Resiliency Improvement of Distribution Network Considering the Charge/Discharge Management of Electric Vehicles in Parking Lots through a Bilevel Optimization Approach
Due to the growing use of Plug-in Electric vehicles (PEVs) in transportation networks, the charge/discharge scheduling of PEVs in Electric Vehicles Parking Lots (EVPLs) can be effective on the distribution network’s (DN) resiliency. This paper presents a bilevel optimization model to improve the res...
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| Format: | Article |
| Language: | English |
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Wiley
2022-01-01
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| Series: | International Transactions on Electrical Energy Systems |
| Online Access: | http://dx.doi.org/10.1155/2022/3878440 |
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| author | Mohammad Alizadeh Meysam Jafari-Nokandi Majid Shahabi |
| author_facet | Mohammad Alizadeh Meysam Jafari-Nokandi Majid Shahabi |
| author_sort | Mohammad Alizadeh |
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| description | Due to the growing use of Plug-in Electric vehicles (PEVs) in transportation networks, the charge/discharge scheduling of PEVs in Electric Vehicles Parking Lots (EVPLs) can be effective on the distribution network’s (DN) resiliency. This paper presents a bilevel optimization model to improve the resiliency of the DN taking into account the interaction between the DN islanding problem and the charge/discharge scheduling of PEVs in the energized EVPLs. In the Upper-Level (UL) problem, regarding the electrical loads and managing the charge/discharge of PEVs, the islands’ boundaries are determined with the aim of maximizing the amount of restored load. Knowing the islands’ boundaries and the energized EVPLs from the UL problem, the changes in travels characteristic including destination EVPLs are determined in the Lower-Level (LL) problem to identify the nearest energized EVPL to the out-of-service destination EVPL. The number of PEV drivers that change their deenergized destination depends on the distance between the nearest energized EVPL to the destination. A combination of mathematical programming and evolutionary algorithm is applied to reach the final solution. The proposed model is implemented by applying several concurrent faults to the 118-bus active DN, which is coupled with a 25-node traffic network. The results confirm the efficiency of the proposed model for improving the resiliency of DNs with managing the charge/discharge of PEVs in the restored EVPLs. |
| format | Article |
| id | doaj-art-d732d24345554c57942b8bd67c261423 |
| institution | Kabale University |
| issn | 2050-7038 |
| language | English |
| publishDate | 2022-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | International Transactions on Electrical Energy Systems |
| spelling | doaj-art-d732d24345554c57942b8bd67c2614232025-02-03T01:23:37ZengWileyInternational Transactions on Electrical Energy Systems2050-70382022-01-01202210.1155/2022/3878440Resiliency Improvement of Distribution Network Considering the Charge/Discharge Management of Electric Vehicles in Parking Lots through a Bilevel Optimization ApproachMohammad Alizadeh0Meysam Jafari-Nokandi1Majid Shahabi2Faculty of Electrical and Computer EngineeringFaculty of Electrical and Computer EngineeringFaculty of Electrical and Computer EngineeringDue to the growing use of Plug-in Electric vehicles (PEVs) in transportation networks, the charge/discharge scheduling of PEVs in Electric Vehicles Parking Lots (EVPLs) can be effective on the distribution network’s (DN) resiliency. This paper presents a bilevel optimization model to improve the resiliency of the DN taking into account the interaction between the DN islanding problem and the charge/discharge scheduling of PEVs in the energized EVPLs. In the Upper-Level (UL) problem, regarding the electrical loads and managing the charge/discharge of PEVs, the islands’ boundaries are determined with the aim of maximizing the amount of restored load. Knowing the islands’ boundaries and the energized EVPLs from the UL problem, the changes in travels characteristic including destination EVPLs are determined in the Lower-Level (LL) problem to identify the nearest energized EVPL to the out-of-service destination EVPL. The number of PEV drivers that change their deenergized destination depends on the distance between the nearest energized EVPL to the destination. A combination of mathematical programming and evolutionary algorithm is applied to reach the final solution. The proposed model is implemented by applying several concurrent faults to the 118-bus active DN, which is coupled with a 25-node traffic network. The results confirm the efficiency of the proposed model for improving the resiliency of DNs with managing the charge/discharge of PEVs in the restored EVPLs.http://dx.doi.org/10.1155/2022/3878440 |
| spellingShingle | Mohammad Alizadeh Meysam Jafari-Nokandi Majid Shahabi Resiliency Improvement of Distribution Network Considering the Charge/Discharge Management of Electric Vehicles in Parking Lots through a Bilevel Optimization Approach International Transactions on Electrical Energy Systems |
| title | Resiliency Improvement of Distribution Network Considering the Charge/Discharge Management of Electric Vehicles in Parking Lots through a Bilevel Optimization Approach |
| title_full | Resiliency Improvement of Distribution Network Considering the Charge/Discharge Management of Electric Vehicles in Parking Lots through a Bilevel Optimization Approach |
| title_fullStr | Resiliency Improvement of Distribution Network Considering the Charge/Discharge Management of Electric Vehicles in Parking Lots through a Bilevel Optimization Approach |
| title_full_unstemmed | Resiliency Improvement of Distribution Network Considering the Charge/Discharge Management of Electric Vehicles in Parking Lots through a Bilevel Optimization Approach |
| title_short | Resiliency Improvement of Distribution Network Considering the Charge/Discharge Management of Electric Vehicles in Parking Lots through a Bilevel Optimization Approach |
| title_sort | resiliency improvement of distribution network considering the charge discharge management of electric vehicles in parking lots through a bilevel optimization approach |
| url | http://dx.doi.org/10.1155/2022/3878440 |
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