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Optimal operational scheduling of distribution network with microgrid via bi-level optimization model with energy band

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dc.contributor.authorKim, Ho-Young-
dc.contributor.authorKim, Mun-Kyeom-
dc.contributor.authorKim, Hyung-Joon-
dc.date.available2020-04-20T02:20:41Z-
dc.date.issued2019-10-
dc.identifier.issn2076-3417-
dc.identifier.issn2076-3417-
dc.identifier.urihttps://scholarworks.bwise.kr/cau/handle/2019.sw.cau/38704-
dc.description.abstractAn optimal operation of new distributed energy resources can significantly advance the performance of power systems, including distribution network (DN). However, increased penetration of renewable energy may negatively affect the system performance under certain conditions. From a system operator perspective, the tie-line control strategy may aid in overcoming various problems regarding increased renewable penetration. We propose a bi-level optimization model incorporating an energy band operation scheme to ensure cooperation between DN and microgrid (MG). The bi-level formulation for the cooperation problem consists of the cost minimization of the DN and profit maximization of the MG. The goal of the upper-level is to minimize the operating costs of the DN by accounting for feedback information, including the operating costs of the MG and energy band. The lower-level aims to maximize the MG profit, simultaneously satisfying the reliability and economic targets imposed in the scheduling requirements by the DN system operator. The bi-level optimization model is solved using an advanced method based on the modified non-dominated sorting genetic algorithm II. Based on simulation results using a typical MG and an actual power system, we demonstrate the applicability, effectiveness, and validity of the proposed bi-level optimization model. © 2019 by the authors.-
dc.language영어-
dc.language.isoENG-
dc.publisherMDPI AG-
dc.titleOptimal operational scheduling of distribution network with microgrid via bi-level optimization model with energy band-
dc.typeArticle-
dc.identifier.doi10.3390/app9204219-
dc.identifier.bibliographicCitationApplied Sciences (Switzerland), v.9, no.20-
dc.description.isOpenAccessY-
dc.identifier.wosid000496269400022-
dc.identifier.scopusid2-s2.0-85074192035-
dc.citation.number20-
dc.citation.titleApplied Sciences (Switzerland)-
dc.citation.volume9-
dc.type.docTypeArticle-
dc.publisher.location스위스-
dc.subject.keywordAuthorBi-level optimization model-
dc.subject.keywordAuthorCooperation-
dc.subject.keywordAuthorDistributed energy resource-
dc.subject.keywordAuthorDistribution network-
dc.subject.keywordAuthorEnergy band-
dc.subject.keywordAuthorMicrogrid-
dc.subject.keywordAuthorModified non-dominated sorting genetic algorithm II-
dc.subject.keywordPlusMANAGEMENT-
dc.subject.keywordPlusGENERATION-
dc.subject.keywordPlusDEMAND-
dc.subject.keywordPlusSYSTEM-
dc.relation.journalResearchAreaChemistry-
dc.relation.journalResearchAreaEngineering-
dc.relation.journalResearchAreaMaterials Science-
dc.relation.journalResearchAreaPhysics-
dc.relation.journalWebOfScienceCategoryChemistry, Multidisciplinary-
dc.relation.journalWebOfScienceCategoryEngineering, Multidisciplinary-
dc.relation.journalWebOfScienceCategoryMaterials Science, Multidisciplinary-
dc.relation.journalWebOfScienceCategoryPhysics, Applied-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
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공과대학 (에너지시스템 공학부)
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