Resilience Improvement of Distribution Networks Using a Two-Stage Stochastic Multi-Objective Programming via Microgrids Optimal Performance

Dealing with major power disruption during natural disasters is one of the most notable concerns in power systems. In this regard, the optimal application of microgrids as a potential solution in increasing and sustaining the distribution system resilience is considered. Furthermore, this purpose is...

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Main Authors: Mahsa Ebadat Parast, Mohammad H. Nazari, Seyed Hossain Hosseinian
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/9491095/
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spelling doaj-7a85ab37558b482aab50f4986a95ca222021-07-27T23:00:57ZengIEEEIEEE Access2169-35362021-01-01910293010295210.1109/ACCESS.2021.30985289491095Resilience Improvement of Distribution Networks Using a Two-Stage Stochastic Multi-Objective Programming via Microgrids Optimal PerformanceMahsa Ebadat Parast0Mohammad H. Nazari1https://orcid.org/0000-0002-2584-7529Seyed Hossain Hosseinian2Department of Electrical Engineering, Amirkabir University of Technology, Tehran, IranDepartment of Electrical Engineering, Amirkabir University of Technology, Tehran, IranDepartment of Electrical Engineering, Amirkabir University of Technology, Tehran, IranDealing with major power disruption during natural disasters is one of the most notable concerns in power systems. In this regard, the optimal application of microgrids as a potential solution in increasing and sustaining the distribution system resilience is considered. Furthermore, this purpose is pursued while maintaining the resilience of each DC microgrid connected to the distribution system, which is an essential and challenging issue. In the proposed method of this paper, a novel modeling strategy is formulated as a multi-period two-stage scenario-based stochastic mixed-integer linear programming (MPTSS-MILP) based on a multi-objective optimization problem (MOOP). In this framework, the operation associated with emergency and normal conditions, according to the influences of each situation on another one, is managed in multi-microgrids coordinately. In this regard, the technical constraints correlated to the operation of microgrids as well as the distribution system are satisfied simultaneously in specific to each condition which covers normal and critical operating under all uncertainty scenarios. Through introducing two evaluation criteria and also a resilience metric in microgrids and distribution systems, the efficiency of the proposed method is demonstrated. Meanwhile, innovative modeling is executed based on the subjective behavior of people affected by the disaster. The proposed method is implemented on a test system that involves a 34-bus distribution system with three distinct DC microgrids. In this regard, the impact of plug-in electric vehicles, as well as social behavior affected by severe events, demonstrate significant results according to the resilience criteria and resilience metric of microgrids and distribution system in three case studies based on the proposed approach.https://ieeexplore.ieee.org/document/9491095/Resilienceextreme eventsmicrogridsstochastic optimizationdistribution system
collection DOAJ
language English
format Article
sources DOAJ
author Mahsa Ebadat Parast
Mohammad H. Nazari
Seyed Hossain Hosseinian
spellingShingle Mahsa Ebadat Parast
Mohammad H. Nazari
Seyed Hossain Hosseinian
Resilience Improvement of Distribution Networks Using a Two-Stage Stochastic Multi-Objective Programming via Microgrids Optimal Performance
IEEE Access
Resilience
extreme events
microgrids
stochastic optimization
distribution system
author_facet Mahsa Ebadat Parast
Mohammad H. Nazari
Seyed Hossain Hosseinian
author_sort Mahsa Ebadat Parast
title Resilience Improvement of Distribution Networks Using a Two-Stage Stochastic Multi-Objective Programming via Microgrids Optimal Performance
title_short Resilience Improvement of Distribution Networks Using a Two-Stage Stochastic Multi-Objective Programming via Microgrids Optimal Performance
title_full Resilience Improvement of Distribution Networks Using a Two-Stage Stochastic Multi-Objective Programming via Microgrids Optimal Performance
title_fullStr Resilience Improvement of Distribution Networks Using a Two-Stage Stochastic Multi-Objective Programming via Microgrids Optimal Performance
title_full_unstemmed Resilience Improvement of Distribution Networks Using a Two-Stage Stochastic Multi-Objective Programming via Microgrids Optimal Performance
title_sort resilience improvement of distribution networks using a two-stage stochastic multi-objective programming via microgrids optimal performance
publisher IEEE
series IEEE Access
issn 2169-3536
publishDate 2021-01-01
description Dealing with major power disruption during natural disasters is one of the most notable concerns in power systems. In this regard, the optimal application of microgrids as a potential solution in increasing and sustaining the distribution system resilience is considered. Furthermore, this purpose is pursued while maintaining the resilience of each DC microgrid connected to the distribution system, which is an essential and challenging issue. In the proposed method of this paper, a novel modeling strategy is formulated as a multi-period two-stage scenario-based stochastic mixed-integer linear programming (MPTSS-MILP) based on a multi-objective optimization problem (MOOP). In this framework, the operation associated with emergency and normal conditions, according to the influences of each situation on another one, is managed in multi-microgrids coordinately. In this regard, the technical constraints correlated to the operation of microgrids as well as the distribution system are satisfied simultaneously in specific to each condition which covers normal and critical operating under all uncertainty scenarios. Through introducing two evaluation criteria and also a resilience metric in microgrids and distribution systems, the efficiency of the proposed method is demonstrated. Meanwhile, innovative modeling is executed based on the subjective behavior of people affected by the disaster. The proposed method is implemented on a test system that involves a 34-bus distribution system with three distinct DC microgrids. In this regard, the impact of plug-in electric vehicles, as well as social behavior affected by severe events, demonstrate significant results according to the resilience criteria and resilience metric of microgrids and distribution system in three case studies based on the proposed approach.
topic Resilience
extreme events
microgrids
stochastic optimization
distribution system
url https://ieeexplore.ieee.org/document/9491095/
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AT mohammadhnazari resilienceimprovementofdistributionnetworksusingatwostagestochasticmultiobjectiveprogrammingviamicrogridsoptimalperformance
AT seyedhossainhosseinian resilienceimprovementofdistributionnetworksusingatwostagestochasticmultiobjectiveprogrammingviamicrogridsoptimalperformance
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