Modelling perception and attitudes towards renewable energy technologies
Autor(a) principal: | |
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Data de Publicação: | 2018 |
Outros Autores: | , , |
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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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 |
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RCAAP |
institution |
RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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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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1799132217580978176 |