A comparative analysis of flow-based resilience indices using topological and load flow models

Power grid is recognized as one of the most important critical infrastructures of society. In our modern world, more parts of our everyday lives are now dependent on electrical energy, and thus hard to find a system that is utterly independent of electricity. Extreme weather events driven by climate...

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Main Authors: Afzal, Suhail, Mokhlis, Hazlie, Illias, Hazlee Azil, Mansor, Nurulafiqah Nadzirah, Mohd Khairuddin, Anis Salwa, Mohd Sarmin, Mohd Khairun Nizam
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Published: 2021
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Online Access:http://eprints.um.edu.my/36127/
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85126449706&doi=10.1109%2fi-PACT52855.2021.9696618&partnerID=40&md5=24c288ab64f0884f9c76d168abb39cb9
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spelling my.um.eprints.361272024-10-28T03:26:19Z http://eprints.um.edu.my/36127/ A comparative analysis of flow-based resilience indices using topological and load flow models Afzal, Suhail Mokhlis, Hazlie Illias, Hazlee Azil Mansor, Nurulafiqah Nadzirah Mohd Khairuddin, Anis Salwa Mohd Sarmin, Mohd Khairun Nizam TK Electrical engineering. Electronics Nuclear engineering Power grid is recognized as one of the most important critical infrastructures of society. In our modern world, more parts of our everyday lives are now dependent on electrical energy, and thus hard to find a system that is utterly independent of electricity. Extreme weather events driven by climate change are a major threat to the power systems as a majority of the grid exists above ground, hence exposed to extreme weather. Recent widespread power cuts due to severe weather have proven that power grid is vulnerable to such events. The vulnerability of power system infrastructures is generally assessed using complex network analysis, and graph theory is a prominent approach that is computationally inexpensive, however, physical characteristics of the system are disregarded. Based on the geometric configuration of power networks, various indices have been proposed to measure the importance of components with respect to their contribution to the network functionality. In this paper, we have presented a comprehensive analysis of several flow-based indices using topological and physics-based models. Numerical results are carried out on IEEE 6-bus system. The outcomes of the analysis can provide important insights to the system operators and decision-makers on enhancing power system resilience. © 2021 IEEE. 2021 Conference or Workshop Item PeerReviewed Afzal, Suhail and Mokhlis, Hazlie and Illias, Hazlee Azil and Mansor, Nurulafiqah Nadzirah and Mohd Khairuddin, Anis Salwa and Mohd Sarmin, Mohd Khairun Nizam (2021) A comparative analysis of flow-based resilience indices using topological and load flow models. In: 3rd IEEE International Virtual Conference on Innovations in Power and Advanced Computing Technologies, i-PACT 2021, 27 November 2021, Virtual, Online. https://www.scopus.com/inward/record.uri?eid=2-s2.0-85126449706&doi=10.1109%2fi-PACT52855.2021.9696618&partnerID=40&md5=24c288ab64f0884f9c76d168abb39cb9
institution Universiti Malaya
building UM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaya
content_source UM Research Repository
url_provider http://eprints.um.edu.my/
topic TK Electrical engineering. Electronics Nuclear engineering
spellingShingle TK Electrical engineering. Electronics Nuclear engineering
Afzal, Suhail
Mokhlis, Hazlie
Illias, Hazlee Azil
Mansor, Nurulafiqah Nadzirah
Mohd Khairuddin, Anis Salwa
Mohd Sarmin, Mohd Khairun Nizam
A comparative analysis of flow-based resilience indices using topological and load flow models
description Power grid is recognized as one of the most important critical infrastructures of society. In our modern world, more parts of our everyday lives are now dependent on electrical energy, and thus hard to find a system that is utterly independent of electricity. Extreme weather events driven by climate change are a major threat to the power systems as a majority of the grid exists above ground, hence exposed to extreme weather. Recent widespread power cuts due to severe weather have proven that power grid is vulnerable to such events. The vulnerability of power system infrastructures is generally assessed using complex network analysis, and graph theory is a prominent approach that is computationally inexpensive, however, physical characteristics of the system are disregarded. Based on the geometric configuration of power networks, various indices have been proposed to measure the importance of components with respect to their contribution to the network functionality. In this paper, we have presented a comprehensive analysis of several flow-based indices using topological and physics-based models. Numerical results are carried out on IEEE 6-bus system. The outcomes of the analysis can provide important insights to the system operators and decision-makers on enhancing power system resilience. © 2021 IEEE.
format Conference or Workshop Item
author Afzal, Suhail
Mokhlis, Hazlie
Illias, Hazlee Azil
Mansor, Nurulafiqah Nadzirah
Mohd Khairuddin, Anis Salwa
Mohd Sarmin, Mohd Khairun Nizam
author_facet Afzal, Suhail
Mokhlis, Hazlie
Illias, Hazlee Azil
Mansor, Nurulafiqah Nadzirah
Mohd Khairuddin, Anis Salwa
Mohd Sarmin, Mohd Khairun Nizam
author_sort Afzal, Suhail
title A comparative analysis of flow-based resilience indices using topological and load flow models
title_short A comparative analysis of flow-based resilience indices using topological and load flow models
title_full A comparative analysis of flow-based resilience indices using topological and load flow models
title_fullStr A comparative analysis of flow-based resilience indices using topological and load flow models
title_full_unstemmed A comparative analysis of flow-based resilience indices using topological and load flow models
title_sort comparative analysis of flow-based resilience indices using topological and load flow models
publishDate 2021
url http://eprints.um.edu.my/36127/
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85126449706&doi=10.1109%2fi-PACT52855.2021.9696618&partnerID=40&md5=24c288ab64f0884f9c76d168abb39cb9
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score 13.211869