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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Bibliographic Details
Main Authors: Younesi, Abdollah, Shayeghi, Hossein, Safari, Amin, Siano, Pierluigi
Format: Article in Journal/Newspaper
Language:unknown
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Online Access:http://www.sciencedirect.com/science/article/pii/S036054422031327X
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Summary: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. Power systems resilience; Smart grid; Multi microgrid; Micro energy grid; Natural disaster; Monte Carlo simulation;