{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,8]],"date-time":"2025-10-08T22:50:08Z","timestamp":1759963808015,"version":"3.40.5"},"reference-count":38,"publisher":"Wiley","license":[{"start":{"date-parts":[[2022,8,24]],"date-time":"2022-08-24T00:00:00Z","timestamp":1661299200000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Journal of Electrical and Computer Engineering"],"published-print":{"date-parts":[[2022,8,24]]},"abstract":"<jats:p>The modern microgrid is designed to withstand various disruptive events that have a high probability of occurrence but have a low impact on the system. This improves the reliability of the system but does not take into consideration the disruptive events that have a low probability of occurrence but have a large impact on the system, such as extreme weather or natural disasters. Redesigning a microgrid to withstand low probability high impact events is very costly and is not a feasible solution to existing microgrids. This paper proposes a method to improve the resilience of an existing microgrid to quickly recover from low probability high impact events. The method used for this purpose is a combination of Monte Carlo simulation and prioritization of load of the microgrid. The efficacy of the method is examined by modeling microgrids using a fragility model. Using the proposed novel resilience index, the resilience of the IEEE 5-Bus system and IEEE 14-Bus system and the effect of load shedding on the resilience of the microgrid are analyzed and presented. The effect on smaller and larger grids and their resilience is examined. A novel resilience index is used to quantify the improvement of resilience of the proposed method when compared to other methods available in the literature.<\/jats:p>","DOI":"10.1155\/2022\/3074298","type":"journal-article","created":{"date-parts":[[2022,8,25]],"date-time":"2022-08-25T03:35:09Z","timestamp":1661398509000},"page":"1-12","source":"Crossref","is-referenced-by-count":10,"title":["Improvement of the Resilience of a Microgrid Using Fragility Modeling and Simulation"],"prefix":"10.1155","volume":"2022","author":[{"given":"Santhan Kumar","family":"Ch","sequence":"first","affiliation":[{"name":"Department of EEE, Lords Institute of Engineering and Technology, Hyderabad, India"}]},{"given":"N.","family":"Karuppiah","sequence":"additional","affiliation":[{"name":"Department of EEE, Vardhaman College of Engineering, Hyderabad, India"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1561-1376","authenticated-orcid":true,"given":"B.","family":"Praveen Kumar","sequence":"additional","affiliation":[{"name":"Department of EEE, Vardhaman College of Engineering, Hyderabad, India"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4931-724X","authenticated-orcid":true,"given":"S.","family":"Shitharth","sequence":"additional","affiliation":[{"name":"Department of CSE, Kebri Dehar University, Somali, Ethiopia"}]},{"given":"B.","family":"Dasu","sequence":"additional","affiliation":[{"name":"Department of EEE, Gudlavalleru Engineering College, Vijayawada, India"}]}],"member":"311","reference":[{"issue":"5","key":"1","doi-asserted-by":"crossref","DOI":"10.1109\/TPWRS.2016.2641463","article-title":"Power system resilience to extreme weather: fragility modelling probabilistic impact assessment and adaptation measures","volume":"32","author":"M. 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