A simulation-optimization approach for the household energy planning problem considering uncertainty in users preferences

Autores
Rossit, Diego Gabriel; Nesmachnow, Sergio; Toutouh, Jamal; Luna, Francisco
Año de publicación
2020
Idioma
inglés
Tipo de recurso
documento de conferencia
Estado
versión publicada
Descripción
Power supply is one of the basic needs in modern smart homes. Computer-aid tools help optimizing energy utilization, contributing to sustainable goals of modern societies. For this purpose, this article presents a mathematical formulation to the household energy planning problem and a specic resolution method to build schedules for using deferrable electric that can reduce the cost of the electricity bill while keeping user satisfaction at a satisfactory level. User satisfaction have a great variability, since it is based on human preferences, thus a stochastic simulation-optimization approach is applied for handling uncertainty in the optimization process. Results over instances based on real-world data show the competitiveness of the proposed approach, which is able to compute dierent compromise solution accounting for the trade-off between these two conficting optimization criteria.
Fil: Rossit, Diego Gabriel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Matemática Bahía Blanca. Universidad Nacional del Sur. Departamento de Matemática. Instituto de Matemática Bahía Blanca; Argentina. Universidad Nacional del Sur. Departamento de Ingeniería; Argentina
Fil: Nesmachnow, Sergio. Universidad de la República; Uruguay
Fil: Toutouh, Jamal. Massachusetts Institute of Technology; Estados Unidos
Fil: Luna, Francisco. Universidad de Málaga; España
International Conference of Production Research - Americas 2020
Bahía Blanca
Argentina
Universidad Nacional del Sur
Materia
SMART CITIES
ENERGY PLANNING
MIXED-INTEGER PROGRAMMING
MULTIOBJECTIVE OPTIMIZATION
SIMULATION
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:11336/147143
Acceder
id CONICETDig_61e93bb3dfc69373731de42ce7690f7c
oai_identifier_str oai:ri.conicet.gov.ar:11336/147143
network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling A simulation-optimization approach for the household energy planning problem considering uncertainty in users preferencesRossit, Diego GabrielNesmachnow, SergioToutouh, JamalLuna, FranciscoSMART CITIESENERGY PLANNINGMIXED-INTEGER PROGRAMMINGMULTIOBJECTIVE OPTIMIZATIONSIMULATIONhttps://purl.org/becyt/ford/2.11https://purl.org/becyt/ford/2Power supply is one of the basic needs in modern smart homes. Computer-aid tools help optimizing energy utilization, contributing to sustainable goals of modern societies. For this purpose, this article presents a mathematical formulation to the household energy planning problem and a specic resolution method to build schedules for using deferrable electric that can reduce the cost of the electricity bill while keeping user satisfaction at a satisfactory level. User satisfaction have a great variability, since it is based on human preferences, thus a stochastic simulation-optimization approach is applied for handling uncertainty in the optimization process. Results over instances based on real-world data show the competitiveness of the proposed approach, which is able to compute dierent compromise solution accounting for the trade-off between these two conficting optimization criteria.Fil: Rossit, Diego Gabriel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Matemática Bahía Blanca. Universidad Nacional del Sur. Departamento de Matemática. Instituto de Matemática Bahía Blanca; Argentina. Universidad Nacional del Sur. Departamento de Ingeniería; ArgentinaFil: Nesmachnow, Sergio. Universidad de la República; UruguayFil: Toutouh, Jamal. Massachusetts Institute of Technology; Estados UnidosFil: Luna, Francisco. Universidad de Málaga; EspañaInternational Conference of Production Research - Americas 2020Bahía BlancaArgentinaUniversidad Nacional del SurUniversidad Nacional del Sur2020info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/conferenceObjectConferenciaJournalhttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/147143A simulation-optimization approach for the household energy planning problem considering uncertainty in users preferences; International Conference of Production Research - Americas 2020; Bahía Blanca; Argentina; 2020; 40-542619-1865CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/https://www.matematica.uns.edu.ar/ipcra/pdf/icpr_americas_2020_proceedings.pdfInternacionalinfo:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T09:35:14Zoai:ri.conicet.gov.ar:11336/147143instacron: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:34982025-09-29 09:35:14.278CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv A simulation-optimization approach for the household energy planning problem considering uncertainty in users preferences
title A simulation-optimization approach for the household energy planning problem considering uncertainty in users preferences
spellingShingle A simulation-optimization approach for the household energy planning problem considering uncertainty in users preferences
Rossit, Diego Gabriel
