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Model-based multi-objective optimal control of a VRF (variable refrigerant flow) combined system with DOAS (dedicated outdoor air system) using genetic algorithm under heating conditions

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dc.contributor.authorKim, Wonuk-
dc.contributor.authorJeon, Seung Won-
dc.contributor.authorKim, Yongchan-
dc.date.accessioned2021-09-03T21:54:49Z-
dc.date.available2021-09-03T21:54:49Z-
dc.date.created2021-06-18-
dc.date.issued2016-07-15-
dc.identifier.issn0360-5442-
dc.identifier.urihttps://scholar.korea.ac.kr/handle/2021.sw.korea/88055-
dc.description.abstractA VRF (variable refrigerant flow) combined system adopting a DOAS (dedicated outdoor air system) has been proposed to reduce the total energy consumption while satisfying IAQ (indoor air quality) and THC (thermal and humidity comfort) with minimum outdoor air. The objective of this study is to develop,a model-based multi-objective optimal control strategy for the VRF combined system with multi-zone in order to optimize the multi-objective functions of the THC, IAQ, and total energy consumption. The performance of the VRF combined system was evaluated using the EnergyPlus model. The VRF combined system was optimized by GA (genetic algorithm) and RSM (response surface methodology) with the multi-objective functions of the THC, IAQ and total energy consumption. The proposed multi-objective optimal control strategies (A and B) were compared with the TS (time schedule) strategy and the DCVH (demand controlled ventilation with humidifying). Optimal control strategy B reduced the total energy consumption by 20.4% and increased the ratio of the hours satisfying the extended comfort zone by 19.1% compared to the DCVH strategy. (C) 2016 Elsevier Ltd. All rights reserved.-
dc.languageEnglish-
dc.language.isoen-
dc.publisherPERGAMON-ELSEVIER SCIENCE LTD-
dc.subjectCONTROLLED VENTILATION STRATEGY-
dc.subjectENERGY SIMULATION-
dc.subjectCOOLING MODE-
dc.subjectVAV-
dc.subjectPERFORMANCE-
dc.titleModel-based multi-objective optimal control of a VRF (variable refrigerant flow) combined system with DOAS (dedicated outdoor air system) using genetic algorithm under heating conditions-
dc.typeArticle-
dc.contributor.affiliatedAuthorKim, Yongchan-
dc.identifier.doi10.1016/j.energy.2016.03.139-
dc.identifier.scopusid2-s2.0-84964459819-
dc.identifier.wosid000378660500016-
dc.identifier.bibliographicCitationENERGY, v.107, pp.196 - 204-
dc.relation.isPartOfENERGY-
dc.citation.titleENERGY-
dc.citation.volume107-
dc.citation.startPage196-
dc.citation.endPage204-
dc.type.rimsART-
dc.type.docTypeArticle-
dc.description.journalClass1-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaThermodynamics-
dc.relation.journalResearchAreaEnergy & Fuels-
dc.relation.journalWebOfScienceCategoryThermodynamics-
dc.relation.journalWebOfScienceCategoryEnergy & Fuels-
dc.subject.keywordPlusCONTROLLED VENTILATION STRATEGY-
dc.subject.keywordPlusENERGY SIMULATION-
dc.subject.keywordPlusCOOLING MODE-
dc.subject.keywordPlusVAV-
dc.subject.keywordPlusPERFORMANCE-
dc.subject.keywordAuthorVariable refrigerant flow-
dc.subject.keywordAuthorDedicated outdoor air system-
dc.subject.keywordAuthorModel-based control-
dc.subject.keywordAuthorMulti-objective optimization-
dc.subject.keywordAuthorMulti-zone ventilation-
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