Operation Optimization with Jointly Controlled Modules Powered by Hybrid Energy Source : A Case Study of Desalination

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dc.contributor.authorLee, Sangkeumko
dc.contributor.authorCho, Hongyeonko
dc.contributor.authorHar, Dongsooko
dc.date.accessioned2018-01-30T05:49:08Z-
dc.date.available2018-01-30T05:49:08Z-
dc.date.created2017-08-22-
dc.date.created2017-08-22-
dc.date.issued2018-01-
dc.identifier.citationRENEWABLE & SUSTAINABLE ENERGY REVIEWS, v.81, no.2, pp.3070 - 3080-
dc.identifier.issn1364-0321-
dc.identifier.urihttp://hdl.handle.net/10203/239459-
dc.description.abstractThis article describes operation optimization with jointly controlled modules powered by hybrid energy source. Operation optimization is theoretically equivalent to optimization of certain objective (function(s)), representing operational efficiency, with imposed operational constraints. When the operation optimization involves multiple modules, joint control of these modules is highly likely to provide improved operational efficiency. Socio-economic advantages of renewable energy, including environmental benefit, infinite availability, and diversification of energy source, have been the motivation of the large number of relevant studies over the past decades. The periodic or aperiodic intermittency of typical renewable energy can be mitigated or removed by complementary measure that helps more stable energy provision. From this viewpoint, combining with other type of renewable energy or power grid in the form of hybrid energy source is effective. Desalination process is taken as the case study of operation optimization with jointly controlled modules powered by hybrid energy source and new experimental results are presented to help understand the impact of joint control, multi-objective optimization, and hybrid energy source on operation optimization.-
dc.languageEnglish-
dc.publisherPERGAMON-ELSEVIER SCIENCE LTD-
dc.subjectMULTIOBJECTIVE EVOLUTIONARY ALGORITHMS-
dc.subjectOF-THE-ART-
dc.subjectWATER DESALINATION-
dc.subjectGENETIC ALGORITHM-
dc.subjectRENEWABLE ENERGY-
dc.subjectECONOMIC-ANALYSIS-
dc.subjectSEAWATER DESALINATION-
dc.subjectRO DESALINATION-
dc.subjectWIND SYSTEM-
dc.subjectFRESH-WATER-
dc.titleOperation Optimization with Jointly Controlled Modules Powered by Hybrid Energy Source : A Case Study of Desalination-
dc.typeArticle-
dc.identifier.wosid000417078200113-
dc.identifier.scopusid2-s2.0-85028306560-
dc.type.rimsART-
dc.citation.volume81-
dc.citation.issue2-
dc.citation.beginningpage3070-
dc.citation.endingpage3080-
dc.citation.publicationnameRENEWABLE & SUSTAINABLE ENERGY REVIEWS-
dc.identifier.doi10.1016/j.rser.2017.08.076-
dc.contributor.localauthorHar, Dongsoo-
dc.contributor.nonIdAuthorLee, Sangkeum-
dc.contributor.nonIdAuthorCho, Hongyeon-
dc.description.isOpenAccessN-
dc.type.journalArticleReview-
dc.subject.keywordAuthorOperation optimization-
dc.subject.keywordAuthorJoint control-
dc.subject.keywordAuthorRenewable energy-
dc.subject.keywordAuthorHybrid source-
dc.subject.keywordAuthorMulti-objective optimization-
dc.subject.keywordAuthorDesalination-
dc.subject.keywordPlusMULTIOBJECTIVE EVOLUTIONARY ALGORITHMS-
dc.subject.keywordPlusOF-THE-ART-
dc.subject.keywordPlusWATER DESALINATION-
dc.subject.keywordPlusGENETIC ALGORITHM-
dc.subject.keywordPlusRENEWABLE ENERGY-
dc.subject.keywordPlusECONOMIC-ANALYSIS-
dc.subject.keywordPlusSEAWATER DESALINATION-
dc.subject.keywordPlusRO DESALINATION-
dc.subject.keywordPlusWIND SYSTEM-
dc.subject.keywordPlusFRESH-WATER-
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