Modelo de diagnóstico para projetos de micro e minigeração distribuída de energia fotovoltaica
Autor(a) principal: | |
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Data de Publicação: | 2019 |
Tipo de documento: | Dissertação |
Idioma: | por |
Título da fonte: | Manancial - Repositório Digital da UFSM |
Texto Completo: | http://repositorio.ufsm.br/handle/1/16792 |
Resumo: | Photovoltaic energy has a promising market throughout the world, and Brazil is still at the beginning of its use. One of the options to increase the participation of this energy in the Brazilian energy matrix is with distributed micro and mini-generation (MMGD). To promote MMGD growth in photovoltaic energy, a number of economic, political, environmental and social factors must be present, mainly because the adoption of an innovation is a complex process. Consequently, there is uncertainty about the success that investors can have with the implementation of photovoltaic systems. So the decision about investing in photovoltaic energy must be made on the basis of objective and measurable factors. Given this context, the aim of the study is to propose a diagnostic model for the implementation of distributed micro and mini-generation projects of photovoltaic energy. The diagnosis was developed through a Performance Measurement System (SMD) based on the Key Performance Indicators (KPI) concept, built from Critical Success Factors (FCS) and grouped into six Fundamental Viewpoints (PVF): Economic, Environmental, Market, Political, Social and Technological. The modeling was structured in order to calculate the impact that each PVF has on the PVF set by the Analytic Hierarchy Process (AHP) weighting method. The research was applied with 19 specialists, researchers in photovoltaic energy and 32 investors in photovoltaic energy. As results, the proposed mathematical formulation was able to weigh the indicators and measure the success of the projects. Of the projects diagnosed, 15 reached a Success Index 76%, judged as "Full Success" projects and 17 were judged as "Potential Success" projects. It was found that with the promotion of some KPI, the "Potential Success" projects could go beyond the "Full Success" level, through the reflection promoted by the diagnosis. In addition, a computational tool was built, with off-line availability, so that future investors can evaluate their projects. It concluded that the diagnosis was able to evaluate the MMGD projects and to judge them properly. The main contributions of this work are the identification of success factors and the measurement methodology developed for the diagnostic model. It can serve to generate new diagnostic models in other subjects and to apply this diagnosis in future MMGD projects, providing more precise decisions at the elaboration of photovoltaic projects. |
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Modelo de diagnóstico para projetos de micro e minigeração distribuída de energia fotovoltaicaDiagnostic model for projects of micro and mini generation distributed of photovoltaic energyGestão da energia fotovoltaicaProjetos de energia fotovoltaicaFatores de sucessoModelo de diagnósticoPhotovoltaic energy managementPhotovoltaic energy projectsSuccess factorsDiagnostic modelCNPQ::ENGENHARIAS::ENGENHARIA DE PRODUCAOPhotovoltaic energy has a promising market throughout the world, and Brazil is still at the beginning of its use. One of the options to increase the participation of this energy in the Brazilian energy matrix is with distributed micro and mini-generation (MMGD). To promote MMGD growth in photovoltaic energy, a number of economic, political, environmental and social factors must be present, mainly because the adoption of an innovation is a complex process. Consequently, there is uncertainty about the success that investors can have with the implementation of photovoltaic systems. So the decision about investing in photovoltaic energy must be made on the basis of objective and measurable factors. Given this context, the aim of the study is to propose a diagnostic model for the implementation of distributed micro and mini-generation projects of photovoltaic energy. The diagnosis was developed through a Performance Measurement System (SMD) based on the Key Performance Indicators (KPI) concept, built from Critical Success Factors (FCS) and grouped into six Fundamental Viewpoints (PVF): Economic, Environmental, Market, Political, Social and Technological. The modeling was structured in order to calculate the impact that each PVF has on the PVF set by the Analytic Hierarchy Process (AHP) weighting method. The research was applied with 19 specialists, researchers in photovoltaic energy and 32 investors in photovoltaic energy. As results, the proposed mathematical formulation was able to weigh the indicators and measure the success of the projects. Of the projects diagnosed, 15 reached a Success Index 76%, judged as "Full Success" projects and 17 were judged as "Potential Success" projects. It was found that with the promotion of some KPI, the "Potential Success" projects could go beyond the "Full Success" level, through the reflection promoted by the diagnosis. In addition, a computational tool was built, with off-line availability, so that future investors can evaluate their projects. It concluded that the diagnosis was able to evaluate the MMGD projects and to judge them properly. The main contributions of this work are the identification of success factors and the measurement methodology developed for the diagnostic model. It can serve to generate new diagnostic models in other subjects and to apply this diagnosis in future MMGD projects, providing more precise decisions at the elaboration of photovoltaic projects.Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPESA energia fotovoltaica exibe um mercado promissor em todo o mundo, e o Brasil se encontra ainda no início de seu aproveitamento. Uma das opções para elevar a participação dessa energia na matriz energética brasileira é com a micro e minigeração distribuída (MMGD). Para impulsionar o crescimento da MMGD de energia fotovoltaica, uma série de fatores econômicos, políticos, ambientais e sociais devem se fazer presentes, principalmente porque a adoção de uma inovação é um processo complexo. Por consequência, surge a incerteza sobre o sucesso que os investidores podem ter com a implementação de sistemas fotovoltaicos. Portanto, a decisão sobre investir na energia fotovoltaica deve ser tomada com base em fatores objetivos e mensuráveis. Diante desse contexto, o objetivo do estudo foi propor um modelo de diagnóstico para a implementação de projetos de micro e minigeração distribuída de energia fotovoltaica. O diagnóstico foi desenvolvido por meio de um Sistema de Mensuração de Desempenho (SMD) baseado no conceito de Key Performance Indicators (KPI), construídos a partir de Fatores Críticos de Sucesso (FCS) e agrupados em seis Pontos de Vista Fundamentais (PVF): Econômico, Ambiental, Mercadológico, Político, Social e Tecnológico. A modelagem foi estruturada de modo a calcular o impacto que cada PVF tem perante o conjunto de PVF por meio do método de ponderação Analytic Hierarchy Process (AHP). A pesquisa foi aplicada com 19 especialistas doutores pesquisadores em energia fotovoltaica e 32 investidores em energia fotovoltaica. Como resultados, a formulação matemática proposta foi capaz de ponderar os indicadores e de mensurar o sucesso dos projetos. Dos projetos diagnosticados, 15 alcançaram Índice Global de Sucesso maior que 76%, julgados como projetos de “Sucesso pleno” e 17 foram julgados como projetos de “Sucesso potencial”. Foi verificado que com a promoção de alguns KPI, os projetos de “Sucesso potencial” poderiam ultrapassar para o nível de “Sucesso pleno”, por meio da reflexão promovida pelo diagnóstico. Ademais, foi construída uma ferramenta computacional, com disponibilidade off-line, para que futuros investidores possam avaliar seus projetos. Conclui-se que o diagnóstico foi capaz de avaliar os projetos de MMGD e julgá-los adequadamente. As principais contribuições deste trabalho dizem respeito a identificação dos fatores de sucesso e da metodologia de mensuração desenvolvida para o modelo de diagnóstico. Podendo servir para gerar novos modelos de diagnóstico em outros temas e para a aplicação deste diagnóstico em futuros projetos de MMGD, propiciando decisões mais precisas no momento de elaboração de projetos fotovoltaicos.Universidade Federal de Santa MariaBrasilEngenharia de ProduçãoUFSMPrograma de Pós-Graduação em Engenharia de ProduçãoCentro de TecnologiaSiluk, Julio Cezar Mairessehttp://lattes.cnpq.br/8315298509051752Lacerda, Daniel Pachecohttp://lattes.cnpq.br/6330279254229431Michels, Leandrohttp://lattes.cnpq.br/9232567042677107Neuenfeldt Júnior, Alvaro Luizhttp://lattes.cnpq.br/9694701078826818Rigo, Paula Donaduzzi2019-06-07T15:00:30Z2019-06-07T15:00:30Z2019-02-19info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttp://repositorio.ufsm.br/handle/1/16792porAttribution-NonCommercial-NoDerivatives 4.0 Internationalhttp://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccessreponame:Manancial - Repositório Digital da UFSMinstname:Universidade Federal de Santa Maria (UFSM)instacron:UFSM2019-06-08T06:01:23Zoai:repositorio.ufsm.br:1/16792Biblioteca Digital de Teses e Dissertaçõeshttps://repositorio.ufsm.br/ONGhttps://repositorio.ufsm.br/oai/requestatendimento.sib@ufsm.br||tedebc@gmail.comopendoar:2019-06-08T06:01:23Manancial - Repositório Digital da UFSM - Universidade Federal de Santa Maria (UFSM)false |
dc.title.none.fl_str_mv |
Modelo de diagnóstico para projetos de micro e minigeração distribuída de energia fotovoltaica Diagnostic model for projects of micro and mini generation distributed of photovoltaic energy |
title |
Modelo de diagnóstico para projetos de micro e minigeração distribuída de energia fotovoltaica |
spellingShingle |
Modelo de diagnóstico para projetos de micro e minigeração distribuída de energia fotovoltaica Rigo, Paula Donaduzzi Gestão da energia fotovoltaica Projetos de energia fotovoltaica Fatores de sucesso Modelo de diagnóstico Photovoltaic energy management Photovoltaic energy projects Success factors Diagnostic model CNPQ::ENGENHARIAS::ENGENHARIA DE PRODUCAO |
title_short |
Modelo de diagnóstico para projetos de micro e minigeração distribuída de energia fotovoltaica |
title_full |
Modelo de diagnóstico para projetos de micro e minigeração distribuída de energia fotovoltaica |
title_fullStr |
