A user-driven pricing and scheduling framework for public electric vehicle charging
Fangting Zhou, Jiaming Wu, Balazs Kulcsar

TL;DR
This paper introduces a user-driven pricing and scheduling framework for public EV charging stations, aiming to improve efficiency and user satisfaction through bid-based interactions.
Contribution
It presents a novel three-stage bidding and decision framework that incorporates user preferences, operator profit, and capacity constraints for EV charging.
Findings
Numerical case studies show trade-offs between user acceptance and operator revenue.
Flexible pricing schemes can enhance system efficiency and user satisfaction.
The framework effectively balances heterogeneous user demands with capacity constraints.
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. 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 quantity bounds. Based on these bids, the charging operator determines prices and charging slot assignments. After observing the outcomes, users decide whether to accept the resulting prices and allocations. The operator's decision problem incorporates profit objectives, user participation requirements, and capacity constraints across charging levels and time slots. The framework captures a three-stage interaction involving user…
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