Enhancing Power System Resilience Through Evolutionary Programming for High Impact Low Probability Events
Ensuring 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 worsen...
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Springer Science and Business Media Deutschland GmbH
2025
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| author | Zakaria F. Musirin I. Kamari N.A.M. Aminuddin N. Johari D. Shaaya S.A. Bajwa A.A. Kumar A.V.S. |
| author2 | 55646310800 |
| author_facet | 55646310800 Zakaria F. Musirin I. Kamari N.A.M. Aminuddin N. Johari D. Shaaya S.A. Bajwa A.A. Kumar A.V.S. |
| author_sort | Zakaria F. |
| building | UNITEN Library |
| collection | Institutional Repository |
| content_provider | Universiti Tenaga Nasional |
| content_source | UNITEN Institutional Repository |
| continent | Asia |
| country | Malaysia |
| description | Ensuring 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. |
| format | Conference paper |
| id | my.uniten.dspace-36929 |
| institution | Universiti Tenaga Nasional |
| publishDate | 2025 |
| publisher | Springer Science and Business Media Deutschland GmbH |
| record_format | dspace |
| spelling | my.uniten.dspace-369292025-03-03T15:45:51Z Enhancing Power System Resilience Through Evolutionary Programming for High Impact Low Probability Events Zakaria F. Musirin I. Kamari N.A.M. Aminuddin N. Johari D. Shaaya S.A. Bajwa A.A. Kumar A.V.S. 55646310800 8620004100 36680312000 57211493660 24733632200 16022846200 57208799045 56888921600 Extreme weather High impact/low probabilities Power Reliability test system Remedial actions Research efforts Resilience Severe weather events System resiliences Well being Ensuring 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. Final 2025-03-03T07:45:51Z 2025-03-03T07:45:51Z 2024 Conference paper 10.1007/978-981-97-3851-9_19 2-s2.0-85205087944 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85205087944&doi=10.1007%2f978-981-97-3851-9_19&partnerID=40&md5=f065053b51ec342ef74a28168c61a333 https://irepository.uniten.edu.my/handle/123456789/36929 1213 LNEE 201 212 Springer Science and Business Media Deutschland GmbH Scopus |
| spellingShingle | Extreme weather High impact/low probabilities Power Reliability test system Remedial actions Research efforts Resilience Severe weather events System resiliences Well being Zakaria F. Musirin I. Kamari N.A.M. Aminuddin N. Johari D. Shaaya S.A. Bajwa A.A. Kumar A.V.S. Enhancing Power System Resilience Through Evolutionary Programming for High Impact Low Probability Events |
| title | Enhancing Power System Resilience Through Evolutionary Programming for High Impact Low Probability Events |
| title_full | Enhancing Power System Resilience Through Evolutionary Programming for High Impact Low Probability Events |
| title_fullStr | Enhancing Power System Resilience Through Evolutionary Programming for High Impact Low Probability Events |
| title_full_unstemmed | Enhancing Power System Resilience Through Evolutionary Programming for High Impact Low Probability Events |
| title_short | Enhancing Power System Resilience Through Evolutionary Programming for High Impact Low Probability Events |
| title_sort | enhancing power system resilience through evolutionary programming for high impact low probability events |
| topic | Extreme weather High impact/low probabilities Power Reliability test system Remedial actions Research efforts Resilience Severe weather events System resiliences Well being |
| url_provider | http://dspace.uniten.edu.my/ |