A technical and economic approach to multi-level optimization models for electricity demand considering user-supplier interaction

Autores
Bragagnolo, Sergio Nicolás; Vaschetti, Jorge Carlos; Magnago, Fernando
Año de publicación
2021
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
One-level optimization methods have been proposed to optimize a single user’s load profile or a cluster of users in the smart grids. In this work, two two-level optimization methods are studied, one case considering technical requirements (case 1) and another considering economic criterion (case 2). In the upper level, the supplier optimizes the objective function. Meanwhile, at the lower level, users optimize their electrical costs. The proposed methods are based on Genetic Algorithm methods. In this sense, an indirect control is established in which users react to a price signal. Simulation results illustrate that both cases improve the demand profile and increase the retailer profit concerning an unscheduled case. However, when the supplier tries to maximize the profit, some users receive benefits to detriment of others, concluding that the technical approach is preferable to the economic one.
Fil: Bragagnolo, Sergio Nicolás. Universidad Tecnologica Nacional. Facultad Regional Cordoba. Centro de Investigacion Desarrollo y Transferencia de Ingenieria En Energia Electrica.; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba; Argentina
Fil: Vaschetti, Jorge Carlos. Universidad Tecnologica Nacional. Facultad Regional Cordoba. Centro de Investigacion Desarrollo y Transferencia de Ingenieria En Energia Electrica.; Argentina
Fil: Magnago, Fernando. Universidad Nacional de Río Cuarto. Facultad de Ingeniería. Grupo de Electrónica Aplicada; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba; Argentina
Materia
DEMAND RESPONSE
DEMAND SIDE MANAGEMENT
GENETIC ALGORITHM
INDIRECT CONTROL
MULTILEVEL OPTIMIZATION
SMART GRIDS
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/157856
Acceder
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oai_identifier_str oai:ri.conicet.gov.ar:11336/157856
network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling A technical and economic approach to multi-level optimization models for electricity demand considering user-supplier interactionBragagnolo, Sergio NicolásVaschetti, Jorge CarlosMagnago, FernandoDEMAND RESPONSEDEMAND SIDE MANAGEMENTGENETIC ALGORITHMINDIRECT CONTROLMULTILEVEL OPTIMIZATIONSMART GRIDShttps://purl.org/becyt/ford/2.2https://purl.org/becyt/ford/2One-level optimization methods have been proposed to optimize a single user’s load profile or a cluster of users in the smart grids. In this work, two two-level optimization methods are studied, one case considering technical requirements (case 1) and another considering economic criterion (case 2). In the upper level, the supplier optimizes the objective function. Meanwhile, at the lower level, users optimize their electrical costs. The proposed methods are based on Genetic Algorithm methods. In this sense, an indirect control is established in which users react to a price signal. Simulation results illustrate that both cases improve the demand profile and increase the retailer profit concerning an unscheduled case. However, when the supplier tries to maximize the profit, some users receive benefits to detriment of others, concluding that the technical approach is preferable to the economic one.Fil: Bragagnolo, Sergio Nicolás. Universidad Tecnologica Nacional. Facultad Regional Cordoba. Centro de Investigacion Desarrollo y Transferencia de Ingenieria En Energia Electrica.; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba; ArgentinaFil: Vaschetti, Jorge Carlos. Universidad Tecnologica Nacional. Facultad Regional Cordoba. Centro de Investigacion Desarrollo y Transferencia de Ingenieria En Energia Electrica.; ArgentinaFil: Magnago, Fernando. Universidad Nacional de Río Cuarto. Facultad de Ingeniería. Grupo de Electrónica Aplicada; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba; ArgentinaKing Saud University2021-02-17info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/157856Bragagnolo, Sergio Nicolás; Vaschetti, Jorge Carlos; Magnago, Fernando; A technical and economic approach to multi-level optimization models for electricity demand considering user-supplier interaction; King Saud University; Journal of King Saud University - Engineering Sciences; 2021; 17-2-2021; 1-81018-36392213-1558CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/ark/https://linkinghub.elsevier.com/retrieve/pii/S1018363921000210info:eu-repo/semantics/altIdentifier/doi/10.1016/j.jksues.2021.02.005info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-nd/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T10:25:12Zoai:ri.conicet.gov.ar:11336/157856instacron: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 10:25:12.344CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv A technical and economic approach to multi-level optimization models for electricity demand considering user-supplier interaction
title A technical and economic approach to multi-level optimization models for electricity demand considering user-supplier interaction
spellingShingle A technical and economic approach to multi-level optimization models for electricity demand considering user-supplier interaction