SMART CITIES
ENERGY PLANNING
MIXED-INTEGER PROGRAMMING
MULTIOBJECTIVE OPTIMIZATION
SIMULATION
title_short A simulation-optimization approach for the household energy planning problem considering uncertainty in users preferences
title_full A simulation-optimization approach for the household energy planning problem considering uncertainty in users preferences
title_fullStr A simulation-optimization approach for the household energy planning problem considering uncertainty in users preferences
title_full_unstemmed A simulation-optimization approach for the household energy planning problem considering uncertainty in users preferences
title_sort A simulation-optimization approach for the household energy planning problem considering uncertainty in users preferences
dc.creator.none.fl_str_mv Rossit, Diego Gabriel
Nesmachnow, Sergio
Toutouh, Jamal
Luna, Francisco
author Rossit, Diego Gabriel
author_facet Rossit, Diego Gabriel
Nesmachnow, Sergio
Toutouh, Jamal
Luna, Francisco
author_role author
author2 Nesmachnow, Sergio
Toutouh, Jamal
Luna, Francisco
author2_role author
author
author
dc.subject.none.fl_str_mv SMART CITIES
ENERGY PLANNING
MIXED-INTEGER PROGRAMMING
MULTIOBJECTIVE OPTIMIZATION
SIMULATION
topic SMART CITIES
ENERGY PLANNING
MIXED-INTEGER PROGRAMMING
MULTIOBJECTIVE OPTIMIZATION
SIMULATION
purl_subject.fl_str_mv https://purl.org/becyt/ford/2.11
https://purl.org/becyt/ford/2
dc.description.none.fl_txt_mv Power supply is one of the basic needs in modern smart homes. Computer-aid tools help optimizing energy utilization, contributing to sustainable goals of modern societies. For this purpose, this article presents a mathematical formulation to the household energy planning problem and a specic resolution method to build schedules for using deferrable electric that can reduce the cost of the electricity bill while keeping user satisfaction at a satisfactory level. User satisfaction have a great variability, since it is based on human preferences, thus a stochastic simulation-optimization approach is applied for handling uncertainty in the optimization process. Results over instances based on real-world data show the competitiveness of the proposed approach, which is able to compute dierent compromise solution accounting for the trade-off between these two conficting optimization criteria.
Fil: Rossit, Diego Gabriel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Matemática Bahía Blanca. Universidad Nacional del Sur. Departamento de Matemática. Instituto de Matemática Bahía Blanca; Argentina. Universidad Nacional del Sur. Departamento de Ingeniería; Argentina
Fil: Nesmachnow, Sergio. Universidad de la República; Uruguay
Fil: Toutouh, Jamal. Massachusetts Institute of Technology; Estados Unidos
Fil: Luna, Francisco. Universidad de Málaga; España
International Conference of Production Research - Americas 2020
Bahía Blanca
Argentina
Universidad Nacional del Sur
description Power supply is one of the basic needs in modern smart homes. Computer-aid tools help optimizing energy utilization, contributing to sustainable goals of modern societies. For this purpose, this article presents a mathematical formulation to the household energy planning problem and a specic resolution method to build schedules for using deferrable electric that can reduce the cost of the electricity bill while keeping user satisfaction at a satisfactory level. User satisfaction have a great variability, since it is based on human preferences, thus a stochastic simulation-optimization approach is applied for handling uncertainty in the optimization process. Results over instances based on real-world data show the competitiveness of the proposed approach, which is able to compute dierent compromise solution accounting for the trade-off between these two conficting optimization criteria.
publishDate 2020
dc.date.none.fl_str_mv 2020
dc.type.none.fl_str_mv info:eu-repo/semantics/publishedVersion
info:eu-repo/semantics/conferenceObject
Conferencia
Journal
http://purl.org/coar/resource_type/c_5794
info:ar-repo/semantics/documentoDeConferencia
status_str publishedVersion
format conferenceObject
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/147143
A simulation-optimization approach for the household energy planning problem considering uncertainty in users preferences; International Conference of Production Research - Americas 2020; Bahía Blanca; Argentina; 2020; 40-54
2619-1865
CONICET Digital
CONICET
url http://hdl.handle.net/11336/147143
identifier_str_mv A simulation-optimization approach for the household energy planning problem considering uncertainty in users preferences; International Conference of Production Research - Americas 2020; Bahía Blanca; Argentina; 2020; 40-54
2619-1865
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/https://www.matematica.uns.edu.ar/ipcra/pdf/icpr_americas_2020_proceedings.pdf
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.coverage.none.fl_str_mv Internacional
dc.publisher.none.fl_str_mv Universidad Nacional del Sur
publisher.none.fl_str_mv Universidad Nacional del Sur
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_ 1844613095430815744
score 13.069144

Publicaciones similares