Multi-objective optimization of the solar orientation of two residential multifamily buildings in south Brazil

Detalhes bibliográficos
Autor(a) principal: Benincá, Letiane
Data de Publicação: 2023
Outros Autores: Crespo Sánchez, Eva, Passuello, Ana Carolina Badalotti, Leitzke, Rodrigo Karini, Cunha, Eduardo Grala da, González Barroso, José María
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da UFRGS
Texto Completo: http://hdl.handle.net/10183/262995
Resumo: The shape and orientation of a building influence the energy demand, therefore optimal decisions should only be made rigorously supported by energy evaluation programs, which allow for measuring the energy demand of a building more precisely. The main purpose of this research is to evaluate the shape and orientation of massive residential social housing multifamily buildings to find the best solar positioning to minimize cooling and heating demands simultaneously in the bioclimatic zone 2 (Cfa) in the southern region of Brazil. To do this, this study utilizes multi-objective optimization with a genetic algorithm (NSGA-II) simulating the thermal behavior in EnergyPlus and performing the optimization with a Python language programming code, totalizing 80,000 simulations. The main results showed that solar orientation optimization could reduce the total demand by 4% for the ‘‘H” shape and 22% for linear buildings in the isolated scenario. For the condominium condition, the reduction is 2% for the ‘‘H” typology and 8% for the linear shape. The results presented can help engineers and architects to design more energyefficient buildings and address the energetic vulnerability in the same building. Moreover, future work can be carried out to improve the constructive pattern replicated all over the country, improving the surroundings.
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spelling Benincá, LetianeCrespo Sánchez, EvaPassuello, Ana Carolina BadalottiLeitzke, Rodrigo KariniCunha, Eduardo Grala daGonzález Barroso, José María2023-08-02T03:31:45Z20230378-7788http://hdl.handle.net/10183/262995001166412The shape and orientation of a building influence the energy demand, therefore optimal decisions should only be made rigorously supported by energy evaluation programs, which allow for measuring the energy demand of a building more precisely. The main purpose of this research is to evaluate the shape and orientation of massive residential social housing multifamily buildings to find the best solar positioning to minimize cooling and heating demands simultaneously in the bioclimatic zone 2 (Cfa) in the southern region of Brazil. To do this, this study utilizes multi-objective optimization with a genetic algorithm (NSGA-II) simulating the thermal behavior in EnergyPlus and performing the optimization with a Python language programming code, totalizing 80,000 simulations. The main results showed that solar orientation optimization could reduce the total demand by 4% for the ‘‘H” shape and 22% for linear buildings in the isolated scenario. For the condominium condition, the reduction is 2% for the ‘‘H” typology and 8% for the linear shape. The results presented can help engineers and architects to design more energyefficient buildings and address the energetic vulnerability in the same building. Moreover, future work can be carried out to improve the constructive pattern replicated all over the country, improving the surroundings.application/pdfengEnergy and buildings : an international journal of research applied to energy efficiency in the built environment. Vol. 285 (2023), p. 112838-112861.Otimização multiobjetivoOrientacao solarAlgoritmo genéticoEficiência energéticaAquecimentoResfriamentoMulti-objective optimizationGenetic algorithmNSGA-IIEnergy efficiencyCooling demandHeating demandEnergy plusPythonMulti-objective optimization of the solar orientation of two residential multifamily buildings in south BrazilEstrangeiroinfo:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/openAccessreponame:Repositório Institucional da UFRGSinstname:Universidade Federal do Rio Grande do Sul (UFRGS)instacron:UFRGSTEXT001166412.pdf.txt001166412.pdf.txtExtracted Texttext/plain110379http://www.lume.ufrgs.br/bitstream/10183/262995/2/001166412.pdf.txt5182338b8182185be0ec58ceb94a7310MD52ORIGINAL001166412.pdfTexto completo (inglês)application/pdf3685007http://www.lume.ufrgs.br/bitstream/10183/262995/1/001166412.pdfab1c1bc56dc271392960617f53626e85MD5110183/2629952023-08-03 03:32:31.297109oai:www.lume.ufrgs.br:10183/262995Repositório de PublicaçõesPUBhttps://lume.ufrgs.br/oai/requestopendoar:2023-08-03T06:32:31Repositório Institucional da UFRGS - Universidade Federal do Rio Grande do Sul (UFRGS)false
