Publication:
Enhancing Power System Resilience Through Evolutionary Programming for High Impact Low Probability Events

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dc.citedby0
dc.contributor.authorZakaria F.en_US
dc.contributor.authorMusirin I.en_US
dc.contributor.authorKamari N.A.M.en_US
dc.contributor.authorAminuddin N.en_US
dc.contributor.authorJohari D.en_US
dc.contributor.authorShaaya S.A.en_US
dc.contributor.authorBajwa A.A.en_US
dc.contributor.authorKumar A.V.S.en_US
dc.contributor.authorid55646310800en_US
dc.contributor.authorid8620004100en_US
dc.contributor.authorid36680312000en_US
dc.contributor.authorid57211493660en_US
dc.contributor.authorid24733632200en_US
dc.contributor.authorid16022846200en_US
dc.contributor.authorid57208799045en_US
dc.contributor.authorid56888921600en_US
dc.date.accessioned2025-03-03T07:45:51Z
dc.date.available2025-03-03T07:45:51Z
dc.date.issued2024
dc.description.abstractEnsuring the sustainability of power systems is of utmost importance for modern societies. It is a fundamental necessity that directly impacts the well-being and functioning of communities and economies. The increasing frequency of power shutdowns triggered by severe weather events, which are worsened by the effects of climate change, has intensified research efforts aimed at enhancing the resilience of power systems. Remedial action needs to be planned for improving the power system?s resilience. The installation of distributed generation (DG) is one of the suitable efforts to alleviate this phenomenon. This paper presents enhancing power system resilience through evolutionary programming for high-impact low probability (HILP) events. Validation on IEEE 30-Bus Reliability Test System (RTS), solved using Evolutionary Programming (EP) under extreme weather demonstrates its capability in improving the power system resilience. In this study, the EP technique is used to identify the best configuration of DG placement and capacity that can effectively improve the system's ability to withstand and recover from such extreme events. After the installation of DG, the system's resilience was significantly enhanced across three different scenarios of HILP events. In scenario 1, the resilience increased from 0.713 to 1. Similarly, in scenario 2 and scenario 3, the resilience improved from 0.174 to 0.257 and from 0 to 0.302, respectively. The results demonstrate that this algorithm effectively quantifies the system?s resilience under HILP events. ? The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.en_US
dc.description.natureFinalen_US
dc.identifier.doi10.1007/978-981-97-3851-9_19
dc.identifier.epage212
dc.identifier.scopus2-s2.0-85205087944
dc.identifier.spage201
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85205087944&doi=10.1007%2f978-981-97-3851-9_19&partnerID=40&md5=f065053b51ec342ef74a28168c61a333
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/36929
dc.identifier.volume1213 LNEE
dc.pagecount11
dc.publisherSpringer Science and Business Media Deutschland GmbHen_US
dc.sourceScopus
dc.sourcetitleLecture Notes in Electrical Engineering
dc.subjectExtreme weather
dc.subjectHigh impact/low probabilities
dc.subjectPower
dc.subjectReliability test system
dc.subjectRemedial actions
dc.subjectResearch efforts
dc.subjectResilience
dc.subjectSevere weather events
dc.subjectSystem resiliences
dc.subjectWell being
dc.titleEnhancing Power System Resilience Through Evolutionary Programming for High Impact Low Probability Eventsen_US
dc.typeConference paperen_US
dspace.entity.typePublication
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