Scheduling deferrable electric appliances in Smart Homes: a bi-objective stochastic optimization approach

Autores
Rossit, Diego Gabriel; Nesmachnow, Sergio; Toutouh, Jamal; Luna, Francisco
Año de publicación
2021
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
In the last decades, cities have increased the number of activities and services that depends on an efficient and reliable electricity service. In particular, households have had a sustained increase of electricity consumption to perform many residential activities. Thus, providing efficient methods to enhance the decision making processes in demand-side management is crucial for achieving a more sustainable usage of the available resources. In this line of work, this article presents an optimization model to schedule deferrable appliances in households, which simultaneously optimize two conflicting objectives: the minimization of the cost of electricity bill and the maximization of users satisfaction with the consumed energy. Since users satisfaction is based on human preferences, it is subjected to a great variability and, thus, stochastic resolution methods have to be applied to solve the proposed model. In turn, a maximum allowable power consumption value is included as constraint, to account for the maximum power contracted for each household or building. Two different algorithms are proposed: a simulation-optimization approach and a greedy heuristic. Both methods are evaluated over problem instances based on real-world data, accounting for different household types. The obtained results show the competitiveness of the proposed approach, which are able to compute different compromising solutions accounting for the trade-off between these two conflicting optimization criteria in reasonable computing times. The simulation-optimization obtains better solutions, outperforming and dominating the greedy heuristic in all considered scenarios.
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. Universidad de Málaga. Departamento de Lenguajes y Ciencias de la Computación; España
Fil: Luna, Francisco. Universidad de Málaga. Departamento de Lenguajes y Ciencias de la Computación; España
Materia
SMART CITIES
SMART HOMES
URBAN DATA ANALYSIS
HOUSEHOLD ENERGY PLANNING
MIXED-INTEGER PROGRAMMING
MONTE CARLO SIMULATION
BI-OBJECTIVE OPTIMIZATION
GREEDY HEURISTIC
STOCHASTIC OPTIMIZATION
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:11336/152119
Acceder
id CONICETDig_2ad1e4d5b576c90a2ea6ed68e37e85be
oai_identifier_str oai:ri.conicet.gov.ar:11336/152119
network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling Scheduling deferrable electric appliances in Smart Homes: a bi-objective stochastic optimization approachRossit, Diego GabrielNesmachnow, SergioToutouh, JamalLuna, FranciscoSMART CITIESSMART HOMESURBAN DATA ANALYSISHOUSEHOLD ENERGY PLANNINGMIXED-INTEGER PROGRAMMINGMONTE CARLO SIMULATIONBI-OBJECTIVE OPTIMIZATIONGREEDY HEURISTICSTOCHASTIC OPTIMIZATIONhttps://purl.org/becyt/ford/2.11https://purl.org/becyt/ford/2In the last decades, cities have increased the number of activities and services that depends on an efficient and reliable electricity service. In particular, households have had a sustained increase of electricity consumption to perform many residential activities. Thus, providing efficient methods to enhance the decision making processes in demand-side management is crucial for achieving a more sustainable usage of the available resources. In this line of work, this article presents an optimization model to schedule deferrable appliances in households, which simultaneously optimize two conflicting objectives: the minimization of the cost of electricity bill and the maximization of users satisfaction with the consumed energy. Since users satisfaction is based on human preferences, it is subjected to a great variability and, thus, stochastic resolution methods have to be applied to solve the proposed model. In turn, a maximum allowable power consumption value is included as constraint, to account for the maximum power contracted for each household or building. Two different algorithms are proposed: a simulation-optimization approach and a greedy heuristic. Both methods are evaluated over problem instances based on real-world data, accounting for different household types. The obtained results show the competitiveness of the proposed approach, which are able to compute different compromising solutions accounting for the trade-off between these two conflicting optimization criteria in reasonable computing times. The simulation-optimization obtains better solutions, outperforming and dominating the greedy heuristic in all considered scenarios.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. Universidad de Málaga. Departamento de Lenguajes y Ciencias de la Computación; EspañaFil: Luna, Francisco. Universidad de Málaga. Departamento de Lenguajes y Ciencias de la Computación; EspañaAmerican Institute of Mathematical Sciences2021-11-08info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/152119Rossit, Diego Gabriel; Nesmachnow, Sergio; Toutouh, Jamal; Luna, Francisco; Scheduling deferrable electric appliances in Smart Homes: a bi-objective stochastic optimization approach; American Institute of Mathematical Sciences; Mathematical Biosciences And Engineering; 19; 1; 8-11-2021; 34-651547-1063CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/https://www.aimspress.com/article/doi/10.3934/mbe.2022002info:eu-repo/semantics/altIdentifier/doi/10.3934/mbe.2022002info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T10:21:04Zoai:ri.conicet.gov.ar:11336/152119instacron: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 10:21:05.007CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Scheduling deferrable electric appliances in Smart Homes: a bi-objective stochastic optimization approach
title Scheduling deferrable electric appliances in Smart Homes: a bi-objective stochastic optimization approach
spellingShingle Scheduling deferrable electric appliances in Smart Homes: a bi-objective stochastic optimization approach
Rossit, Diego Gabriel
SMART CITIES
SMART HOMES
URBAN DATA ANALYSIS
