfully restore the power system and effectively determine the optimal GSUS.</description><identifier>ISSN: 0885-8950</identifier><identifier>EISSN: 1558-0679</identifier><identifier>DOI: 10.1109/TPWRS.2018.2849265</identifier><identifier>CODEN: ITPSEG</identifier><language>eng</language><publisher>New York: IEEE</publisher><subject>Black-start ; Computer simulation ; Electric power grids ; Energy conservation ; Integer programming ; Linear programming ; Mathematical models ; microgrid ; Microgrids ; Mixed integer ; model predictive control (MPC) ; Optimization ; Power generation ; Power system restoration ; power system restoration (PSR) ; Power system stability ; POWER TRANSMISSION AND DISTRIBUTION ; Predictive control ; probability mass transportation problem (PMTP) ; Restoration ; scenario reduction ; Strategy ; Transportation problem ; Uncertainty</subject><ispartof>IEEE transactions on power systems, 2018-11, Vol.33 (6), p.7189-7203</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2018</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c415t-d12909bf99d1c088fbd96caa601b2308608b3453e2f1612009b8ce701aa260573</citedby><cites>FETCH-LOGICAL-c415t-d12909bf99d1c088fbd96caa601b2308608b3453e2f1612009b8ce701aa260573</cites><orcidid>0000-0003-4389-5636 ; 0000-0003-2125-9604 ; 0000-0003-1451-1875 ; 0000-0001-7912-6332 ; 0000000179126332 ; 0000000321259604 ; 0000000314511875 ; 0000000343895636</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/8389207$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>230,315,782,786,798,887,27933,27934,54767</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/8389207$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc><backlink>$$Uhttps://www.osti.gov/servlets/purl/1523722$$D View this record in Osti.gov$$Hfree_for_read</backlink></links><search><creatorcontrib>Zhao, Yuxuan</creatorcontrib><creatorcontrib>Lin, Zhenzhi</creatorcontrib><creatorcontrib>Ding, Yi</creatorcontrib><creatorcontrib>Liu, Yilu</creatorcontrib><creatorcontrib>Sun, Lei</creatorcontrib><creatorcontrib>Yan, Yong</creatorcontrib><creatorcontrib>Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)</creatorcontrib><title>A Model Predictive Control Based Generator Start-Up Optimization Strategy for Restoration With Microgrids as Black-Start Resources</title><title>IEEE transactions on power systems</title><addtitle>TPWRS</addtitle><description>Microgrids (MGs) can operate in an islanded mode and serve as black-start resources for power system restoration (PSR). In this work, a model predictive control (MPC) based generator start-up optimization strategy for PSR is proposed utilizing MGs as black-start resources. First, the generator start-up sequence (GSUS) optimization is formulated as a mixed integer linear programming. Then, the uncertainties of MG black-start resources (MBSRs) are modeled by discretizing the probability distribution of the forecast errors, and representative scenarios for MBSRs extracted by formulating the probability mass transportation problem. Third, the generator start-up optimization strategy considering MBSRs is proposed utilizing the MPC technique, in which the optimization objective is to maximize the energy capability of the power systems and minimize the load curtailment of the MGs in each looking-ahead interval. Simulations on the IEEE 118 bus system with MGs and Zhejiang provincial power system in China verify that the proposed strategy for PSR can successfully restore the power system and effectively determine the optimal GSUS.</description><subject>Black-start</subject><subject>Computer simulation</subject><subject>Electric power grids</subject><subject>Energy conservation</subject><subject>Integer programming</subject><subject>Linear programming</subject><subject>Mathematical models</subject><subject>microgrid</subject><subject>Microgrids</subject><subject>Mixed integer</subject><subject>model predictive control (MPC)</subject><subject>Optimization</subject><subject>Power generation</subject><subject>Power system restoration</subject><subject>power system restoration (PSR)</subject><subject>Power system stability</subject><subject>POWER TRANSMISSION AND DISTRIBUTION</subject><subject>Predictive control</subject><subject>probability mass transportation problem (PMTP)</subject><subject>Restoration</subject><subject>scenario reduction</subject><subject>Strategy</subject><subject>Transportation problem</subject><subject>Uncertainty</subject><issn>0885-8950</issn><issn>1558-0679</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2018</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNo9kUtLBDEQhIMouD7-gF6CnmftZDaZ5KiLL1AUH3gM2UyPRtfJmkRBj_5ys454auj6qumiCNlhMGYM9MHd9cPN7ZgDU2OuJppLsUJGTAhVgWz0KhmBUqJSWsA62UjpGQBkEUbk-5Behhbn9Dpi6132H0inoc8xzOmRTdjSU-wx2hwivc025up-Qa8W2b_6L5t96Mu2qPj4SbuC3GAq5CA8-PxEL72L4TH6NlGb6NHcupfq984SDe_RYdoia52dJ9z-m5vk_uT4bnpWXVydnk8PLyo3YSJXLeMa9KzTumWuxOlmrZbOWglsxmtQEtSsnogaecck41BY5bABZi2XIJp6k-wNd0PK3iTnM7onF_oeXTZM8LrhvED7A7SI4e29pDHP5cu-_GU440yrSSPrQvGBKuFSitiZRfSvNn4aBmZZiPktxCwLMX-FFNPuYPKI-G9QtdIcmvoHRoqHvw</recordid><startdate>20181101</startdate><enddate>20181101</enddate><creator>Zhao, Yuxuan</creator><creator>Lin, Zhenzhi</creator><creator>Ding, Yi</creator><creator>Liu, Yilu</creator><creator>Sun, Lei</creator><creator>Yan, Yong</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. 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(ORNL), Oak Ridge, TN (United States)</aucorp><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A Model Predictive Control Based Generator Start-Up Optimization Strategy for Restoration With Microgrids as Black-Start Resources</atitle><jtitle>IEEE transactions on power systems</jtitle><stitle>TPWRS</stitle><date>2018-11-01</date><risdate>2018</risdate><volume>33</volume><issue>6</issue><spage>7189</spage><epage>7203</epage><pages>7189-7203</pages><issn>0885-8950</issn><eissn>1558-0679</eissn><coden>ITPSEG</coden><abstract>Microgrids (MGs) can operate in an islanded mode and serve as black-start resources for power system restoration (PSR). In this work, a model predictive control (MPC) based generator start-up optimization strategy for PSR is proposed utilizing MGs as black-start resources. First, the generator start-up sequence (GSUS) optimization is formulated as a mixed integer linear programming. Then, the uncertainties of MG black-start resources (MBSRs) are modeled by discretizing the probability distribution of the forecast errors, and representative scenarios for MBSRs extracted by formulating the probability mass transportation problem. Third, the generator start-up optimization strategy considering MBSRs is proposed utilizing the MPC technique, in which the optimization objective is to maximize the energy capability of the power systems and minimize the load curtailment of the MGs in each looking-ahead interval. 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subjects | Black-start Computer simulation Electric power grids Energy conservation Integer programming Linear programming Mathematical models microgrid Microgrids Mixed integer model predictive control (MPC) Optimization Power generation Power system restoration power system restoration (PSR) Power system stability POWER TRANSMISSION AND DISTRIBUTION Predictive control probability mass transportation problem (PMTP) Restoration scenario reduction Strategy Transportation problem Uncertainty |
title | A Model Predictive Control Based Generator Start-Up Optimization Strategy for Restoration With Microgrids as Black-Start Resources |
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