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

Fangting Zhou, Jiaming Wu, Balazs Kulcsar

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 bidding, operator decisions, and user acceptance. Numerical case studies reveal trade-offs among user acceptance, operator revenue, and charging capacity utilization under different charging levels. The findings provide practical guidance and insights into designing flexible pricing schemes that better accommodate heterogeneous user preferences while improving system efficiency.

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. 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 bidding, operator decisions, and user acceptance. Numerical case studies reveal trade-offs among user acceptance, operator revenue, and charging capacity utilization under different charging levels. The findings provide practical guidance and insights into designing flexible pricing schemes that better accommodate heterogeneous user preferences while improving system efficiency.

Paper Structure

This paper contains 19 sections, 23 equations, 12 figures, 2 tables.

Table of Contents

  1. Introduction
  2. Literature review
  3. Methodology
  4. Step 1: User Bidding
  5. Step 2: Operator Decision Model for Bid Response
  6. Step 3: User Response and Acceptance Decision
  7. Numerical experiments
  8. Scenario design
  9. Homogeneous users
  10. Single charging rate
  11. Multiple charging rates
  12. Heterogeneous users
  13. Single charging rate
  14. Multiple charging rates
  15. Large-scale cases
  16. ...and 4 more sections

Figures (12)

  • Figure 1: Three-step negotiation process between users and the operator.
  • Figure 2: Impact of $\gamma$ on system outcomes.
  • Figure 3: Final prices vs. user bidding prices under different $\gamma$ values.
  • Figure 4: User-level outcomes under varying values of $\gamma$.
  • Figure 5: User-level outcomes under varying values of $\gamma$ with expanded bid range $[1, 6]$
  • ...and 7 more figures