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| Main Authors: | , |
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| Format: | Preprint |
| Published: |
2026
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2603.16202 |
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| _version_ | 1866908893232234496 |
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| author | Liu, Ruiwu Zhu, Yangjian |
| author_facet | Liu, Ruiwu Zhu, Yangjian |
| contents | Electric vehicles (EVs) require substantially longer refueling times than gasoline vehicles, which can generate severe congestion at charging stations when demand concentrates. We propose a two-stage allocation framework for EV charging networks. In Stage 1, a central coordinator determines station-level admission quotas to control worst-station delay using a queue-informed congestion metric. In Stage 2, given these quotas and feasibility constraints (e.g., reachability), the coordinator solves a utility-maximizing capacitated assignment to allocate EVs across stations. To keep Stage~2 tractable while capturing heterogeneous charging needs, we precompute each EV-station pair's optimal charging amount in closed form under a battery-capacity constraint and then solve a transportation/assignment problem. Finally, we introduce a reduced-form participation model to characterize adoption thresholds under network benefits, spillovers, and coordination costs. Numerical experiments illustrate substantial reductions in worst-case congestion with limited impact on average utility, and highlight scaling patterns as the number of stations increases. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2603_16202 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Efficient Electric Vehicle Charging Allocation: A Two-Stage Optimization and Participation Analysis Liu, Ruiwu Zhu, Yangjian Theoretical Economics Electric vehicles (EVs) require substantially longer refueling times than gasoline vehicles, which can generate severe congestion at charging stations when demand concentrates. We propose a two-stage allocation framework for EV charging networks. In Stage 1, a central coordinator determines station-level admission quotas to control worst-station delay using a queue-informed congestion metric. In Stage 2, given these quotas and feasibility constraints (e.g., reachability), the coordinator solves a utility-maximizing capacitated assignment to allocate EVs across stations. To keep Stage~2 tractable while capturing heterogeneous charging needs, we precompute each EV-station pair's optimal charging amount in closed form under a battery-capacity constraint and then solve a transportation/assignment problem. Finally, we introduce a reduced-form participation model to characterize adoption thresholds under network benefits, spillovers, and coordination costs. Numerical experiments illustrate substantial reductions in worst-case congestion with limited impact on average utility, and highlight scaling patterns as the number of stations increases. |
| title | Efficient Electric Vehicle Charging Allocation: A Two-Stage Optimization and Participation Analysis |
| topic | Theoretical Economics |
| url | https://arxiv.org/abs/2603.16202 |