Use of artificial intelligence in fire safety in solar photovoltaic systems

Detalhes bibliográficos
Autor(a) principal: Brito, Merivaldo de Freitas
Data de Publicação: 2023
Outros Autores: Lima, Lutero Carmo de, Batista, Natasha Esteves
Tipo de documento: Artigo
Idioma: por
Título da fonte: Research, Society and Development
Texto Completo: https://rsdjournal.org/index.php/rsd/article/view/44567
Resumo: Photovoltaic solar energy, especially in the form of Distributed Generation (DG), plays an essential role in the global energy matrix, including the Brazilian scenario. This article aims to analyze the application of Artificial Intelligence (AI) in fire safety in photovoltaic solar systems, focusing on improving and optimizing prevention, detection and response processes to fire-related incidents. Therefore, it becomes essential to implement comprehensive measures, especially intelligent arc detection and rapid shutdown technologies, in order to improve the safety and management of PV plants, whether in residential, commercial and industrial installations or even in solar farms. As a methodology, it adopts a descriptive approach and case study, of a qualitative nature, as well as bibliographical sources in books, articles and online journals, seeking to understand the application of AI in the safety of photovoltaic solar systems, as well as case analysis. specifications that exemplify the effectiveness of AI in preventing and responding to fire incidents in solar installations. Among the results, we seek to demonstrate the contributions of AI in a significant way to maximize safety and reliability for users of solar PV systems, protecting lives and properties. It is concluded that the application of AI in this context contributes not only to the protection of users and their properties, but also to the ongoing sustainability and reliability of solar PV power generation. Therefore, its use must be encouraged and regulated in accordance with current safety standards.
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spelling Use of artificial intelligence in fire safety in solar photovoltaic systemsUso de inteligencia artificial en seguridad contra incendios en sistemas solares fotovoltaicosUso da inteligência artificial na segurança contra incêndio em sistema solar fotovoltaico Artificial intelligenceSolar systemPhotovoltaicSecurityFire.Inteligencia artificialSistema solarFotovoltaicaSeguridadFuego.Inteligência artificialSistema solarFotovoltaicoSegurançaIncêndio.Photovoltaic solar energy, especially in the form of Distributed Generation (DG), plays an essential role in the global energy matrix, including the Brazilian scenario. This article aims to analyze the application of Artificial Intelligence (AI) in fire safety in photovoltaic solar systems, focusing on improving and optimizing prevention, detection and response processes to fire-related incidents. Therefore, it becomes essential to implement comprehensive measures, especially intelligent arc detection and rapid shutdown technologies, in order to improve the safety and management of PV plants, whether in residential, commercial and industrial installations or even in solar farms. As a methodology, it adopts a descriptive approach and case study, of a qualitative nature, as well as bibliographical sources in books, articles and online journals, seeking to understand the application of AI in the safety of photovoltaic solar systems, as well as case analysis. specifications that exemplify the effectiveness of AI in preventing and responding to fire incidents in solar installations. Among the results, we seek to demonstrate the contributions of AI in a significant way to maximize safety and reliability for users of solar PV systems, protecting lives and properties. It is concluded that the application of AI in this context contributes not only to the protection of users and their properties, but also to the ongoing sustainability and reliability of solar PV power generation. Therefore, its use must be encouraged and regulated in accordance with current safety standards.La energía solar fotovoltaica, especialmente en la forma de Generación Distribuida (GD), juega un papel esencial en la matriz energética global, incluido el escenario brasileño. Este artículo tiene como objetivo analizar la aplicación de la Inteligencia Artificial (IA) en la seguridad contra incendios en sistemas solares fotovoltaicos, centrándose en mejorar y optimizar los procesos de prevención, detección y respuesta ante incidentes relacionados con incendios. Por ello, se hace imprescindible implementar medidas