A review of power system predictive failure model for resilience enhancement against hurricane events

Abstract Natural events such as hurricanes usually cause unimaginable destruction to the electric power system infrastructures across the globe leading to large‐scale power outages. While the transmission network offers relatively high resilience to the hurricane extreme wind speed intensity (HEWSI)...

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Autores principales:	Okeolu Samuel Omogoye, Komla Agbenyo Folly, Kehinde Oladayo Awodele
Formato:	article
Lenguaje:	EN
Publicado:	Wiley 2021
Materias:	Engineering (General). Civil engineering (General) TA1-2040
Acceso en línea:	https://doaj.org/article/ae9019e710564be0a7ada3de0a3dc162
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spelling	oai:doaj.org-article:ae9019e710564be0a7ada3de0a3dc1622021-11-19T06:50:34ZA review of power system predictive failure model for resilience enhancement against hurricane events2051-330510.1049/tje2.12092https://doaj.org/article/ae9019e710564be0a7ada3de0a3dc1622021-11-01T00:00:00Zhttps://doi.org/10.1049/tje2.12092https://doaj.org/toc/2051-3305Abstract Natural events such as hurricanes usually cause unimaginable destruction to the electric power system infrastructures across the globe leading to large‐scale power outages. While the transmission network offers relatively high resilience to the hurricane extreme wind speed intensity (HEWSI), the distribution power system network (DPSN) is always the worst hit. To enhance the DPSN against hurricane events, both the pre‐ and post‐event power system resilience enhancement techniques can be reviewed, and their limitations improved. Handling hurricane risks proactively for effective recovery plans requires rigorous techniques for locating and estimating the number of system component's damage causing outages on a DPSN. A review of the resilience evaluation methodologies utilized for a proactive statistical system component's failure predictive model is presented in this paper. As a contribution, this article presents the current practices, the problems, and points out the future research directions for a statistical system components’ line outage predictive model that can greatly enhance the DPSN against hurricane events for short‐term operational planning.Okeolu Samuel OmogoyeKomla Agbenyo FollyKehinde Oladayo AwodeleWileyarticleEngineering (General). Civil engineering (General)TA1-2040ENThe Journal of Engineering, Vol 2021, Iss 11, Pp 644-652 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Engineering (General). Civil engineering (General) TA1-2040
spellingShingle	Engineering (General). Civil engineering (General) TA1-2040 Okeolu Samuel Omogoye Komla Agbenyo Folly Kehinde Oladayo Awodele A review of power system predictive failure model for resilience enhancement against hurricane events
description	Abstract Natural events such as hurricanes usually cause unimaginable destruction to the electric power system infrastructures across the globe leading to large‐scale power outages. While the transmission network offers relatively high resilience to the hurricane extreme wind speed intensity (HEWSI), the distribution power system network (DPSN) is always the worst hit. To enhance the DPSN against hurricane events, both the pre‐ and post‐event power system resilience enhancement techniques can be reviewed, and their limitations improved. Handling hurricane risks proactively for effective recovery plans requires rigorous techniques for locating and estimating the number of system component's damage causing outages on a DPSN. A review of the resilience evaluation methodologies utilized for a proactive statistical system component's failure predictive model is presented in this paper. As a contribution, this article presents the current practices, the problems, and points out the future research directions for a statistical system components’ line outage predictive model that can greatly enhance the DPSN against hurricane events for short‐term operational planning.
format	article
author	Okeolu Samuel Omogoye Komla Agbenyo Folly Kehinde Oladayo Awodele
author_facet	Okeolu Samuel Omogoye Komla Agbenyo Folly Kehinde Oladayo Awodele
author_sort	Okeolu Samuel Omogoye
title	A review of power system predictive failure model for resilience enhancement against hurricane events
title_short	A review of power system predictive failure model for resilience enhancement against hurricane events
title_full	A review of power system predictive failure model for resilience enhancement against hurricane events
title_fullStr	A review of power system predictive failure model for resilience enhancement against hurricane events
title_full_unstemmed	A review of power system predictive failure model for resilience enhancement against hurricane events
title_sort	review of power system predictive failure model for resilience enhancement against hurricane events
publisher	Wiley
publishDate	2021
url	https://doaj.org/article/ae9019e710564be0a7ada3de0a3dc162
work_keys_str_mv	AT okeolusamuelomogoye areviewofpowersystempredictivefailuremodelforresilienceenhancementagainsthurricaneevents AT komlaagbenyofolly areviewofpowersystempredictivefailuremodelforresilienceenhancementagainsthurricaneevents AT kehindeoladayoawodele areviewofpowersystempredictivefailuremodelforresilienceenhancementagainsthurricaneevents AT okeolusamuelomogoye reviewofpowersystempredictivefailuremodelforresilienceenhancementagainsthurricaneevents AT komlaagbenyofolly reviewofpowersystempredictivefailuremodelforresilienceenhancementagainsthurricaneevents AT kehindeoladayoawodele reviewofpowersystempredictivefailuremodelforresilienceenhancementagainsthurricaneevents
_version_	1718420335220490240

A review of power system predictive failure model for resilience enhancement against hurricane events

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