Residential building design optimisation using sensitivity analysis and genetic algorithm

Autores
Bre, Facundo; Silva, Arthur Santos; Ghisi, Enedir; Fachinotti, Victor Daniel
Año de publicación
2016
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
The objective of this paper is to combine sensitivity analysis and simulation-based optimisation in order to optimise the thermal and energy performance of residential buildings in the Argentine Littoral region. An actual house was selected as case study. This is a typical, local, single-family house having some rooms conditioned only by natural ventilation, and other rooms with natural ventilation supplemented by mechanical air-conditioning (hybrid ventilation). Hence, the total degree-hours at the naturally ventilated living room and the total energy consumption by air-conditioning at the bedrooms were chosen as objective functions to be minimised. The global objective function characterising the thermal and energy performance of the house was defined as the weighted sum of these objective functions. This objective function was computed using the EnergyPlus building performance simulation programme. Then, we performed a sensitivity analysis using the Morris screening method to rank the influence of the design variables on the objective function. This showed that the type of external walls, the windows infiltration rate and the solar azimuth were the most influential design variables on the given objective function for the considered house, and also that the azimuth either had a highly nonlinear effect on the objective function or was highly correlated to the others variables, deserving in any case a finer discretisation. Finally, we solved an optimisation problem using genetic algorithms in order to find the optimal set of design variables for the considered house. The results highlighted the efficiency and the effectiveness of the proposed methodology to redesign a typical house in the Argentine Littoral region, improving hugely its thermal and energy performance.
Fil: Bre, Facundo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Centro de Investigaciones en Métodos Computacionales. Universidad Nacional del Litoral. Centro de Investigaciones en Métodos Computacionales; Argentina. Universidad Tecnológica Nacional. Facultad Regional Concepción del Uruguay; Argentina
Fil: Silva, Arthur Santos. Universidade Federal de Santa Catarina; Brasil
Fil: Ghisi, Enedir. Universidade Federal de Santa Catarina; Brasil
Fil: Fachinotti, Victor Daniel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Centro de Investigaciones en Métodos Computacionales. Universidad Nacional del Litoral. Centro de Investigaciones en Métodos Computacionales; Argentina
Materia
Energy Consumption
Energyplus
Genetic Algorithms
Hybrid Ventilation
Multi-Objective Optimisation
Residential Building
Sensitivity Analysis
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/38286
Acceder
id CONICETDig_b68325f51ff757eeac1847dcb469058c
oai_identifier_str oai:ri.conicet.gov.ar:11336/38286
network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling Residential building design optimisation using sensitivity analysis and genetic algorithmBre, FacundoSilva, Arthur SantosGhisi, EnedirFachinotti, Victor DanielEnergy ConsumptionEnergyplusGenetic AlgorithmsHybrid VentilationMulti-Objective OptimisationResidential BuildingSensitivity Analysishttps://purl.org/becyt/ford/2.1https://purl.org/becyt/ford/2https://purl.org/becyt/ford/1.2https://purl.org/becyt/ford/1The objective of this paper is to combine sensitivity analysis and simulation-based optimisation in order to optimise the thermal and energy performance of residential buildings in the Argentine Littoral region. An actual house was selected as case study. This is a typical, local, single-family house having some rooms conditioned only by natural ventilation, and other rooms with natural ventilation supplemented by mechanical air-conditioning (hybrid ventilation). Hence, the total degree-hours at the naturally ventilated living room and the total energy consumption by air-conditioning at the bedrooms were chosen as objective functions to be minimised. The global objective function characterising the thermal and energy performance of the house was defined as the weighted sum of these objective functions. This objective function was computed using the EnergyPlus building performance simulation programme. Then, we performed a sensitivity analysis using the Morris screening method to rank the influence of the design variables on the objective function. This showed that the type of external walls, the windows infiltration rate and the solar azimuth were the most influential design variables on the given objective function for the considered house, and also that the azimuth either had a highly nonlinear effect on the objective function or was highly correlated to the others variables, deserving in any case a finer discretisation. Finally, we solved an optimisation problem using genetic algorithms in order to find the optimal set of design variables for the considered house. The results highlighted the efficiency and the