Distribution system resilience enhancement by microgrid formation considering distributed energy resources

Due to increasing in natural disasters in the recent years, the issue of distribution network resilience has become highly important. Microgrids with different types of distributed energy resources have the capabilities to improve distribution network resilience under extreme events. In this paper,...

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Bibliographic Details
Published in:Energy (Oxford) 2020-01, Vol.191, p.116442, Article 116442
Main Authors: Gilani, Mohammad Amin, Kazemi, Ahad, Ghasemi, Mostafa
Format: Article
Language:English
Subjects:
Constraint modelling
Distributed energy resources
Distributed generation
Distribution system resilience
Electric power distribution
Electric power grids
Emergency operation budgets
Emergency procedures
Energy management
Energy resources
Energy sources
Energy storage
Microgrids
Mixed-integer linear program
Natural disasters
Networks
Renewable energy
Resilience
Smart grid
Smart grid technology
Storage units
Topology
Turbines
Wind power
Wind turbines
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Summary:Due to increasing in natural disasters in the recent years, the issue of distribution network resilience has become highly important. Microgrids with different types of distributed energy resources have the capabilities to improve distribution network resilience under extreme events. In this paper, we present a mixed-integer linear program to restore prioritized loads while satisfying topology and operational constraints. In the presented model, we study dynamic microgrid formation and optimal management of various smart grid technologies such as distributed generations, demand response programs, wind turbines and energy storage units. We also investigate the significant impact of renewable energy resources, loads and their uncertainty on distribution system resilience. In addition, we determine the required emergency budgets of operation to restore a distribution system from extreme events. We also intend to examine the effects of demand response programs on improving the distribution system performance in the recovery period. Finally, we verify the effectiveness of the presented model on a modified IEEE 33-node test system and a real distribution system. •A linear approach is presented to enhance the resilience of distribution system.•A resilient model is proposed to form dynamic microgrids.•A stochastic programming is used to model the uncertainty of renewable energy.
ISSN:0360-5442
1873-6785
DOI:10.1016/j.energy.2019.116442