Optimal Siting of EV Fleet Charging Station Considering EV Mobility and Microgrid Formation for Enhanced Grid Resilience
Coordinating infrastructure planning for transportation and the power grid is essential for enhanced reliability and resilience during operation and disaster management. This paper presents a two-stage stochastic model to optimize the location of electric vehicle fleet charging stations (FEVCSs) to...
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2023-11-01
|
| Series: | Applied Sciences |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2076-3417/13/22/12181 |
| _version_ | 1827640712197308416 |
|---|---|
| author | Abhijith Ravi Linquan Bai Hong Wang |
| author_facet | Abhijith Ravi Linquan Bai Hong Wang |
| author_sort | Abhijith Ravi |
| collection | DOAJ |
| description | Coordinating infrastructure planning for transportation and the power grid is essential for enhanced reliability and resilience during operation and disaster management. This paper presents a two-stage stochastic model to optimize the location of electric vehicle fleet charging stations (FEVCSs) to enhance the resilience of a distribution network. The first stage of this model deals with the decision to place an FEVCS at the most favorable and optimized location, whereas the second stage aims to minimize the weighted sum of the value of lost load in multiple potential scenarios with different faults. Indeed, the second stage is a joint grid restoration scheme with network reconfiguration and microgrid formation using available distributed generators and fleet electric vehicles. The proposed model is tested on a modified IEEE-33 node distribution network and a four-node transportation network. Case studies demonstrate the effectiveness of the proposed model. |
| first_indexed | 2024-03-09T17:03:29Z |
| format | Article |
| id | doaj.art-5e3a897022754d0da41e892ad656ff39 |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-09T17:03:29Z |
| publishDate | 2023-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-5e3a897022754d0da41e892ad656ff392023-11-24T14:26:31ZengMDPI AGApplied Sciences2076-34172023-11-0113221218110.3390/app132212181Optimal Siting of EV Fleet Charging Station Considering EV Mobility and Microgrid Formation for Enhanced Grid ResilienceAbhijith Ravi0Linquan Bai1Hong Wang2Industrial and Systems Engineering, University of North Carolina at Charlotte, Charlotte, NC 28223, USAIndustrial and Systems Engineering, University of North Carolina at Charlotte, Charlotte, NC 28223, USAOak Ridge National Laboratory, Oak Ridge, TN 37831, USACoordinating infrastructure planning for transportation and the power grid is essential for enhanced reliability and resilience during operation and disaster management. This paper presents a two-stage stochastic model to optimize the location of electric vehicle fleet charging stations (FEVCSs) to enhance the resilience of a distribution network. The first stage of this model deals with the decision to place an FEVCS at the most favorable and optimized location, whereas the second stage aims to minimize the weighted sum of the value of lost load in multiple potential scenarios with different faults. Indeed, the second stage is a joint grid restoration scheme with network reconfiguration and microgrid formation using available distributed generators and fleet electric vehicles. The proposed model is tested on a modified IEEE-33 node distribution network and a four-node transportation network. Case studies demonstrate the effectiveness of the proposed model.https://www.mdpi.com/2076-3417/13/22/12181electric vehiclefleet electrificationgrid resilienceservice restoration |
| spellingShingle | Abhijith Ravi Linquan Bai Hong Wang Optimal Siting of EV Fleet Charging Station Considering EV Mobility and Microgrid Formation for Enhanced Grid Resilience Applied Sciences electric vehicle fleet electrification grid resilience service restoration |
| title | Optimal Siting of EV Fleet Charging Station Considering EV Mobility and Microgrid Formation for Enhanced Grid Resilience |
| title_full | Optimal Siting of EV Fleet Charging Station Considering EV Mobility and Microgrid Formation for Enhanced Grid Resilience |
| title_fullStr | Optimal Siting of EV Fleet Charging Station Considering EV Mobility and Microgrid Formation for Enhanced Grid Resilience |
| title_full_unstemmed | Optimal Siting of EV Fleet Charging Station Considering EV Mobility and Microgrid Formation for Enhanced Grid Resilience |
| title_short | Optimal Siting of EV Fleet Charging Station Considering EV Mobility and Microgrid Formation for Enhanced Grid Resilience |
| title_sort | optimal siting of ev fleet charging station considering ev mobility and microgrid formation for enhanced grid resilience |
| topic | electric vehicle fleet electrification grid resilience service restoration |
| url | https://www.mdpi.com/2076-3417/13/22/12181 |
| work_keys_str_mv | AT abhijithravi optimalsitingofevfleetchargingstationconsideringevmobilityandmicrogridformationforenhancedgridresilience AT linquanbai optimalsitingofevfleetchargingstationconsideringevmobilityandmicrogridformationforenhancedgridresilience AT hongwang optimalsitingofevfleetchargingstationconsideringevmobilityandmicrogridformationforenhancedgridresilience |