effectiveness of the proposed methodology to redesign a typical house in the Argentine Littoral region, improving hugely its thermal and energy performance.Fil: Bre, Facundo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Centro de Investigaciones en Métodos Computacionales. Universidad Nacional del Litoral. Centro de Investigaciones en Métodos Computacionales; Argentina. Universidad Tecnológica Nacional. Facultad Regional Concepción del Uruguay; ArgentinaFil: Silva, Arthur Santos. Universidade Federal de Santa Catarina; BrasilFil: Ghisi, Enedir. Universidade Federal de Santa Catarina; BrasilFil: Fachinotti, Victor Daniel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Centro de Investigaciones en Métodos Computacionales. Universidad Nacional del Litoral. Centro de Investigaciones en Métodos Computacionales; ArgentinaElsevier Science Sa2016-12info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/38286Bre, Facundo; Silva, Arthur Santos; Ghisi, Enedir; Fachinotti, Victor Daniel; Residential building design optimisation using sensitivity analysis and genetic algorithm; Elsevier Science Sa; Energy and Buildings; 133; 12-2016; 853-8660378-7788CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/http://www.sciencedirect.com/science/article/pii/S0378778816312440info:eu-repo/semantics/altIdentifier/doi/10.1016/j.enbuild.2016.10.025info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-10-22T11:06:08Zoai:ri.conicet.gov.ar:11336/38286instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-10-22 11:06:08.635CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Residential building design optimisation using sensitivity analysis and genetic algorithm
title Residential building design optimisation using sensitivity analysis and genetic algorithm
spellingShingle Residential building design optimisation using sensitivity analysis and genetic algorithm
Bre, Facundo
Energy Consumption
Energyplus
Genetic Algorithms
Hybrid Ventilation
Multi-Objective Optimisation
Residential Building
Sensitivity Analysis
title_short Residential building design optimisation using sensitivity analysis and genetic algorithm
title_full Residential building design optimisation using sensitivity analysis and genetic algorithm
title_fullStr Residential building design optimisation using sensitivity analysis and genetic algorithm
title_full_unstemmed Residential building design optimisation using sensitivity analysis and genetic algorithm
title_sort Residential building design optimisation using sensitivity analysis and genetic algorithm
dc.creator.none.fl_str_mv Bre, Facundo
Silva, Arthur Santos
Ghisi, Enedir
Fachinotti, Victor Daniel
author Bre, Facundo
author_facet Bre, Facundo
Silva, Arthur Santos
Ghisi, Enedir
Fachinotti, Victor Daniel
author_role author
author2 Silva, Arthur Santos
Ghisi, Enedir
Fachinotti, Victor Daniel
author2_role author
author
author
dc.subject.none.fl_str_mv Energy Consumption
Energyplus
Genetic Algorithms
Hybrid Ventilation
Multi-Objective Optimisation
Residential Building
Sensitivity Analysis
topic Energy Consumption
Energyplus
Genetic Algorithms
Hybrid Ventilation
Multi-Objective Optimisation
Residential Building
Sensitivity Analysis
purl_subject.fl_str_mv https://purl.org/becyt/ford/2.1
https://purl.org/becyt/ford/2
https://purl.org/becyt/ford/1.2
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv The objective of this paper is to combine sensitivity analysis and simulation-based optimisation in order to optimise the thermal and energy performance of residential buildings in the Argentine Littoral region. An actual house was selected as case study. This is a typical, local, single-family house having some rooms conditioned only by natural ventilation, and other rooms with natural ventilation supplemented by mechanical air-conditioning (hybrid ventilation). Hence, the total degree-hours at the naturally ventilated living room and the total energy consumption by air-conditioning at the bedrooms were chosen as objective functions to be minimised. The global objective function characterising the thermal and energy performance of the house was defined as the weighted sum of these objective functions. This objective function was computed using the EnergyPlus building performance simulation programme. Then, we performed a sensitivity analysis using the Morris screening method to rank the influence of the design variables on the objective function. This showed that the type of external walls, the windows infiltration rate and the solar azimuth were the most influential design variables on the given objective function for the considered house, and also that the azimuth either had a highly nonlinear effect on the objective function or was highly correlated to the others variables, deserving in any case a finer discretisation. Finally, we solved an optimisation problem using genetic algorithms in order to find the optimal set of design variables for the considered house. The results highlighted the efficiency and the effectiveness of the proposed methodology to redesign a typical house in the Argentine Littoral region, improving hugely its thermal and energy performance.
