Evaluating future scenarios for the power generation sector using a Multi-Criteria Decision Analysis (MCDA) tool: the Portuguese case

Detalhes bibliográficos
Autor(a) principal: Ribeiro, Fernando
Data de Publicação: 2013
Outros Autores: Ferreira, Paula Varandas, Araújo, Maria Madalena Teixeira de
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: https://hdl.handle.net/1822/26142
Resumo: A Multi-Criteria Decision Analysis (MCDA) tool was designed and used to support the evaluation of different electricity production scenarios. The MCDA tool is implemented in a user-friendly Excel worksheet and uses information obtained from a mixed integer optimization model, to produce a set of optimal schemes under different assumptions. Given the input, the MCDA allowed ranking different scenarios relying on their performance on 13 criteria covering economic, job market, quality of life of local populations, technical and environmental issues. The MCDA tool was used by a group of experts and academics with background in economics, engineering and environment. Regarding the totality of results, both the most and least expensive scenarios ranked first the same amount of times. These scenarios were, respectively, “Coal”, relying mainly in new coal power plants and “Maximum Renewable”, relying mainly in new wind and hydro power facilities. The opinions were divided towards these two solutions with different fundamental characteristics: “Maximum Renewable” with costs higher than “Coal” but leading to substantial reduction of the external energy dependency. Sensitivity analysis suggests that, although the costs are regarded as the most important criterion, those who had different rankings in their preferences have different attitudes towards other criteria.
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spelling Evaluating future scenarios for the power generation sector using a Multi-Criteria Decision Analysis (MCDA) tool: the Portuguese caseMulti-criteria decision toolsEnergy scenariosPower supplyScience & TechnologyA Multi-Criteria Decision Analysis (MCDA) tool was designed and used to support the evaluation of different electricity production scenarios. The MCDA tool is implemented in a user-friendly Excel worksheet and uses information obtained from a mixed integer optimization model, to produce a set of optimal schemes under different assumptions. Given the input, the MCDA allowed ranking different scenarios relying on their performance on 13 criteria covering economic, job market, quality of life of local populations, technical and environmental issues. The MCDA tool was used by a group of experts and academics with background in economics, engineering and environment. Regarding the totality of results, both the most and least expensive scenarios ranked first the same amount of times. These scenarios were, respectively, “Coal”, relying mainly in new coal power plants and “Maximum Renewable”, relying mainly in new wind and hydro power facilities. The opinions were divided towards these two solutions with different fundamental characteristics: “Maximum Renewable” with costs higher than “Coal” but leading to substantial reduction of the external energy dependency. Sensitivity analysis suggests that, although the costs are regarded as the most important criterion, those who had different rankings in their preferences have different attitudes towards other criteria.This work was financed by: the QREN Operational Programme for Competitiveness Factors, the European Union e European Regional Development Fund and National Funds e Portuguese Foundation for Science and Technology, under Project FCOMP-01- 0124-FEDER-011377 and Project Pest-OE/EME/UI0252/2011.ElsevierUniversidade do MinhoRibeiro, FernandoFerreira, Paula VarandasAraújo, Maria Madalena Teixeira de20132013-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttps://hdl.handle.net/1822/26142eng0360-544210.1016/j.energy.2012.12.036http://www.sciencedirect.com/science/article/pii/S0360544213000029info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-07-21T12:41:46Zoai:repositorium.sdum.uminho.pt:1822/26142Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T19:38:50.187161Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Evaluating future scenarios for the power generation sector using a Multi-Criteria Decision Analysis (MCDA) tool: the Portuguese case
title Evaluating future scenarios for the power generation sector using a Multi-Criteria Decision Analysis (MCDA) tool: the Portuguese case
spellingShingle Evaluating future scenarios for the power generation sector using a Multi-Criteria Decision Analysis (MCDA) tool: the Portuguese case
Ribeiro, Fernando
Multi-criteria decision tools
Energy scenarios
Power supply
Science & Technology
title_short Evaluating future scenarios for the power generation sector using a Multi-Criteria Decision Analysis (MCDA) tool: the Portuguese case
title_full Evaluating future scenarios for the power generation sector using a Multi-Criteria Decision Analysis (MCDA) tool: the Portuguese case
title_fullStr Evaluating future scenarios for the power generation sector using a Multi-Criteria Decision Analysis (MCDA) tool: the Portuguese case
title_full_unstemmed Evaluating future scenarios for the power generation sector using a Multi-Criteria Decision Analysis (MCDA) tool: the Portuguese case
title_sort Evaluating future scenarios for the power generation sector using a Multi-Criteria Decision Analysis (MCDA) tool: the Portuguese case
author Ribeiro, Fernando
author_facet Ribeiro, Fernando
Ferreira, Paula Varandas
Araújo, Maria Madalena Teixeira de
author_role author
author2 Ferreira, Paula Varandas
Araújo, Maria Madalena Teixeira de
author2_role author
author
dc.contributor.none.fl_str_mv Universidade do Minho
dc.contributor.author.fl_str_mv Ribeiro, Fernando
Ferreira, Paula Varandas
Araújo, Maria Madalena Teixeira de
dc.subject.por.fl_str_mv Multi-criteria decision tools
Energy scenarios
Power supply
Science & Technology
topic Multi-criteria decision tools
Energy scenarios
Power supply
Science & Technology
description A Multi-Criteria Decision Analysis (MCDA) tool was designed and used to support the evaluation of different electricity production scenarios. The MCDA tool is implemented in a user-friendly Excel worksheet and uses information obtained from a mixed integer optimization model, to produce a set of optimal schemes under different assumptions. Given the input, the MCDA allowed ranking different scenarios relying on their performance on 13 criteria covering economic, job market, quality of life of local populations, technical and environmental issues. The MCDA tool was used by a group of experts and academics with background in economics, engineering and environment. Regarding the totality of results, both the most and least expensive scenarios ranked first the same amount of times. These scenarios were, respectively, “Coal”, relying mainly in new coal power plants and “Maximum Renewable”, relying mainly in new wind and hydro power facilities. The opinions were divided towards these two solutions with different fundamental characteristics: “Maximum Renewable” with costs higher than “Coal” but leading to substantial reduction of the external energy dependency. Sensitivity analysis suggests that, although the costs are regarded as the most important criterion, those who had different rankings in their preferences have different attitudes towards other criteria.
publishDate 2013
dc.date.none.fl_str_mv 2013
2013-01-01T00:00:00Z
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 https://hdl.handle.net/1822/26142
url https://hdl.handle.net/1822/26142
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 0360-5442
10.1016/j.energy.2012.12.036
http://www.sciencedirect.com/science/article/pii/S0360544213000029
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eu_rights_str_mv openAccess
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dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
dc.source.none.fl_str_mv reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
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reponame_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
collection Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
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