A Hybrid Multi-Criteria Methodology for Solving the Sustainable Dispatch Problem

Detalhes bibliográficos
Autor(a) principal: Santos Martins, Andrea Camila dos [UNESP]
Data de Publicação: 2020
Outros Autores: Roberto Balbo, Antonio [UNESP], Jones, Dylan, Nepomuceno, Leonardo [UNESP], Martins Soler, Edilaine [UNESP], Cassia Baptista, Edmea [UNESP]
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da UNESP
Texto Completo: http://dx.doi.org/10.3390/su12176780
http://hdl.handle.net/11449/209471
Resumo: Wind energy is becoming an increasingly substantial component of many nations' energy portfolios. The intermittent nature of wind energy is traded off in a multi-objective sense against its environmental benefits when compared to conventional thermal energy sources. This gives rise to the multi-criteria sustainable dispatch problem considered in this paper. A relevant multi-objective model is formulated considering both environmental and economic criteria as well as ensuring adequate production levels. The techniques of weighted goal programming (WGP) and the progressive bounded constraint method (PBC) are combined in a novel manner in order to overcome computational challenges associated with the sinusoidal nature of the model. This allows the generation of a representative set of Pareto efficient solutions. The proposed methodology is demonstrated on a test set of relevant examples, and conclusions are drawn from both methodological and application perspectives. The results provide a quantification of the economic and environmental benefits of added wind power to a solely thermal system. However, a trade-off between the levels of economic versus environmental benefits gained is also demonstrated.
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spelling A Hybrid Multi-Criteria Methodology for Solving the Sustainable Dispatch Problemwind energymulti-objective optimizationweighted goal programmingprogressive bounded constraintWind energy is becoming an increasingly substantial component of many nations' energy portfolios. The intermittent nature of wind energy is traded off in a multi-objective sense against its environmental benefits when compared to conventional thermal energy sources. This gives rise to the multi-criteria sustainable dispatch problem considered in this paper. A relevant multi-objective model is formulated considering both environmental and economic criteria as well as ensuring adequate production levels. The techniques of weighted goal programming (WGP) and the progressive bounded constraint method (PBC) are combined in a novel manner in order to overcome computational challenges associated with the sinusoidal nature of the model. This allows the generation of a representative set of Pareto efficient solutions. The proposed methodology is demonstrated on a test set of relevant examples, and conclusions are drawn from both methodological and application perspectives. The results provide a quantification of the economic and environmental benefits of added wind power to a solely thermal system. However, a trade-off between the levels of economic versus environmental benefits gained is also demonstrated.PROPG-UNESPUniv Estadual Paulista, Fac Engn FEB, Dept Elect Engn, BR-17033360 Bauru, SP, BrazilUniv Estadual Paulista, Fac Sci FC, Dept Math, BR-17033360 Bauru, SP, BrazilUniv Portsmouth, Ctr Operat Res & Logist, Sch Math & Phys, Portsmouth PO1 3HF, Hants, EnglandUniv Estadual Paulista, Fac Engn FEB, Dept Elect Engn, BR-17033360 Bauru, SP, BrazilUniv Estadual Paulista, Fac Sci FC, Dept Math, BR-17033360 Bauru, SP, BrazilPROPG-UNESP: PGEE/2018MdpiUniversidade Estadual Paulista (Unesp)Univ PortsmouthSantos Martins, Andrea Camila dos [UNESP]Roberto Balbo, Antonio [UNESP]Jones, DylanNepomuceno, Leonardo [UNESP]Martins Soler, Edilaine [UNESP]Cassia Baptista, Edmea [UNESP]2021-06-25T12:19:41Z2021-06-25T12:19:41Z2020-09-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article20http://dx.doi.org/10.3390/su12176780Sustainability. Basel: Mdpi, v. 12, n. 17, 20 p., 2020.http://hdl.handle.net/11449/20947110.3390/su12176780WOS:000570336500001Web of Sciencereponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengSustainabilityinfo:eu-repo/semantics/openAccess2024-06-28T13:34:24Zoai:repositorio.unesp.br:11449/209471Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T21:08:31.455429Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false