integrales, especialmente tecnologías inteligentes de detección de arco y apagado rápido, para mejorar la seguridad y gestión de las plantas fotovoltaicas, ya sea en instalaciones residenciales, comerciales e industriales o incluso en parques solares. Como metodología, adopta un enfoque descriptivo y estudio de casos, de carácter cualitativo, así como fuentes bibliográficas en libros, artículos y revistas en línea, buscando comprender la aplicación de la IA en la seguridad de los sistemas solares fotovoltaicos, así como análisis de casos. análisis especificaciones que ejemplifican la eficacia de la IA en la prevención y respuesta a incidentes de incendio en instalaciones solares. Entre los resultados, buscamos demostrar las contribuciones de la IA de manera significativa para maximizar la seguridad y confiabilidad de los usuarios de sistemas solares fotovoltaicos, protegiendo vidas y propiedades. Se concluye que la aplicación de la IA en este contexto contribuye no sólo a la protección de los usuarios y sus propiedades, sino también a la sostenibilidad y confiabilidad continua de la generación de energía solar fotovoltaica. Por ello, se debe fomentar y regular su uso de acuerdo con las normas de seguridad vigentes.A energia solar fotovoltaica, especialmente na modalidade de Geração Distribuída (GD), desempenha um papel essencial na matriz energética global, incluindo o cenário brasileiro. Este artigo tem como objetivo analisar a aplicação da Inteligência Artificial (IA) na segurança contra incêndios em sistemas solares fotovoltaicos, com foco no aprimoramento e otimização dos processos de prevenção, detecção e resposta aos incidentes relacionados a incêndios. Portanto, torna-se essencial implementar medidas abrangentes, detecção de arco especialmente inteligente e desligamento rápido de tecnologias, a fim de melhorar a segurança e a gestão das plantas FV, seja em instalações residenciais, comerciais e industriais ou mesmo nas fazendas solares. Como metodologia adota uma abordagem descritiva e estudo de caso, de caráter qualitativo, bem como fontes bibliográficas em livros, artigos e periódicos online, busca-se compreender e temática da aplicação da IA na segurança de sistemas solares fotovoltaicos, bem como a análise de casos específicos que exemplifiquem a eficácia da IA na prevenção e resposta a incidentes de incêndio em instalações solares. Dentre os resultados, buscam-se demonstrar as contribuições da IA de forma significativa para maximizar a segurança e a confiabilidade aos usuários de sistemas solares FV, protegendo vidas e propriedades. Conclui-se que a aplicação da IA nesse contexto contribui não apenas para a proteção dos usuários e suas propriedades, mas também para a sustentabilidade e confiabilidade contínuas da geração de energia solar FV. Sendo assim, a sua utilização deve ser incentivada e regulamentada de acordo com as normas de segurança em vigor.Research, Society and Development2023-12-26info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://rsdjournal.org/index.php/rsd/article/view/4456710.33448/rsd-v12i14.44567Research, Society and Development; Vol. 12 No. 14; e106121444567Research, Society and Development; Vol. 12 Núm. 14; e106121444567Research, Society and Development; v. 12 n. 14; e1061214445672525-3409reponame:Research, Society and Developmentinstname:Universidade Federal de Itajubá (UNIFEI)instacron:UNIFEIporhttps://rsdjournal.org/index.php/rsd/article/view/44567/35673Copyright (c) 2023 Merivaldo de Freitas Brito; Lutero Carmo de Lima; Natasha Esteves Batistahttps://creativecommons.org/licenses/by/4.0info:eu-repo/semantics/openAccessBrito, Merivaldo de Freitas Lima, Lutero Carmo de Batista, Natasha Esteves2024-01-01T11:23:38Zoai:ojs.pkp.sfu.ca:article/44567Revistahttps://rsdjournal.org/index.php/rsd/indexPUBhttps://rsdjournal.org/index.php/rsd/oairsd.articles@gmail.com2525-34092525-3409opendoar:2024-01-01T11:23:38Research, Society and Development - Universidade Federal de Itajubá (UNIFEI)false
dc.title.none.fl_str_mv Use of artificial intelligence in fire safety in solar photovoltaic systems
Uso de inteligencia artificial en seguridad contra incendios en sistemas solares fotovoltaicos
Uso da inteligência artificial na segurança contra incêndio em sistema solar fotovoltaico
title Use of artificial intelligence in fire safety in solar photovoltaic systems
spellingShingle Use of artificial intelligence in fire safety in solar photovoltaic systems
Brito, Merivaldo de Freitas
Artificial intelligence
Solar system
Photovoltaic
Security
Fire.
Inteligencia artificial
Sistema solar
Fotovoltaica
Seguridad
Fuego.