dc.title.pt_BR.fl_str_mv Multi-objective optimization of the solar orientation of two residential multifamily buildings in south Brazil
title Multi-objective optimization of the solar orientation of two residential multifamily buildings in south Brazil
spellingShingle Multi-objective optimization of the solar orientation of two residential multifamily buildings in south Brazil
Benincá, Letiane
Otimização multiobjetivo
Orientacao solar
Algoritmo genético
Eficiência energética
Aquecimento
Resfriamento
Multi-objective optimization
Genetic algorithm
NSGA-II
Energy efficiency
Cooling demand
Heating demand
Energy plus
Python
title_short Multi-objective optimization of the solar orientation of two residential multifamily buildings in south Brazil
title_full Multi-objective optimization of the solar orientation of two residential multifamily buildings in south Brazil
title_fullStr Multi-objective optimization of the solar orientation of two residential multifamily buildings in south Brazil
title_full_unstemmed Multi-objective optimization of the solar orientation of two residential multifamily buildings in south Brazil
title_sort Multi-objective optimization of the solar orientation of two residential multifamily buildings in south Brazil
author Benincá, Letiane
author_facet Benincá, Letiane
Crespo Sánchez, Eva
Passuello, Ana Carolina Badalotti
Leitzke, Rodrigo Karini
Cunha, Eduardo Grala da
González Barroso, José María
author_role author
author2 Crespo Sánchez, Eva
Passuello, Ana Carolina Badalotti
Leitzke, Rodrigo Karini
Cunha, Eduardo Grala da
González Barroso, José María
author2_role author
author
author
author
author
dc.contributor.author.fl_str_mv Benincá, Letiane
Crespo Sánchez, Eva
Passuello, Ana Carolina Badalotti
Leitzke, Rodrigo Karini
Cunha, Eduardo Grala da
González Barroso, José María
dc.subject.por.fl_str_mv Otimização multiobjetivo
Orientacao solar
Algoritmo genético
Eficiência energética
Aquecimento
Resfriamento
topic Otimização multiobjetivo
Orientacao solar
Algoritmo genético
Eficiência energética
Aquecimento
Resfriamento
Multi-objective optimization
Genetic algorithm
NSGA-II
Energy efficiency
Cooling demand
Heating demand
Energy plus
Python
dc.subject.eng.fl_str_mv Multi-objective optimization
Genetic algorithm
NSGA-II
Energy efficiency
Cooling demand
Heating demand
Energy plus
Python
description The shape and orientation of a building influence the energy demand, therefore optimal decisions should only be made rigorously supported by energy evaluation programs, which allow for measuring the energy demand of a building more precisely. The main purpose of this research is to evaluate the shape and orientation of massive residential social housing multifamily buildings to find the best solar positioning to minimize cooling and heating demands simultaneously in the bioclimatic zone 2 (Cfa) in the southern region of Brazil. To do this, this study utilizes multi-objective optimization with a genetic algorithm (NSGA-II) simulating the thermal behavior in EnergyPlus and performing the optimization with a Python language programming code, totalizing 80,000 simulations. The main results showed that solar orientation optimization could reduce the total demand by 4% for the ‘‘H” shape and 22% for linear buildings in the isolated scenario. For the condominium condition, the reduction is 2% for the ‘‘H” typology and 8% for the linear shape. The results presented can help engineers and architects to design more energyefficient buildings and address the energetic vulnerability in the same building. Moreover, future work can be carried out to improve the constructive pattern replicated all over the country, improving the surroundings.
publishDate 2023
dc.date.accessioned.fl_str_mv 2023-08-02T03:31:45Z
dc.date.issued.fl_str_mv 2023
dc.type.driver.fl_str_mv Estrangeiro
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dc.language.iso.fl_str_mv eng
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dc.relation.ispartof.pt_BR.fl_str_mv Energy and buildings : an international journal of research applied to energy efficiency in the built environment. Vol. 285 (2023), p. 112838-112861.
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reponame_str Repositório Institucional da UFRGS
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