Modelling perception and attitudes towards renewable energy technologies

Detalhes bibliográficos
Autor(a) principal: Ribeiro, Fernando
Data de Publicação: 2018
Outros Autores: Ferreira, Paula Varandas, Araújo, Maria Madalena Teixeira de, Braga, A. C.
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/1822/70678
Resumo: While renewable energy technologies (RET) increase their share in power generation systems worldwide, some questions remain open, namely those concerning the opinion of the populations on new projects of these technologies. Given the long period of planning and large capital sums required by RET and, in some cases, the fact of being subsidized, it is desirable for decision-makers to acknowledge the public opinion and at least perceive if the opinions are rooted on biased perceptions. In this paper we propose a methodology for public perception and awareness assessment, involving an initial phase of data collection by means of a survey, followed by a phase of regression models construction resulting in predictive models of expected perceptions and attitudes towards RET. The models were translated in a free and easy to use computational Excel application and its usefulness was demonstrated for the case of four electricity RET in Portugal: hydro, wind, biomass and solar. (C) 2018 Elsevier Ltd. All rights reserved.
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spelling Modelling perception and attitudes towards renewable energy technologiesRenewable energy technologiesPublic opinionOrdered logistic regressionBinary logistic regressionExcel simulation toolScience & TechnologyWhile renewable energy technologies (RET) increase their share in power generation systems worldwide, some questions remain open, namely those concerning the opinion of the populations on new projects of these technologies. Given the long period of planning and large capital sums required by RET and, in some cases, the fact of being subsidized, it is desirable for decision-makers to acknowledge the public opinion and at least perceive if the opinions are rooted on biased perceptions. In this paper we propose a methodology for public perception and awareness assessment, involving an initial phase of data collection by means of a survey, followed by a phase of regression models construction resulting in predictive models of expected perceptions and attitudes towards RET. The models were translated in a free and easy to use computational Excel application and its usefulness was demonstrated for the case of four electricity RET in Portugal: hydro, wind, biomass and solar. (C) 2018 Elsevier Ltd. All rights reserved.ElsevierUniversidade do MinhoRibeiro, FernandoFerreira, Paula VarandasAraújo, Maria Madalena Teixeira deBraga, A. C.2018-072018-07-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/1822/70678eng0960-14811879-068210.1016/j.renene.2018.01.104https://www.sciencedirect.com/science/article/pii/S0960148118301149info: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:RCAAP2023-07-21T11:56:36Zoai:repositorium.sdum.uminho.pt:1822/70678Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T18:46:13.080060Repositório 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 Modelling perception and attitudes towards renewable energy technologies
title Modelling perception and attitudes towards renewable energy technologies
spellingShingle Modelling perception and attitudes towards renewable energy technologies
Ribeiro, Fernando
Renewable energy technologies
Public opinion
Ordered logistic regression
Binary logistic regression
Excel simulation tool
Science & Technology
title_short Modelling perception and attitudes towards renewable energy technologies
title_full Modelling perception and attitudes towards renewable energy technologies
title_fullStr Modelling perception and attitudes towards renewable energy technologies
title_full_unstemmed Modelling perception and attitudes towards renewable energy technologies
title_sort Modelling perception and attitudes towards renewable energy technologies
author Ribeiro, Fernando
author_facet Ribeiro, Fernando
Ferreira, Paula Varandas
Araújo, Maria Madalena Teixeira de
Braga, A. C.
author_role author
author2 Ferreira, Paula Varandas
Araújo, Maria Madalena Teixeira de
Braga, A. C.
author2_role author
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
Braga, A. C.
dc.subject.por.fl_str_mv Renewable energy technologies
Public opinion
Ordered logistic regression
Binary logistic regression
Excel simulation tool
Science & Technology
topic Renewable energy technologies
Public opinion
Ordered logistic regression
Binary logistic regression
Excel simulation tool
Science & Technology
description While renewable energy technologies (RET) increase their share in power generation systems worldwide, some questions remain open, namely those concerning the opinion of the populations on new projects of these technologies. Given the long period of planning and large capital sums required by RET and, in some cases, the fact of being subsidized, it is desirable for decision-makers to acknowledge the public opinion and at least perceive if the opinions are rooted on biased perceptions. In this paper we propose a methodology for public perception and awareness assessment, involving an initial phase of data collection by means of a survey, followed by a phase of regression models construction resulting in predictive models of expected perceptions and attitudes towards RET. The models were translated in a free and easy to use computational Excel application and its usefulness was demonstrated for the case of four electricity RET in Portugal: hydro, wind, biomass and solar. (C) 2018 Elsevier Ltd. All rights reserved.
publishDate 2018
dc.date.none.fl_str_mv 2018-07
2018-07-01T00:00:00Z
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 http://hdl.handle.net/1822/70678
url http://hdl.handle.net/1822/70678
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 0960-1481
1879-0682
10.1016/j.renene.2018.01.104
https://www.sciencedirect.com/science/article/pii/S0960148118301149
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
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
instacron:RCAAP
instname_str Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron_str RCAAP
institution RCAAP
reponame_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
collection Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository.name.fl_str_mv Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
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