A New Model for a Resilient Distribution System After Natural Disasters Using Microgrid Formation and Considering ICE Cars

The severe impact of natural disasters on distribution system (DS) infrastructure highlights the importance of enhancing the resiliency of such systems. The loss of critical loads, one of the worst results of these events, increases the significance of resilient restoration approaches. In addition t...

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Main Authors: Ahad Abessi, Shahram Jadid, M. M. A. Salama
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/9310188/
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author Ahad Abessi
Shahram Jadid
M. M. A. Salama
author_facet Ahad Abessi
Shahram Jadid
M. M. A. Salama
author_sort Ahad Abessi
collection DOAJ
description The severe impact of natural disasters on distribution system (DS) infrastructure highlights the importance of enhancing the resiliency of such systems. The loss of critical loads, one of the worst results of these events, increases the significance of resilient restoration approaches. In addition to distributed generators (DGs), which are common resources in restoration schemes, internal combustion engines (ICE) cars can considerably affect DS resiliency. This article first introduces an idea for using ICE vehicle as energy resources in a DS to enhance the system's flexibility during restoration efforts after natural disasters. The amount of electrical consumption of modern cars and the availability of home inverters makes this idea practical. In addition, a novel comprehensive method is proposed based on the optimal formation of dynamic microgrids (MGs) that satisfies operational constraints and considers the ICE vehicles and is not based on path-based or children-parent nodes concepts. Moreover, the proposed method considers the integration of DGs in one microgrid. The proposed method is based on two-stage stochastic mixed-integer linear programming (MILP), and considers uncertain load consumption and demand response (DR). Finally, the effectiveness of the proposed method is evaluated using a modified 33-bus IEEE test system. The results show that integration of DGs leads to restoring more loads. Moreover, distribution and selection of the buses corresponding to ICE cars affect directly on the amount of restored load. Budget limitation is also considered in this article. Evaluation of the proposed method shows the considerable effectiveness in increasing the resiliency of DS.
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spelling doaj.art-424568d0fdb54a93baf6b73ebce140c92022-12-21T23:35:06ZengIEEEIEEE Access2169-35362021-01-0194616462910.1109/ACCESS.2020.30479049310188A New Model for a Resilient Distribution System After Natural Disasters Using Microgrid Formation and Considering ICE CarsAhad Abessi0https://orcid.org/0000-0001-6538-3821Shahram Jadid1https://orcid.org/0000-0002-7761-2430M. M. A. Salama2https://orcid.org/0000-0002-3970-4844Department of Electrical Engineering, University of Waterloo, Waterloo, CanadaDepartment of Electrical Engineering, Iran University of Science and Technology, Tehran, IranDepartment of Electrical Engineering, University of Waterloo, Waterloo, CanadaThe severe impact of natural disasters on distribution system (DS) infrastructure highlights the importance of enhancing the resiliency of such systems. The loss of critical loads, one of the worst results of these events, increases the significance of resilient restoration approaches. In addition to distributed generators (DGs), which are common resources in restoration schemes, internal combustion engines (ICE) cars can considerably affect DS resiliency. This article first introduces an idea for using ICE vehicle as energy resources in a DS to enhance the system's flexibility during restoration efforts after natural disasters. The amount of electrical consumption of modern cars and the availability of home inverters makes this idea practical. In addition, a novel comprehensive method is proposed based on the optimal formation of dynamic microgrids (MGs) that satisfies operational constraints and considers the ICE vehicles and is not based on path-based or children-parent nodes concepts. Moreover, the proposed method considers the integration of DGs in one microgrid. The proposed method is based on two-stage stochastic mixed-integer linear programming (MILP), and considers uncertain load consumption and demand response (DR). Finally, the effectiveness of the proposed method is evaluated using a modified 33-bus IEEE test system. The results show that integration of DGs leads to restoring more loads. Moreover, distribution and selection of the buses corresponding to ICE cars affect directly on the amount of restored load. Budget limitation is also considered in this article. Evaluation of the proposed method shows the considerable effectiveness in increasing the resiliency of DS.https://ieeexplore.ieee.org/document/9310188/Internal combustion engine (ICE) carsMG formationresiliency
spellingShingle Ahad Abessi
Shahram Jadid
M. M. A. Salama
A New Model for a Resilient Distribution System After Natural Disasters Using Microgrid Formation and Considering ICE Cars
IEEE Access
Internal combustion engine (ICE) cars
MG formation
resiliency
title A New Model for a Resilient Distribution System After Natural Disasters Using Microgrid Formation and Considering ICE Cars
title_full A New Model for a Resilient Distribution System After Natural Disasters Using Microgrid Formation and Considering ICE Cars
title_fullStr A New Model for a Resilient Distribution System After Natural Disasters Using Microgrid Formation and Considering ICE Cars
title_full_unstemmed A New Model for a Resilient Distribution System After Natural Disasters Using Microgrid Formation and Considering ICE Cars
title_short A New Model for a Resilient Distribution System After Natural Disasters Using Microgrid Formation and Considering ICE Cars
title_sort new model for a resilient distribution system after natural disasters using microgrid formation and considering ice cars
topic Internal combustion engine (ICE) cars
MG formation
resiliency
url https://ieeexplore.ieee.org/document/9310188/
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