Modelo de diagnóstico para projetos de micro e minigeração distribuída de energia fotovoltaica |
title_full_unstemmed |
Modelo de diagnóstico para projetos de micro e minigeração distribuída de energia fotovoltaica |
title_sort |
Modelo de diagnóstico para projetos de micro e minigeração distribuída de energia fotovoltaica |
author |
Rigo, Paula Donaduzzi |
author_facet |
Rigo, Paula Donaduzzi |
author_role |
author |
dc.contributor.none.fl_str_mv |
Siluk, Julio Cezar Mairesse http://lattes.cnpq.br/8315298509051752 Lacerda, Daniel Pacheco http://lattes.cnpq.br/6330279254229431 Michels, Leandro http://lattes.cnpq.br/9232567042677107 Neuenfeldt Júnior, Alvaro Luiz http://lattes.cnpq.br/9694701078826818 |
dc.contributor.author.fl_str_mv |
Rigo, Paula Donaduzzi |
dc.subject.por.fl_str_mv |
Gestão da energia fotovoltaica Projetos de energia fotovoltaica Fatores de sucesso Modelo de diagnóstico Photovoltaic energy management Photovoltaic energy projects Success factors Diagnostic model CNPQ::ENGENHARIAS::ENGENHARIA DE PRODUCAO |
topic |
Gestão da energia fotovoltaica Projetos de energia fotovoltaica Fatores de sucesso Modelo de diagnóstico Photovoltaic energy management Photovoltaic energy projects Success factors Diagnostic model CNPQ::ENGENHARIAS::ENGENHARIA DE PRODUCAO |
description |
Photovoltaic energy has a promising market throughout the world, and Brazil is still at the beginning of its use. One of the options to increase the participation of this energy in the Brazilian energy matrix is with distributed micro and mini-generation (MMGD). To promote MMGD growth in photovoltaic energy, a number of economic, political, environmental and social factors must be present, mainly because the adoption of an innovation is a complex process. Consequently, there is uncertainty about the success that investors can have with the implementation of photovoltaic systems. So the decision about investing in photovoltaic energy must be made on the basis of objective and measurable factors. Given this context, the aim of the study is to propose a diagnostic model for the implementation of distributed micro and mini-generation projects of photovoltaic energy. The diagnosis was developed through a Performance Measurement System (SMD) based on the Key Performance Indicators (KPI) concept, built from Critical Success Factors (FCS) and grouped into six Fundamental Viewpoints (PVF): Economic, Environmental, Market, Political, Social and Technological. The modeling was structured in order to calculate the impact that each PVF has on the PVF set by the Analytic Hierarchy Process (AHP) weighting method. The research was applied with 19 specialists, researchers in photovoltaic energy and 32 investors in photovoltaic energy. As results, the proposed mathematical formulation was able to weigh the indicators and measure the success of the projects. Of the projects diagnosed, 15 reached a Success Index 76%, judged as "Full Success" projects and 17 were judged as "Potential Success" projects. It was found that with the promotion of some KPI, the "Potential Success" projects could go beyond the "Full Success" level, through the reflection promoted by the diagnosis. In addition, a computational tool was built, with off-line availability, so that future investors can evaluate their projects. It concluded that the diagnosis was able to evaluate the MMGD projects and to judge them properly. The main contributions of this work are the identification of success factors and the measurement methodology developed for the diagnostic model. It can serve to generate new diagnostic models in other subjects and to apply this diagnosis in future MMGD projects, providing more precise decisions at the elaboration of photovoltaic projects. |
publishDate |
2019 |
dc.date.none.fl_str_mv |
2019-06-07T15:00:30Z 2019-06-07T15:00:30Z 2019-02-19 |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/masterThesis |
format |
masterThesis |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://repositorio.ufsm.br/handle/1/16792 |
url |
http://repositorio.ufsm.br/handle/1/16792 |
dc.language.iso.fl_str_mv |
por |
language |
por |
dc.rights.driver.fl_str_mv |
Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/ info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/ |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Universidade Federal de Santa Maria Brasil Engenharia de Produção UFSM Programa de Pós-Graduação em Engenharia de Produção Centro de Tecnologia |
publisher.none.fl_str_mv |
Universidade Federal de Santa Maria Brasil Engenharia de Produção UFSM Programa de Pós-Graduação em Engenharia de Produção Centro de Tecnologia |
dc.source.none.fl_str_mv |
reponame:Manancial - Repositório Digital da UFSM instname:Universidade Federal de Santa Maria (UFSM) instacron:UFSM |
instname_str |
Universidade Federal de Santa Maria (UFSM) |
instacron_str |
UFSM |
institution |
UFSM |
reponame_str |
Manancial - Repositório Digital da UFSM |
collection |
Manancial - Repositório Digital da UFSM |
repository.name.fl_str_mv |
Manancial - Repositório Digital da UFSM - Universidade Federal de Santa Maria (UFSM) |
repository.mail.fl_str_mv |
atendimento.sib@ufsm.br||tedebc@gmail.com |
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1805922097193549824 |