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Main Authors: Liu, Ruiwu, Zhu, Yangjian
Format: Preprint
Published: 2026
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Online Access:https://arxiv.org/abs/2603.16202
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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