HOUSEHOLD ENERGY PLANNING
MIXED-INTEGER PROGRAMMING
MONTE CARLO SIMULATION
BI-OBJECTIVE OPTIMIZATION
GREEDY HEURISTIC
STOCHASTIC OPTIMIZATION
title_short Scheduling deferrable electric appliances in Smart Homes: a bi-objective stochastic optimization approach
title_full Scheduling deferrable electric appliances in Smart Homes: a bi-objective stochastic optimization approach
title_fullStr Scheduling deferrable electric appliances in Smart Homes: a bi-objective stochastic optimization approach
title_full_unstemmed Scheduling deferrable electric appliances in Smart Homes: a bi-objective stochastic optimization approach
title_sort Scheduling deferrable electric appliances in Smart Homes: a bi-objective stochastic optimization approach
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
SMART HOMES
URBAN DATA ANALYSIS
HOUSEHOLD ENERGY PLANNING
MIXED-INTEGER PROGRAMMING
MONTE CARLO SIMULATION
BI-OBJECTIVE OPTIMIZATION
GREEDY HEURISTIC
STOCHASTIC OPTIMIZATION
topic SMART CITIES
SMART HOMES
URBAN DATA ANALYSIS
HOUSEHOLD ENERGY PLANNING
MIXED-INTEGER PROGRAMMING
MONTE CARLO SIMULATION
BI-OBJECTIVE OPTIMIZATION
GREEDY HEURISTIC
STOCHASTIC OPTIMIZATION
purl_subject.fl_str_mv https://purl.org/becyt/ford/2.11
https://purl.org/becyt/ford/2
dc.description.none.fl_txt_mv In the last decades, cities have increased the number of activities and services that depends on an efficient and reliable electricity service. In particular, households have had a sustained increase of electricity consumption to perform many residential activities. Thus, providing efficient methods to enhance the decision making processes in demand-side management is crucial for achieving a more sustainable usage of the available resources. In this line of work, this article presents an optimization model to schedule deferrable appliances in households, which simultaneously optimize two conflicting objectives: the minimization of the cost of electricity bill and the maximization of users satisfaction with the consumed energy. Since users satisfaction is based on human preferences, it is subjected to a great variability and, thus, stochastic resolution methods have to be applied to solve the proposed model. In turn, a maximum allowable power consumption value is included as constraint, to account for the maximum power contracted for each household or building. Two different algorithms are proposed: a simulation-optimization approach and a greedy heuristic. Both methods are evaluated over problem instances based on real-world data, accounting for different household types. The obtained results show the competitiveness of the proposed approach, which are able to compute different compromising solutions accounting for the trade-off between these two conflicting optimization criteria in reasonable computing times. The simulation-optimization obtains better solutions, outperforming and dominating the greedy heuristic in all considered scenarios.
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. Universidad de Málaga. Departamento de Lenguajes y Ciencias de la Computación; España
Fil: Luna, Francisco. Universidad de Málaga. Departamento de Lenguajes y Ciencias de la Computación; España
description In the last decades, cities have increased the number of activities and services that depends on an efficient and reliable electricity service. In particular, households have had a sustained increase of electricity consumption to perform many residential activities. Thus, providing efficient methods to enhance the decision making processes in demand-side management is crucial for achieving a more sustainable usage of the available resources. In this line of work, this article presents an optimization model to schedule deferrable appliances in households, which simultaneously optimize two conflicting objectives: the minimization of the cost of electricity bill and the maximization of users satisfaction with the consumed energy. Since users satisfaction is based on human preferences, it is subjected to a great variability and, thus, stochastic resolution methods have to be applied to solve the proposed model. In turn, a maximum allowable power consumption value is included as constraint, to account for the maximum power contracted for each household or building. Two different algorithms are proposed: a simulation-optimization approach and a greedy heuristic. Both methods are evaluated over problem instances based on real-world data, accounting for different household types. The obtained results show the competitiveness of the proposed approach, which are able to compute different compromising solutions accounting for the trade-off between these two conflicting optimization criteria in reasonable computing times. The simulation-optimization obtains better solutions, outperforming and dominating the greedy heuristic in all considered scenarios.
publishDate 2021
dc.date.none.fl_str_mv 2021-11-08
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/11336/152119
Rossit, Diego Gabriel; Nesmachnow, Sergio; Toutouh, Jamal; Luna, Francisco; Scheduling deferrable electric appliances in Smart Homes: a bi-objective stochastic optimization approach; American Institute of Mathematical Sciences; Mathematical Biosciences And Engineering; 19; 1; 8-11-2021; 34-65
1547-1063
CONICET Digital
CONICET
url http://hdl.handle.net/11336/152119
identifier_str_mv Rossit, Diego Gabriel; Nesmachnow, Sergio; Toutouh, Jamal; Luna, Francisco; Scheduling deferrable electric appliances in Smart Homes: a bi-objective stochastic optimization approach; American Institute of Mathematical Sciences; Mathematical Biosciences And Engineering; 19; 1; 8-11-2021; 34-65
1547-1063
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.aimspress.com/article/doi/10.3934/mbe.2022002
info:eu-repo/semantics/altIdentifier/doi/10.3934/mbe.2022002
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
dc.publisher.none.fl_str_mv American Institute of Mathematical Sciences
publisher.none.fl_str_mv American Institute of Mathematical Sciences
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_ 1844614197240922112
score 13.069144

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