Optimal Allocation Model for EV Charging Stations Coordinating Investor and User Benefits
Deploying charging stations (CSs) catering to the demand from electric vehicles plays an important role in modernizing energy infrastructures. In this paper, a bi-level optimal allocation model for allocating fast CSs is proposed aiming to maximize the CS investor benefit (upper layer sub-problem) b...
| Main Authors: | , , , , , |
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| Format: | Article |
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IEEE
2018-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/8371598/ |
| _version_ | 1818618236901523456 |
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| author | Youbo Liu Yue Xiang Yangyang Tan Bin Wang Junyong Liu Zhiyu Yang |
| author_facet | Youbo Liu Yue Xiang Yangyang Tan Bin Wang Junyong Liu Zhiyu Yang |
| author_sort | Youbo Liu |
| collection | DOAJ |
| description | Deploying charging stations (CSs) catering to the demand from electric vehicles plays an important role in modernizing energy infrastructures. In this paper, a bi-level optimal allocation model for allocating fast CSs is proposed aiming to maximize the CS investor benefit (upper layer sub-problem) by optimally allocating CSs with the coordinated determination of the expected efficiency of charging service supply (lower layer sub-problem). The efficiency is formulated as a charging performance index in terms of user satisfaction degree, which mathematically couples the upper level and lower level subproblems. The proposed nonlinear bi-level model is reduced to a single-layer optimization model under the Karush-Kuhn-Tucker optimality conditions. An improved dynamic differential evolution algorithm with an adaptive update strategy is proposed to solve this single-layer optimization model. The proposed method is validated using a realistic case. The test results show that the proposed methodology is able to co-ordinate both objectives of interest, i.e., allocating CSs network with the maximized benefits and optimizing the fast charging service efficiency at the same time. |
| first_indexed | 2024-12-16T17:18:23Z |
| format | Article |
| id | doaj.art-78af5a12ea684de1a327bdd9ab21f5d0 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-16T17:18:23Z |
| publishDate | 2018-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-78af5a12ea684de1a327bdd9ab21f5d02022-12-21T22:23:14ZengIEEEIEEE Access2169-35362018-01-016360393604910.1109/ACCESS.2018.28438108371598Optimal Allocation Model for EV Charging Stations Coordinating Investor and User BenefitsYoubo Liu0Yue Xiang1https://orcid.org/0000-0001-8456-1195Yangyang Tan2Bin Wang3Junyong Liu4Zhiyu Yang5College of Electrical Engineering and Information Technology, Sichuan University, Chengdu, ChinaCollege of Electrical Engineering and Information Technology, Sichuan University, Chengdu, ChinaState Grid Chengdu Power Supply Company, Chengdu, ChinaDepartment of Electrical and Computer Engineering, Texas A&M University, College Station, TX, USACollege of Electrical Engineering and Information Technology, Sichuan University, Chengdu, ChinaCollege of Electrical Engineering and Information Technology, Sichuan University, Chengdu, ChinaDeploying charging stations (CSs) catering to the demand from electric vehicles plays an important role in modernizing energy infrastructures. In this paper, a bi-level optimal allocation model for allocating fast CSs is proposed aiming to maximize the CS investor benefit (upper layer sub-problem) by optimally allocating CSs with the coordinated determination of the expected efficiency of charging service supply (lower layer sub-problem). The efficiency is formulated as a charging performance index in terms of user satisfaction degree, which mathematically couples the upper level and lower level subproblems. The proposed nonlinear bi-level model is reduced to a single-layer optimization model under the Karush-Kuhn-Tucker optimality conditions. An improved dynamic differential evolution algorithm with an adaptive update strategy is proposed to solve this single-layer optimization model. The proposed method is validated using a realistic case. The test results show that the proposed methodology is able to co-ordinate both objectives of interest, i.e., allocating CSs network with the maximized benefits and optimizing the fast charging service efficiency at the same time.https://ieeexplore.ieee.org/document/8371598/EV charging stationoptimal allocation modeluser satisfaction degreebi-level programming |
| spellingShingle | Youbo Liu Yue Xiang Yangyang Tan Bin Wang Junyong Liu Zhiyu Yang Optimal Allocation Model for EV Charging Stations Coordinating Investor and User Benefits IEEE Access EV charging station optimal allocation model user satisfaction degree bi-level programming |
| title | Optimal Allocation Model for EV Charging Stations Coordinating Investor and User Benefits |
| title_full | Optimal Allocation Model for EV Charging Stations Coordinating Investor and User Benefits |
| title_fullStr | Optimal Allocation Model for EV Charging Stations Coordinating Investor and User Benefits |
| title_full_unstemmed | Optimal Allocation Model for EV Charging Stations Coordinating Investor and User Benefits |
| title_short | Optimal Allocation Model for EV Charging Stations Coordinating Investor and User Benefits |
| title_sort | optimal allocation model for ev charging stations coordinating investor and user benefits |
| topic | EV charging station optimal allocation model user satisfaction degree bi-level programming |
| url | https://ieeexplore.ieee.org/document/8371598/ |
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