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Modeling, calibration, and sensitivity analysis of direct expansion AHU-Water source VRF system

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dc.contributor.authorKang, Won Hee-
dc.contributor.authorLee, Jong Man-
dc.contributor.authorYeon, Sang Hun-
dc.contributor.authorPark, Min Kyeong-
dc.contributor.authorKim, Chul Ho-
dc.contributor.authorLee, Je Hyeon-
dc.contributor.authorMoon, Jin Woo-
dc.contributor.authorLee, Kwang Ho-
dc.date.accessioned2021-08-31T00:01:10Z-
dc.date.available2021-08-31T00:01:10Z-
dc.date.created2021-06-19-
dc.date.issued2020-05-15-
dc.identifier.issn0360-5442-
dc.identifier.urihttps://scholar.korea.ac.kr/handle/2021.sw.korea/55697-
dc.description.abstractThe term variable refrigerant flow (VRF) refers to the ability of a system to control the amount of refrigerant flow rate, which enables the use of many evaporators (indoor units) of differing capacities and configurations connected to a single condensing unit. The feature offers individualized comfort control and simultaneous heating and cooling in different zones. In this study, a performance prediction model of a DX AHU (direct expansion air handling unit)-water source VRF heat pump system was constructed based on EnergyPlus, MATLAB and BCVTB using actual measured data. Advanced control logic using an EMS function was used in EnergyPlus for outdoor unit modeling, while prediction models for a cooling tower, boiler and pump were constructed in Matlab. In order to predict the model's quantitative energy consumption, performance curves and power consumption were calculated. The calculations were checked by comparing them with actual data and the performance curves were then calibrated. The validity test results after the calibrations showed reliable results with a Cv(RMSE) of 14.5%. Based on these results, we performed a sensitivity analysis of the DX AHU-water source VRF system's cooling energy according to the AHU discharge air temperature, refrigerant evaporative temperature and condenser fluid temperature and flow rate. (C) 2020 Elsevier Ltd. All rights reserved.-
dc.languageEnglish-
dc.language.isoen-
dc.publisherPERGAMON-ELSEVIER SCIENCE LTD-
dc.subjectARTIFICIAL NEURAL-NETWORKS-
dc.subjectREFRIGERANT FLOW SYSTEMS-
dc.subjectAIR-CONDITIONING SYSTEM-
dc.subjectCOOLING ENERGY-
dc.subjectPERFORMANCE-
dc.subjectVAV-
dc.titleModeling, calibration, and sensitivity analysis of direct expansion AHU-Water source VRF system-
dc.typeArticle-
dc.contributor.affiliatedAuthorLee, Kwang Ho-
dc.identifier.doi10.1016/j.energy.2020.117435-
dc.identifier.scopusid2-s2.0-85082871016-
dc.identifier.wosid000527571300022-
dc.identifier.bibliographicCitationENERGY, v.199-
dc.relation.isPartOfENERGY-
dc.citation.titleENERGY-
dc.citation.volume199-
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.keywordPlusARTIFICIAL NEURAL-NETWORKS-
dc.subject.keywordPlusREFRIGERANT FLOW SYSTEMS-
dc.subject.keywordPlusAIR-CONDITIONING SYSTEM-
dc.subject.keywordPlusCOOLING ENERGY-
dc.subject.keywordPlusPERFORMANCE-
dc.subject.keywordPlusVAV-
dc.subject.keywordAuthorVariable refrigerant flow (VRF)-
dc.subject.keywordAuthorEnergyPlus-
dc.subject.keywordAuthorPerformance curve-
dc.subject.keywordAuthorPart load ratio-
dc.subject.keywordAuthorCooling capacity-
dc.subject.keywordAuthorCalibration-
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