Control of Charging of Electric Vehicles Through Menu-Based Pricing

Ghosh, Arnob; Aggarwal, Vaneet · 2018 · Crossref

DOI: 10.1109/tsg.2017.2698830

archive: archived pipeline: cataloged verified

Get this paper ↗ (DOI — opens at the source; we link to it, we don't host it)

Summary

This paper addresses the challenge of efficiently managing electric vehicle (EV) charging stations by proposing an online, menu-based pricing mechanism. The motivation stems from the need to balance two conflicting objectives: maximizing the profit of charging stations to ensure their economic viability and deployment, and maximizing social welfare (the sum of station profit and user surplus) to incentivize EV adoption and reduce environmental impact. The authors aim to control both the energy consumption and the charging deadline of arriving EVs through dynamic pricing, thereby optimizing resource utilization in stations equipped with limited charging spots and hybrid energy sources (renewable harvesting and conventional grid energy). The study models a charging station that offers a menu of contracts to each arriving user, where each contract specifies a certain amount of energy and a deadline for completion at a prescribed price. Users select the contract that maximizes their surplus or reject all options. The charging station is modeled as myopic, making pricing decisions based on current arrivals and existing commitments without knowledge of future arrivals. The cost of fulfilling a contract is determined by solving a linear programming problem that minimizes the cost of procuring energy from renewable storage and the conventional market, subject to battery capacity and charging rate constraints. The authors analyze pricing strategies under two scenarios: when the station has perfect knowledge of user utilities (clairvoyant) and when it only knows the statistical distribution of utilities. The results demonstrate that while a pricing strategy based on marginal cost maximizes social welfare, it yields zero profit for the station, rendering it economically unviable. When user utilities are unknown, the authors prove that no single pricing strategy can simultaneously maximize ex-post social welfare and expected profit. To address this, they propose a "fixed profit pricing strategy" that guarantees a specific profit level for the station while maximizing social welfare with a high probability. Theoretical analysis shows that this strategy can achieve maximum profit for certain classes of utility functions. Empirical evaluations indicate that the proposed menu-based pricing reduces peak demand and improves the utilization of charging spots compared to existing mechanisms, allowing for fewer physical spots to serve the same demand. The significance of this work lies in providing a practical, online pricing framework that reconciles economic incentives for charging station operators with regulatory goals for social welfare. By allowing users to trade off charging speed for lower prices, the mechanism encourages efficient use of renewable energy and reduces strain on the grid. The findings suggest that menu-based pricing is superior to traditional time-of-use or deadline-differentiated pricing in online settings, as it offers greater flexibility and ensures contract fulfillment without requiring users to manage complex charging schedules. This approach supports the scalable deployment of EV infrastructure by ensuring profitability while maintaining high social welfare.

Provenance

The full processing record for this entry. Every stage of this paper's journey through the pipeline is logged — what ran, with which tool and model, how many attempts it took, and when it last completed.

Summary generated by qwen3.6-27b-prismaquant on 2026-06-26; verification: verified.

Topics

Ranked by relevance to this paper. Hover a topic for its definition.

• telematics ubi feedback