Inteligência artificial
Sistema solar
Fotovoltaico
Segurança
Incêndio.
title_short Use of artificial intelligence in fire safety in solar photovoltaic systems
title_full Use of artificial intelligence in fire safety in solar photovoltaic systems
title_fullStr Use of artificial intelligence in fire safety in solar photovoltaic systems
title_full_unstemmed Use of artificial intelligence in fire safety in solar photovoltaic systems
title_sort Use of artificial intelligence in fire safety in solar photovoltaic systems
author Brito, Merivaldo de Freitas
author_facet Brito, Merivaldo de Freitas
Lima, Lutero Carmo de
Batista, Natasha Esteves
author_role author
author2 Lima, Lutero Carmo de
Batista, Natasha Esteves
author2_role author
author
dc.contributor.author.fl_str_mv Brito, Merivaldo de Freitas
Lima, Lutero Carmo de
Batista, Natasha Esteves
dc.subject.por.fl_str_mv Artificial intelligence
Solar system
Photovoltaic
Security
Fire.
Inteligencia artificial
Sistema solar
Fotovoltaica
Seguridad
Fuego.
Inteligência artificial
Sistema solar
Fotovoltaico
Segurança
Incêndio.
topic Artificial intelligence
Solar system
Photovoltaic
Security
Fire.
Inteligencia artificial
Sistema solar
Fotovoltaica
Seguridad
Fuego.
Inteligência artificial
Sistema solar
Fotovoltaico
Segurança
Incêndio.
description Photovoltaic solar energy, especially in the form of Distributed Generation (DG), plays an essential role in the global energy matrix, including the Brazilian scenario. This article aims to analyze the application of Artificial Intelligence (AI) in fire safety in photovoltaic solar systems, focusing on improving and optimizing prevention, detection and response processes to fire-related incidents. Therefore, it becomes essential to implement comprehensive measures, especially intelligent arc detection and rapid shutdown technologies, in order to improve the safety and management of PV plants, whether in residential, commercial and industrial installations or even in solar farms. As a methodology, it adopts a descriptive approach and case study, of a qualitative nature, as well as bibliographical sources in books, articles and online journals, seeking to understand the application of AI in the safety of photovoltaic solar systems, as well as case analysis. specifications that exemplify the effectiveness of AI in preventing and responding to fire incidents in solar installations. Among the results, we seek to demonstrate the contributions of AI in a significant way to maximize safety and reliability for users of solar PV systems, protecting lives and properties. It is concluded that the application of AI in this context contributes not only to the protection of users and their properties, but also to the ongoing sustainability and reliability of solar PV power generation. Therefore, its use must be encouraged and regulated in accordance with current safety standards.
publishDate 2023
dc.date.none.fl_str_mv 2023-12-26
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv https://rsdjournal.org/index.php/rsd/article/view/44567
10.33448/rsd-v12i14.44567
url https://rsdjournal.org/index.php/rsd/article/view/44567
identifier_str_mv 10.33448/rsd-v12i14.44567
dc.language.iso.fl_str_mv por
language por
dc.relation.none.fl_str_mv https://rsdjournal.org/index.php/rsd/article/view/44567/35673
dc.rights.driver.fl_str_mv Copyright (c) 2023 Merivaldo de Freitas Brito; Lutero Carmo de Lima; Natasha Esteves Batista
https://creativecommons.org/licenses/by/4.0
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Copyright (c) 2023 Merivaldo de Freitas Brito; Lutero Carmo de Lima; Natasha Esteves Batista
https://creativecommons.org/licenses/by/4.0
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Research, Society and Development
publisher.none.fl_str_mv Research, Society and Development
dc.source.none.fl_str_mv Research, Society and Development; Vol. 12 No. 14; e106121444567
Research, Society and Development; Vol. 12 Núm. 14; e106121444567
Research, Society and Development; v. 12 n. 14; e106121444567
2525-3409
reponame:Research, Society and Development
instname:Universidade Federal de Itajubá (UNIFEI)
instacron:UNIFEI
instname_str Universidade Federal de Itajubá (UNIFEI)
instacron_str UNIFEI
institution UNIFEI
reponame_str Research, Society and Development
collection Research, Society and Development
repository.name.fl_str_mv Research, Society and Development - Universidade Federal de Itajubá (UNIFEI)
repository.mail.fl_str_mv rsd.articles@gmail.com
_version_ 1797052636030042112

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