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Please use this identifier to cite or link to this item: http://hdl.handle.net/1843/58540
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dc.creatorAlex Henrique Coutinho Santospt_BR
dc.creatorTiago de Freitas Paulinopt_BR
dc.creatorDaniele Marques Ferreirapt_BR
dc.creatorPaulo Eduardo Lopes Barbierept_BR
dc.date.accessioned2023-09-07T00:08:05Z-
dc.date.available2023-09-07T00:08:05Z-
dc.date.issued2022-
dc.citation.issue19pt_BR
dc.citation.spage1pt_BR
dc.citation.epage10pt_BR
dc.identifier.urihttp://hdl.handle.net/1843/58540-
dc.description.resumoIn 2017, electrical air conditioning systems represent an approximate consumption of 20% of the total electrical energy consumed in Brazilian homes. In addition, air conditioning systems may account for 85% of the consumption of residential electric energy in the peak of summer and in commercial establishments approximately 40% of the electric energy consumed is destined for the acclimatization of environments. An innovative technology that can collaborate to mitigate environmental problems and make energy consumption more efficient is thermal energy storage (TES). The TES also helps to decouple the cooling production and the use of it. In that way the cold should be produced during the night, for example and use during the day. This paper proposes a mathematical model using Python language and CoolProp for refrigerant properties. A chiller refrigerant system able to meet a colling capacity of 15 TR is selected. It simulates the operation of refrigeration systems to evaluate the coefficient of performance (COP) during the year of 2020 for three cities in different regions in Brazil: Fortaleza - CE (Northeast), Brasília - DF (Midwest) and Monte Verde – MG (Southeast). In each city will verify the efficiency of three different refrigerant fluids, R134a, R1234yf and R717. The mathematical model of refrigeration system considers a chiller with a TES (Thermal Energy System) to produce and storage cold during the night to be consumed during the day, specially at the peak time. As the condition in the evaporator are keep constant in the system, the model consider only the compressor and the condenser. The mathematical model applied in this study make a comparison between the refrigerant fluids, where R134a is considered as a reference, and comparing with R1234yf and R717. The objective of the manuscript is to select the refrigerant that best suit to the context of the selected cities, considering R134a as a reference, we have that the COP of R717 is greater by about 16.1% for Fortaleza - CE, 14.6% for Brasília - DF and 13.2% for Monte Verde - MGpt_BR
dc.format.mimetypepdfpt_BR
dc.languageengpt_BR
dc.publisherUniversidade Federal de Minas Geraispt_BR
dc.publisher.countryBrasilpt_BR
dc.publisher.departmentENG - DEPARTAMENTO DE ENGENHARIA MECÂNICApt_BR
dc.publisher.initialsUFMGpt_BR
dc.rightsAcesso Abertopt_BR
dc.rightsAtribuição 3.0 Portugal*
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/pt/*
dc.subjectRefrigerant selectionpt_BR
dc.subjectMathematical modelpt_BR
dc.subjectAir conditioning systempt_BR
dc.subject.otherAr condicionadopt_BR
dc.titleRefrigerant selection for a chiller air conditioning system in Brazilpt_BR
dc.typeArtigo de Eventopt_BR
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