OHL Assessment and Risk Evaluation Based on Environmental and Inspection Data

Detalhes bibliográficos
Autor(a) principal: Azevedo, Francisco de Moura E Castro Ascensão de
Data de Publicação: 2015
Outros Autores: Gomes-Mota,  João, Campos-Pinto, Luis, Machado, Nelio, de Graaff, Susana de Almeida
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10362/20799
Resumo: REN – Rede Eléctrica Nacional, S.A., Portuguese Transmission System Operator (TSO), has been using LiDAR technology in their aerial inspections. The acquired three-dimensional data in this Power Line Maintenance System are automatically processed, with support of the video inspections and geo-referenced systems. The national transmission grid was fully characterized at span level with urbanization and vegetation growth rate indices. The collection of historical data, together with the knowledge of asset characteristics and system operation conditions, is structured in a generalized relational database, extended with a comprehensive set of different environmental, meteorological and geographic data over the years. A methodology to evaluate operational risk was developed, taking into account the probabilistic nature of contingencies and their severity under specific operating conditions. Risk indices provide an insight to operators of the network state and of the constraints that operators face. Different optimization tools are also being developed.
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spelling OHL Assessment and Risk Evaluation Based on Environmental and Inspection DataData baseEnvironmentInspectionOHLPlanningRiskREN – Rede Eléctrica Nacional, S.A., Portuguese Transmission System Operator (TSO), has been using LiDAR technology in their aerial inspections. The acquired three-dimensional data in this Power Line Maintenance System are automatically processed, with support of the video inspections and geo-referenced systems. The national transmission grid was fully characterized at span level with urbanization and vegetation growth rate indices. The collection of historical data, together with the knowledge of asset characteristics and system operation conditions, is structured in a generalized relational database, extended with a comprehensive set of different environmental, meteorological and geographic data over the years. A methodology to evaluate operational risk was developed, taking into account the probabilistic nature of contingencies and their severity under specific operating conditions. Risk indices provide an insight to operators of the network state and of the constraints that operators face. Different optimization tools are also being developed.DI - Departamento de InformáticaNOVALincsRUNAzevedo, Francisco de Moura E Castro Ascensão deGomes-Mota,  JoãoCampos-Pinto, LuisMachado, Neliode Graaff, Susana de Almeida2017-05-30T13:57:47Z2015-092015-09-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10362/20799eng0142-0615PURE: 484408https://doi.org/10.1016/j.ijepes.2014.11.002info: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:RCAAP2024-03-11T04:06:40Zoai:run.unl.pt:10362/20799Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T03:26:29.108659Repositório 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 OHL Assessment and Risk Evaluation Based on Environmental and Inspection Data
title OHL Assessment and Risk Evaluation Based on Environmental and Inspection Data
spellingShingle OHL Assessment and Risk Evaluation Based on Environmental and Inspection Data
Azevedo, Francisco de Moura E Castro Ascensão de
Data base
Environment
Inspection
OHL
Planning
Risk
title_short OHL Assessment and Risk Evaluation Based on Environmental and Inspection Data
title_full OHL Assessment and Risk Evaluation Based on Environmental and Inspection Data
title_fullStr OHL Assessment and Risk Evaluation Based on Environmental and Inspection Data
title_full_unstemmed OHL Assessment and Risk Evaluation Based on Environmental and Inspection Data
title_sort OHL Assessment and Risk Evaluation Based on Environmental and Inspection Data
author Azevedo, Francisco de Moura E Castro Ascensão de
author_facet Azevedo, Francisco de Moura E Castro Ascensão de
Gomes-Mota,  João
Campos-Pinto, Luis
Machado, Nelio
de Graaff, Susana de Almeida
author_role author
author2 Gomes-Mota,  João
Campos-Pinto, Luis
Machado, Nelio
de Graaff, Susana de Almeida
author2_role author
author
author
author
dc.contributor.none.fl_str_mv DI - Departamento de Informática
NOVALincs
RUN
dc.contributor.author.fl_str_mv Azevedo, Francisco de Moura E Castro Ascensão de
Gomes-Mota,  João
Campos-Pinto, Luis
Machado, Nelio
de Graaff, Susana de Almeida
dc.subject.por.fl_str_mv Data base
Environment
Inspection
OHL
Planning
Risk
topic Data base
Environment
Inspection
OHL
Planning
Risk
description REN – Rede Eléctrica Nacional, S.A., Portuguese Transmission System Operator (TSO), has been using LiDAR technology in their aerial inspections. The acquired three-dimensional data in this Power Line Maintenance System are automatically processed, with support of the video inspections and geo-referenced systems. The national transmission grid was fully characterized at span level with urbanization and vegetation growth rate indices. The collection of historical data, together with the knowledge of asset characteristics and system operation conditions, is structured in a generalized relational database, extended with a comprehensive set of different environmental, meteorological and geographic data over the years. A methodology to evaluate operational risk was developed, taking into account the probabilistic nature of contingencies and their severity under specific operating conditions. Risk indices provide an insight to operators of the network state and of the constraints that operators face. Different optimization tools are also being developed.
publishDate 2015
dc.date.none.fl_str_mv 2015-09
2015-09-01T00:00:00Z
2017-05-30T13:57:47Z
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/10362/20799
url http://hdl.handle.net/10362/20799
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 0142-0615
PURE: 484408
https://doi.org/10.1016/j.ijepes.2014.11.002
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.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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