Assessing the resilience of multi microgrid based widespread power systems against natural disasters using Monte Carlo Simulation

The primary objective of this paper is to assess the resilience of a large-scale multi-microgrid based power system to cope with the wide-area natural disasters with severe destructive effects. The proposed resilience assessment method is quantitative and reflects various aspects of power system suc...

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Published in:Energy
Main Authors: Younesi A., Shayeghi H., Safari A., Siano P.
Other Authors: Younesi, A., Shayeghi, H., Safari, A., Siano, P.
Format: Article in Journal/Newspaper
Language:English
Published: 2020
Subjects:
Online Access:http://hdl.handle.net/11386/4757728
https://doi.org/10.1016/j.energy.2020.118220
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author Younesi A.
Shayeghi H.
Safari A.
Siano P.
author2 Younesi, A.
Shayeghi, H.
Safari, A.
Siano, P.
author_facet Younesi A.
Shayeghi H.
Safari A.
Siano P.
author_sort Younesi A.
collection EleA@Unisa (Università degli Studi di Salerno)
container_start_page 118220
container_title Energy
container_volume 207
description The primary objective of this paper is to assess the resilience of a large-scale multi-microgrid based power system to cope with the wide-area natural disasters with severe destructive effects. The proposed resilience assessment method is quantitative and reflects various aspects of power system such as the fragility and uncertainties along with disaster characteristics such as the type and severity. In addition, it is comparable for different power systems and can be used in decision-making by power system operators and planners for future contingency planning and upgrade schemes. The impact of multiple-microgrids is entered in the formulations using the calculation of discrete-time multi-state transition model of the power system in response to an extreme event. The tiN−1me-homogeneous Markov chain is considered to determine the probability of system states (normal, microgrid, and emergency) using the time-independent transition matrix. In order to numerically assess the proposed resilience measure, IEEE 30-bus test case and Iceland 189-bus power system are used and simulations are continued by generating 10000 scenarios considering different event type, severity level and location upon the power system. Finally, Monte Carlo Simulation is used for calculating the resilience metrics.
format Article in Journal/Newspaper
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op_doi https://doi.org/10.1016/j.energy.2020.118220
op_relation volume:207
issue:118220
firstpage:1
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numberofpages:15
journal:ENERGY
http://hdl.handle.net/11386/4757728
doi:10.1016/j.energy.2020.118220
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spelling ftunisalernoiris:oai:www.iris.unisa.it:11386/4757728 2025-01-16T22:38:27+00:00 Assessing the resilience of multi microgrid based widespread power systems against natural disasters using Monte Carlo Simulation Younesi A. Shayeghi H. Safari A. Siano P. Younesi, A. Shayeghi, H. Safari, A. Siano, P. 2020 http://hdl.handle.net/11386/4757728 https://doi.org/10.1016/j.energy.2020.118220 eng eng volume:207 issue:118220 firstpage:1 lastpage:15 numberofpages:15 journal:ENERGY http://hdl.handle.net/11386/4757728 doi:10.1016/j.energy.2020.118220 info:eu-repo/semantics/altIdentifier/scopus/2-s2.0-85087653599 Micro energy grid Monte Carlo simulation Multi microgrid Natural disaster Power systems resilience Smart grid info:eu-repo/semantics/article 2020 ftunisalernoiris https://doi.org/10.1016/j.energy.2020.118220 2024-01-17T17:44:27Z The primary objective of this paper is to assess the resilience of a large-scale multi-microgrid based power system to cope with the wide-area natural disasters with severe destructive effects. The proposed resilience assessment method is quantitative and reflects various aspects of power system such as the fragility and uncertainties along with disaster characteristics such as the type and severity. In addition, it is comparable for different power systems and can be used in decision-making by power system operators and planners for future contingency planning and upgrade schemes. The impact of multiple-microgrids is entered in the formulations using the calculation of discrete-time multi-state transition model of the power system in response to an extreme event. The tiN−1me-homogeneous Markov chain is considered to determine the probability of system states (normal, microgrid, and emergency) using the time-independent transition matrix. In order to numerically assess the proposed resilience measure, IEEE 30-bus test case and Iceland 189-bus power system are used and simulations are continued by generating 10000 scenarios considering different event type, severity level and location upon the power system. Finally, Monte Carlo Simulation is used for calculating the resilience metrics. Article in Journal/Newspaper Iceland EleA@Unisa (Università degli Studi di Salerno) Energy 207 118220
spellingShingle Micro energy grid
Monte Carlo simulation
Multi microgrid
Natural disaster
Power systems resilience
Smart grid
Younesi A.
Shayeghi H.
Safari A.
Siano P.
Assessing the resilience of multi microgrid based widespread power systems against natural disasters using Monte Carlo Simulation
title Assessing the resilience of multi microgrid based widespread power systems against natural disasters using Monte Carlo Simulation
title_full Assessing the resilience of multi microgrid based widespread power systems against natural disasters using Monte Carlo Simulation
title_fullStr Assessing the resilience of multi microgrid based widespread power systems against natural disasters using Monte Carlo Simulation
title_full_unstemmed Assessing the resilience of multi microgrid based widespread power systems against natural disasters using Monte Carlo Simulation
title_short Assessing the resilience of multi microgrid based widespread power systems against natural disasters using Monte Carlo Simulation
title_sort assessing the resilience of multi microgrid based widespread power systems against natural disasters using monte carlo simulation
topic Micro energy grid
Monte Carlo simulation
Multi microgrid
Natural disaster
Power systems resilience
Smart grid
topic_facet Micro energy grid
Monte Carlo simulation
Multi microgrid
Natural disaster
Power systems resilience
Smart grid
url http://hdl.handle.net/11386/4757728
https://doi.org/10.1016/j.energy.2020.118220