Fil: Bre, Facundo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Centro de Investigaciones en Métodos Computacionales. Universidad Nacional del Litoral. Centro de Investigaciones en Métodos Computacionales; Argentina. Universidad Tecnológica Nacional. Facultad Regional Concepción del Uruguay; Argentina
Fil: Silva, Arthur Santos. Universidade Federal de Santa Catarina; Brasil
Fil: Ghisi, Enedir. Universidade Federal de Santa Catarina; Brasil
Fil: Fachinotti, Victor Daniel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Centro de Investigaciones en Métodos Computacionales. Universidad Nacional del Litoral. Centro de Investigaciones en Métodos Computacionales; Argentina
description The objective of this paper is to combine sensitivity analysis and simulation-based optimisation in order to optimise the thermal and energy performance of residential buildings in the Argentine Littoral region. An actual house was selected as case study. This is a typical, local, single-family house having some rooms conditioned only by natural ventilation, and other rooms with natural ventilation supplemented by mechanical air-conditioning (hybrid ventilation). Hence, the total degree-hours at the naturally ventilated living room and the total energy consumption by air-conditioning at the bedrooms were chosen as objective functions to be minimised. The global objective function characterising the thermal and energy performance of the house was defined as the weighted sum of these objective functions. This objective function was computed using the EnergyPlus building performance simulation programme. Then, we performed a sensitivity analysis using the Morris screening method to rank the influence of the design variables on the objective function. This showed that the type of external walls, the windows infiltration rate and the solar azimuth were the most influential design variables on the given objective function for the considered house, and also that the azimuth either had a highly nonlinear effect on the objective function or was highly correlated to the others variables, deserving in any case a finer discretisation. Finally, we solved an optimisation problem using genetic algorithms in order to find the optimal set of design variables for the considered house. The results highlighted the efficiency and the effectiveness of the proposed methodology to redesign a typical house in the Argentine Littoral region, improving hugely its thermal and energy performance.
publishDate 2016
dc.date.none.fl_str_mv 2016-12
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/38286
Bre, Facundo; Silva, Arthur Santos; Ghisi, Enedir; Fachinotti, Victor Daniel; Residential building design optimisation using sensitivity analysis and genetic algorithm; Elsevier Science Sa; Energy and Buildings; 133; 12-2016; 853-866
0378-7788
CONICET Digital
CONICET
url http://hdl.handle.net/11336/38286
identifier_str_mv Bre, Facundo; Silva, Arthur Santos; Ghisi, Enedir; Fachinotti, Victor Daniel; Residential building design optimisation using sensitivity analysis and genetic algorithm; Elsevier Science Sa; Energy and Buildings; 133; 12-2016; 853-866
0378-7788
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/http://www.sciencedirect.com/science/article/pii/S0378778816312440
info:eu-repo/semantics/altIdentifier/doi/10.1016/j.enbuild.2016.10.025
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
application/pdf
dc.publisher.none.fl_str_mv Elsevier Science Sa
publisher.none.fl_str_mv Elsevier Science Sa
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
_version_ 1846781354636738560
score 12.982451

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