dc.title.none.fl_str_mv A Hybrid Multi-Criteria Methodology for Solving the Sustainable Dispatch Problem
title A Hybrid Multi-Criteria Methodology for Solving the Sustainable Dispatch Problem
spellingShingle A Hybrid Multi-Criteria Methodology for Solving the Sustainable Dispatch Problem
Santos Martins, Andrea Camila dos [UNESP]
wind energy
multi-objective optimization
weighted goal programming
progressive bounded constraint
title_short A Hybrid Multi-Criteria Methodology for Solving the Sustainable Dispatch Problem
title_full A Hybrid Multi-Criteria Methodology for Solving the Sustainable Dispatch Problem
title_fullStr A Hybrid Multi-Criteria Methodology for Solving the Sustainable Dispatch Problem
title_full_unstemmed A Hybrid Multi-Criteria Methodology for Solving the Sustainable Dispatch Problem
title_sort A Hybrid Multi-Criteria Methodology for Solving the Sustainable Dispatch Problem
author Santos Martins, Andrea Camila dos [UNESP]
author_facet Santos Martins, Andrea Camila dos [UNESP]
Roberto Balbo, Antonio [UNESP]
Jones, Dylan
Nepomuceno, Leonardo [UNESP]
Martins Soler, Edilaine [UNESP]
Cassia Baptista, Edmea [UNESP]
author_role author
author2 Roberto Balbo, Antonio [UNESP]
Jones, Dylan
Nepomuceno, Leonardo [UNESP]
Martins Soler, Edilaine [UNESP]
Cassia Baptista, Edmea [UNESP]
author2_role author
author
author
author
author
dc.contributor.none.fl_str_mv Universidade Estadual Paulista (Unesp)
Univ Portsmouth
dc.contributor.author.fl_str_mv Santos Martins, Andrea Camila dos [UNESP]
Roberto Balbo, Antonio [UNESP]
Jones, Dylan
Nepomuceno, Leonardo [UNESP]
Martins Soler, Edilaine [UNESP]
Cassia Baptista, Edmea [UNESP]
dc.subject.por.fl_str_mv wind energy
multi-objective optimization
weighted goal programming
progressive bounded constraint
topic wind energy
multi-objective optimization
weighted goal programming
progressive bounded constraint
description Wind energy is becoming an increasingly substantial component of many nations' energy portfolios. The intermittent nature of wind energy is traded off in a multi-objective sense against its environmental benefits when compared to conventional thermal energy sources. This gives rise to the multi-criteria sustainable dispatch problem considered in this paper. A relevant multi-objective model is formulated considering both environmental and economic criteria as well as ensuring adequate production levels. The techniques of weighted goal programming (WGP) and the progressive bounded constraint method (PBC) are combined in a novel manner in order to overcome computational challenges associated with the sinusoidal nature of the model. This allows the generation of a representative set of Pareto efficient solutions. The proposed methodology is demonstrated on a test set of relevant examples, and conclusions are drawn from both methodological and application perspectives. The results provide a quantification of the economic and environmental benefits of added wind power to a solely thermal system. However, a trade-off between the levels of economic versus environmental benefits gained is also demonstrated.
publishDate 2020
dc.date.none.fl_str_mv 2020-09-01
2021-06-25T12:19:41Z
2021-06-25T12:19:41Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://dx.doi.org/10.3390/su12176780
Sustainability. Basel: Mdpi, v. 12, n. 17, 20 p., 2020.
http://hdl.handle.net/11449/209471
10.3390/su12176780
WOS:000570336500001
url http://dx.doi.org/10.3390/su12176780
http://hdl.handle.net/11449/209471
identifier_str_mv Sustainability. Basel: Mdpi, v. 12, n. 17, 20 p., 2020.
10.3390/su12176780
WOS:000570336500001
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Sustainability
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 20
dc.publisher.none.fl_str_mv Mdpi
publisher.none.fl_str_mv Mdpi
dc.source.none.fl_str_mv Web of Science
reponame:Repositório Institucional da UNESP
instname:Universidade Estadual Paulista (UNESP)
instacron:UNESP
instname_str Universidade Estadual Paulista (UNESP)
instacron_str UNESP
institution UNESP
reponame_str Repositório Institucional da UNESP
collection Repositório Institucional da UNESP
repository.name.fl_str_mv Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)
repository.mail.fl_str_mv
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