Logo
ScienceStack
Table of Contents
Fetching ...
Sign In

Scheduling the Charge of Temporally Flexible Electric Vehicles: a Market-based Approach

Sabri El Amrani, Thibaut Horel, Saurabh Vaishampayan, Maryam Kamgarpour, Munther A. Dahleh

TL;DR

This work tackles scheduling for temporally flexible EVs to enable V2G arbitrage and reduce charging-station congestion. It models a capacity-constrained station with private driver preferences and solves a mixed-integer quadratic program approximately via ADMM, while using a VCG mechanism to elicit truthful private information. Case-study results indicate V2G profitability is contingent on lower battery-wear costs and price volatility, with substantial gains from drivers’ heterogeneous flexibility when congestion is high. The authors demonstrate that truthful preference elicitation is essential for optimal scheduling and show the mechanism can operate without subsidies, outlining paths for extending to networks of stations and uncertain preferences.

Abstract

The increasing electrification of human activities and the rapid integration of variable renewable energy sources strain the power grid. A solution to address the need for more grid storage is to use the battery of electric vehicles as a back-up capacity. However, drivers tend to disconnect their electric vehicle when its battery is needed the most. We propose a charge scheduler that incentivizes drivers to delay their disconnection to improve vehicle-to-grid services. We also leverage drivers' temporal flexibility to alleviate congestion in oversubscribed charging stations. We formulate the computation of an optimal flexible schedule as a mixed-integer quadratic problem. We tractably approximate its solution using the Alternating Direction Method of Multipliers. Considering the possibility that strategic drivers misreport their charging preferences to the station coordinator, we then propose a Vickrey-Clarke-Groves mechanism that incentivizes truthful reporting. We conclude with a simulated case study using real-world data to quantitatively assess the added value of drivers' temporal flexibility for enhancing vehicle-to-grid services and reducing station congestion.

Scheduling the Charge of Temporally Flexible Electric Vehicles: a Market-based Approach

TL;DR

This work tackles scheduling for temporally flexible EVs to enable V2G arbitrage and reduce charging-station congestion. It models a capacity-constrained station with private driver preferences and solves a mixed-integer quadratic program approximately via ADMM, while using a VCG mechanism to elicit truthful private information. Case-study results indicate V2G profitability is contingent on lower battery-wear costs and price volatility, with substantial gains from drivers’ heterogeneous flexibility when congestion is high. The authors demonstrate that truthful preference elicitation is essential for optimal scheduling and show the mechanism can operate without subsidies, outlining paths for extending to networks of stations and uncertain preferences.

Abstract

The increasing electrification of human activities and the rapid integration of variable renewable energy sources strain the power grid. A solution to address the need for more grid storage is to use the battery of electric vehicles as a back-up capacity. However, drivers tend to disconnect their electric vehicle when its battery is needed the most. We propose a charge scheduler that incentivizes drivers to delay their disconnection to improve vehicle-to-grid services. We also leverage drivers' temporal flexibility to alleviate congestion in oversubscribed charging stations. We formulate the computation of an optimal flexible schedule as a mixed-integer quadratic problem. We tractably approximate its solution using the Alternating Direction Method of Multipliers. Considering the possibility that strategic drivers misreport their charging preferences to the station coordinator, we then propose a Vickrey-Clarke-Groves mechanism that incentivizes truthful reporting. We conclude with a simulated case study using real-world data to quantitatively assess the added value of drivers' temporal flexibility for enhancing vehicle-to-grid services and reducing station congestion.

Paper Structure

This paper contains 16 sections, 13 equations, 10 figures, 1 table.

Table of Contents

  1. Introduction
  2. Scheduling the Charge of Flexible Electric Vehicles
  3. The Scheduling Problem
  4. The Models of the Charging station and the Electric Vehicles
  5. The Scheduling Decision
  6. The Scheduling Objective
  7. A Decomposition Technique for Efficient Scheduling
  8. Eliciting Electric Vehicle Drivers' Private Charging Preferences
  9. The Mechanism Design Problem
  10. The Vickrey–Clarke–Groves Mechanism
  11. Case Study
  12. Simulation Set-up
  13. The Impact of Battery Wear and Drivers' Temporal Flexibility on Vehicle-to-Grid
  14. The Benefits of Temporal Flexibility for the Alleviation of Station Congestion
  15. An Empirical Analysis of Vickrey–Clarke–Groves Taxes
  16. ...and 1 more sections

Figures (10)

  • Figure 1: A schematic representation of the model of the charging station.
  • Figure 2: Real-world datasets used in our case study. (a) Market prices in New England (Nov. 1, 2023 to Oct. 31, 2024) iso_new_england_pricing_2024. (b) EV disconnection times at a parking lot (Nov. 1, 2018 to Jan. 2, 2019)lee_acn-data_2019. (c) Initial and final charge of EVs in 3 charging stations distributed_electrical_systems_laboratory_desl_epfl_desl-epfllevel-3-ev-charging-dataset_2025. (d) Compensation requested by drivers to delay their scheduled departure by one hour according to a survey suel_vehicle--grid_2024. This compensation for a one-hour delay also corresponds to the value of the inflexibility coefficient $\alpha_n$ in our EV cost model \ref{['eq:ev_cost']}.
  • Figure 3: Optimal flexible scheduling with energy market prices of Jan. 17, 2024, in a regularly congested station. (a) Bidirectional charging is not profitable with the real battery wear cost of 0.13 $/kWh. (b) Bidirectional charging becomes profitable when battery wear cost is reduced by 75%.
  • Figure 4: Total cost savings of a flexible bidirectional charge schedule with respect to a flexible unidirectional charging schedule, as a function of the battery wear cost (mean value and standard deviation over 20 randomly sampled runs, regularly congested station). The lower the battery wear cost, the more savings can be made by allowing bidirectional power flows. Increasing drivers' temporal inflexibility does not increase cost savings because the profits from bidirectional charging are too small to justify delays.
  • Figure 5: Optimal flexible scheduling with energy market prices of Jan. 17, 2024. (a) Delays are not scheduled with a regular EVCS power limit of 15 kW. (b) Delays become necessary with a lower EVCS power limit of 10 kW.
  • ...and 5 more figures

Theorems & