Multiobjective Electric Vehicle Charging Network Planning Considering Chance-Constraint on the Travel Distance for Charging
Electric vehicle charging stations (EVCSs) are important infrastructures to support sustainable development of electric vehicles (EVs), by providing convenient, rapid charging services. Therefore, the planning of electric vehicle charging network (EVCN) has attracted wide interest from both industry...
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| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2023-01-01
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| Series: | IET Electrical Systems in Transportation |
| Online Access: | http://dx.doi.org/10.1049/2023/6690544 |
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| _version_ | 1832546601615228928 |
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| author | Yunxiang Guo Xinsong Zhang Daxiang Li Chenghong Gu Cheng Lu Ting Ji Yue Wang |
| author_facet | Yunxiang Guo Xinsong Zhang Daxiang Li Chenghong Gu Cheng Lu Ting Ji Yue Wang |
| author_sort | Yunxiang Guo |
| collection | DOAJ |
| description | Electric vehicle charging stations (EVCSs) are important infrastructures to support sustainable development of electric vehicles (EVs), by providing convenient, rapid charging services. Therefore, the planning of electric vehicle charging network (EVCN) has attracted wide interest from both industry and academia. In this paper, a multiobjective planning model for EVCN is developed, where a fixed number of EVCSs are planned in the traffic network (TN) to achieve two objectives, i.e., minimizing both average travel distance for charging (TDfC) of EVs and investment costs of EVCN. According to the random characteristics of EVs’ TDfC, its constraint is presented as a chance constraint in the developed EVCN planning model. The nondominated sorting genetic Algorithm II with the constraint domination principle (NSGA-II-CDP) is customized to solve the developed multiobjective EVCN planning model, by designing a special coding scheme, a crossover operator, and a mutation operator. Then, a maximum gradient principle of investment revenue is designed to select the optimal planning strategy from the Pareto-optimal solution set, when taking the investment return ratio as primary consideration. A 25-node TN is used to justify the effectiveness of the developed methodology. |
| format | Article |
| id | doaj-art-65e71d1c4134450b879d2b337a82d97b |
| institution | Kabale University |
| issn | 2042-9746 |
| language | English |
| publishDate | 2023-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | IET Electrical Systems in Transportation |
| spelling | doaj-art-65e71d1c4134450b879d2b337a82d97b2025-02-03T06:47:46ZengWileyIET Electrical Systems in Transportation2042-97462023-01-01202310.1049/2023/6690544Multiobjective Electric Vehicle Charging Network Planning Considering Chance-Constraint on the Travel Distance for ChargingYunxiang Guo0Xinsong Zhang1Daxiang Li2Chenghong Gu3Cheng Lu4Ting Ji5Yue Wang6Department of Electrical EngineeringDepartment of Electrical EngineeringDepartment of Electrical EngineeringDepartment of Electronic & Electrical EngineeringDepartment of Electrical EngineeringDepartment of Electrical EngineeringHuaneng Nantong Power Generation Co. LtdElectric vehicle charging stations (EVCSs) are important infrastructures to support sustainable development of electric vehicles (EVs), by providing convenient, rapid charging services. Therefore, the planning of electric vehicle charging network (EVCN) has attracted wide interest from both industry and academia. In this paper, a multiobjective planning model for EVCN is developed, where a fixed number of EVCSs are planned in the traffic network (TN) to achieve two objectives, i.e., minimizing both average travel distance for charging (TDfC) of EVs and investment costs of EVCN. According to the random characteristics of EVs’ TDfC, its constraint is presented as a chance constraint in the developed EVCN planning model. The nondominated sorting genetic Algorithm II with the constraint domination principle (NSGA-II-CDP) is customized to solve the developed multiobjective EVCN planning model, by designing a special coding scheme, a crossover operator, and a mutation operator. Then, a maximum gradient principle of investment revenue is designed to select the optimal planning strategy from the Pareto-optimal solution set, when taking the investment return ratio as primary consideration. A 25-node TN is used to justify the effectiveness of the developed methodology.http://dx.doi.org/10.1049/2023/6690544 |
| spellingShingle | Yunxiang Guo Xinsong Zhang Daxiang Li Chenghong Gu Cheng Lu Ting Ji Yue Wang Multiobjective Electric Vehicle Charging Network Planning Considering Chance-Constraint on the Travel Distance for Charging IET Electrical Systems in Transportation |
| title | Multiobjective Electric Vehicle Charging Network Planning Considering Chance-Constraint on the Travel Distance for Charging |
| title_full | Multiobjective Electric Vehicle Charging Network Planning Considering Chance-Constraint on the Travel Distance for Charging |
| title_fullStr | Multiobjective Electric Vehicle Charging Network Planning Considering Chance-Constraint on the Travel Distance for Charging |
| title_full_unstemmed | Multiobjective Electric Vehicle Charging Network Planning Considering Chance-Constraint on the Travel Distance for Charging |
| title_short | Multiobjective Electric Vehicle Charging Network Planning Considering Chance-Constraint on the Travel Distance for Charging |
| title_sort | multiobjective electric vehicle charging network planning considering chance constraint on the travel distance for charging |
| url | http://dx.doi.org/10.1049/2023/6690544 |
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