A user-driven pricing and scheduling framework for public electric vehicle charging

Abstract

Public electric vehicle (EV) charging infrastructure has expanded rapidly, yet utilization across charging stations remains uneven and often inefficient. Existing operator-determined pricing schemes offer limited flexibility to coordinate heterogeneous user demand within constrained capacity, especially when users differ in willingness to pay, desired energy quantity, and acceptable charging times. This study proposes a user-driven pricing and scheduling framework for public EV charging. Users submit advance bids specifying acceptable time slots, bid prices, and charging quantity bounds. Based on these bids, the charging operator jointly decides whether to accept the original bid, issue a counter-offer, or reject the request, while assigning charging rates and continuous charging schedules. The operator’s decision problem is formulated as a mixed-integer linear program that maximizes planned profit under pricing constraints, charger-capacity limits, energy-demand bounds, and charging-continuity requirements. The framework is user-driven because user-submitted bids inform operator-side pricing and scheduling decisions, while a utility-based response layer evaluates users’ final acceptance of the resulting offers. Numerical case studies are conducted under homogeneous and heterogeneous user settings, single- and multi-rate charger configurations, and different bid-preservation levels. The results reveal trade-offs among planned and realized profits, offered-price fairness, final user acceptance, and charging utilization. Greater pricing flexibility increases planned profit, whereas stronger bid preservation limits markups and can improve final acceptance, although overly restrictive preservation can reduce allocation coverage. Heterogeneous charger configurations improve scheduling flexibility and help accommodate users with different time windows and service requirements. Benchmark comparisons show that rate-dependent fixed tariffs yield higher absolute realized profits, whereas moderate bid-preservation levels achieve higher profit realization, realized service rates, and charging utilization. These comparative patterns remain stable across 100 user-preference scenarios. The findings provide practical guidance and insights into designing flexible, bid-informed pricing schemes that better align heterogeneous user preferences with system-level charging operations.

Keywords

electric vehicle / public charging / user-driven / pricing / charging scheduling

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Higher Education Press 2026

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