Efficient Electric Vehicle Charging Allocation: A Two-Stage Optimization and Participation Analysis

Ruiwu Liu and Yangjian Zhu

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Abstract: 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.

Date: 2026-03
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