Bragagnolo, Sergio Nicolás
DEMAND RESPONSE
DEMAND SIDE MANAGEMENT
GENETIC ALGORITHM
INDIRECT CONTROL
MULTILEVEL OPTIMIZATION
SMART GRIDS
title_short A technical and economic approach to multi-level optimization models for electricity demand considering user-supplier interaction
title_full A technical and economic approach to multi-level optimization models for electricity demand considering user-supplier interaction
title_fullStr A technical and economic approach to multi-level optimization models for electricity demand considering user-supplier interaction
title_full_unstemmed A technical and economic approach to multi-level optimization models for electricity demand considering user-supplier interaction
title_sort A technical and economic approach to multi-level optimization models for electricity demand considering user-supplier interaction
dc.creator.none.fl_str_mv Bragagnolo, Sergio Nicolás
Vaschetti, Jorge Carlos
Magnago, Fernando
author Bragagnolo, Sergio Nicolás
author_facet Bragagnolo, Sergio Nicolás
Vaschetti, Jorge Carlos
Magnago, Fernando
author_role author
author2 Vaschetti, Jorge Carlos
Magnago, Fernando
author2_role author
author
dc.subject.none.fl_str_mv DEMAND RESPONSE
DEMAND SIDE MANAGEMENT
GENETIC ALGORITHM
INDIRECT CONTROL
MULTILEVEL OPTIMIZATION
SMART GRIDS
topic DEMAND RESPONSE
DEMAND SIDE MANAGEMENT
GENETIC ALGORITHM
INDIRECT CONTROL
MULTILEVEL OPTIMIZATION
SMART GRIDS
purl_subject.fl_str_mv https://purl.org/becyt/ford/2.2
https://purl.org/becyt/ford/2
dc.description.none.fl_txt_mv One-level optimization methods have been proposed to optimize a single user’s load profile or a cluster of users in the smart grids. In this work, two two-level optimization methods are studied, one case considering technical requirements (case 1) and another considering economic criterion (case 2). In the upper level, the supplier optimizes the objective function. Meanwhile, at the lower level, users optimize their electrical costs. The proposed methods are based on Genetic Algorithm methods. In this sense, an indirect control is established in which users react to a price signal. Simulation results illustrate that both cases improve the demand profile and increase the retailer profit concerning an unscheduled case. However, when the supplier tries to maximize the profit, some users receive benefits to detriment of others, concluding that the technical approach is preferable to the economic one.
Fil: Bragagnolo, Sergio Nicolás. Universidad Tecnologica Nacional. Facultad Regional Cordoba. Centro de Investigacion Desarrollo y Transferencia de Ingenieria En Energia Electrica.; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba; Argentina
Fil: Vaschetti, Jorge Carlos. Universidad Tecnologica Nacional. Facultad Regional Cordoba. Centro de Investigacion Desarrollo y Transferencia de Ingenieria En Energia Electrica.; Argentina
Fil: Magnago, Fernando. Universidad Nacional de Río Cuarto. Facultad de Ingeniería. Grupo de Electrónica Aplicada; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba; Argentina
description One-level optimization methods have been proposed to optimize a single user’s load profile or a cluster of users in the smart grids. In this work, two two-level optimization methods are studied, one case considering technical requirements (case 1) and another considering economic criterion (case 2). In the upper level, the supplier optimizes the objective function. Meanwhile, at the lower level, users optimize their electrical costs. The proposed methods are based on Genetic Algorithm methods. In this sense, an indirect control is established in which users react to a price signal. Simulation results illustrate that both cases improve the demand profile and increase the retailer profit concerning an unscheduled case. However, when the supplier tries to maximize the profit, some users receive benefits to detriment of others, concluding that the technical approach is preferable to the economic one.
publishDate 2021
dc.date.none.fl_str_mv 2021-02-17
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/11336/157856
Bragagnolo, Sergio Nicolás; Vaschetti, Jorge Carlos; Magnago, Fernando; A technical and economic approach to multi-level optimization models for electricity demand considering user-supplier interaction; King Saud University; Journal of King Saud University - Engineering Sciences; 2021; 17-2-2021; 1-8
1018-3639
2213-1558
CONICET Digital
CONICET
url http://hdl.handle.net/11336/157856
identifier_str_mv Bragagnolo, Sergio Nicolás; Vaschetti, Jorge Carlos; Magnago, Fernando; A technical and economic approach to multi-level optimization models for electricity demand considering user-supplier interaction; King Saud University; Journal of King Saud University - Engineering Sciences; 2021; 17-2-2021; 1-8
1018-3639
2213-1558
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/ark/https://linkinghub.elsevier.com/retrieve/pii/S1018363921000210
info:eu-repo/semantics/altIdentifier/doi/10.1016/j.jksues.2021.02.005
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv King Saud University
publisher.none.fl_str_mv King Saud University
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_ 1844614250439376896
score 13.070432

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