Risk mitigation approaches for improved resilience in distribution networks
Autor(a) principal: | |
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Data de Publicação: | 2020 |
Outros Autores: | |
Tipo de documento: | Artigo de conferência |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UNESP |
Texto Completo: | http://dx.doi.org/10.1109/TDLA47668.2020.9326210 http://hdl.handle.net/11449/205882 |
Resumo: | traditionally the risk analysis framework comprises two steps: risk assessment and risk mitigation. The tracking of operating conditions for each feeder section of a distribution network using the prediction of hourly risk levels and monthly accumulated risks corresponds to the first step. In this paper, we evaluate the use of two modern approaches to risk mitigation, one commonly named as automatic fault location, isolation and service restoration (FLISR), and other as demand response management (DRM). Since the implementation of these approaches depends on distribution automation, the control actions to mitigate the risk are carried out through the distribution management system. Results reveal advantages in the implementation of FLISR and DRM for improving the distribution network resilience. The developed visualization tool with georeferenced data from a real-world distribution network supports the achieved benefits. |
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Risk mitigation approaches for improved resilience in distribution networksDemand Response Management (DRM)Fault LocationIsolation and Service Restoration (FLISR)Power Distribution SystemPredictive Risk AssessmentResilienceRisk Mitigationtraditionally the risk analysis framework comprises two steps: risk assessment and risk mitigation. The tracking of operating conditions for each feeder section of a distribution network using the prediction of hourly risk levels and monthly accumulated risks corresponds to the first step. In this paper, we evaluate the use of two modern approaches to risk mitigation, one commonly named as automatic fault location, isolation and service restoration (FLISR), and other as demand response management (DRM). Since the implementation of these approaches depends on distribution automation, the control actions to mitigate the risk are carried out through the distribution management system. Results reveal advantages in the implementation of FLISR and DRM for improving the distribution network resilience. The developed visualization tool with georeferenced data from a real-world distribution network supports the achieved benefits.São Paulo State University - UNESP Dep. of Electrical EngineeringTexas AM University Dep. of Electrical and Computer EngineeringSão Paulo State University - UNESP Dep. of Electrical EngineeringUniversidade Estadual Paulista (Unesp)Dep. of Electrical and Computer EngineeringLeite, Jonatas Boas [UNESP]Kezunovic, Mladen2021-06-25T10:22:49Z2021-06-25T10:22:49Z2020-09-28info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/conferenceObjecthttp://dx.doi.org/10.1109/TDLA47668.2020.93262102020 IEEE PES Transmission and Distribution Conference and Exhibition - Latin America, T and D LA 2020.http://hdl.handle.net/11449/20588210.1109/TDLA47668.2020.93262102-s2.0-85100862008Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPeng2020 IEEE PES Transmission and Distribution Conference and Exhibition - Latin America, T and D LA 2020info:eu-repo/semantics/openAccess2021-10-22T19:44:33Zoai:repositorio.unesp.br:11449/205882Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462021-10-22T19:44:33Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
Risk mitigation approaches for improved resilience in distribution networks |
title |
Risk mitigation approaches for improved resilience in distribution networks |
spellingShingle |
Risk mitigation approaches for improved resilience in distribution networks Leite, Jonatas Boas [UNESP] Demand Response Management (DRM) Fault Location Isolation and Service Restoration (FLISR) Power Distribution System Predictive Risk Assessment Resilience Risk Mitigation |
title_short |
Risk mitigation approaches for improved resilience in distribution networks |
title_full |
Risk mitigation approaches for improved resilience in distribution networks |
title_fullStr |
Risk mitigation approaches for improved resilience in distribution networks |
title_full_unstemmed |
Risk mitigation approaches for improved resilience in distribution networks |
title_sort |
Risk mitigation approaches for improved resilience in distribution networks |
author |
Leite, Jonatas Boas [UNESP] |
author_facet |
Leite, Jonatas Boas [UNESP] Kezunovic, Mladen |
author_role |
author |
author2 |
Kezunovic, Mladen |
author2_role |
author |
dc.contributor.none.fl_str_mv |
Universidade Estadual Paulista (Unesp) Dep. of Electrical and Computer Engineering |
dc.contributor.author.fl_str_mv |
Leite, Jonatas Boas [UNESP] Kezunovic, Mladen |
dc.subject.por.fl_str_mv |
Demand Response Management (DRM) Fault Location Isolation and Service Restoration (FLISR) Power Distribution System Predictive Risk Assessment Resilience Risk Mitigation |
topic |
Demand Response Management (DRM) Fault Location Isolation and Service Restoration (FLISR) Power Distribution System Predictive Risk Assessment Resilience Risk Mitigation |
description |
traditionally the risk analysis framework comprises two steps: risk assessment and risk mitigation. The tracking of operating conditions for each feeder section of a distribution network using the prediction of hourly risk levels and monthly accumulated risks corresponds to the first step. In this paper, we evaluate the use of two modern approaches to risk mitigation, one commonly named as automatic fault location, isolation and service restoration (FLISR), and other as demand response management (DRM). Since the implementation of these approaches depends on distribution automation, the control actions to mitigate the risk are carried out through the distribution management system. Results reveal advantages in the implementation of FLISR and DRM for improving the distribution network resilience. The developed visualization tool with georeferenced data from a real-world distribution network supports the achieved benefits. |
publishDate |
2020 |
dc.date.none.fl_str_mv |
2020-09-28 2021-06-25T10:22:49Z 2021-06-25T10:22:49Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/conferenceObject |
format |
conferenceObject |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://dx.doi.org/10.1109/TDLA47668.2020.9326210 2020 IEEE PES Transmission and Distribution Conference and Exhibition - Latin America, T and D LA 2020. http://hdl.handle.net/11449/205882 10.1109/TDLA47668.2020.9326210 2-s2.0-85100862008 |
url |
http://dx.doi.org/10.1109/TDLA47668.2020.9326210 http://hdl.handle.net/11449/205882 |
identifier_str_mv |
2020 IEEE PES Transmission and Distribution Conference and Exhibition - Latin America, T and D LA 2020. 10.1109/TDLA47668.2020.9326210 2-s2.0-85100862008 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
2020 IEEE PES Transmission and Distribution Conference and Exhibition - Latin America, T and D LA 2020 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.source.none.fl_str_mv |
Scopus reponame:Repositório Institucional da UNESP instname:Universidade Estadual Paulista (UNESP) instacron:UNESP |
instname_str |
Universidade Estadual Paulista (UNESP) |
instacron_str |
UNESP |
institution |
UNESP |
reponame_str |
Repositório Institucional da UNESP |
collection |
Repositório Institucional da UNESP |
repository.name.fl_str_mv |
Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP) |
repository.mail.fl_str_mv |
|
_version_ |
1803649546228596736 |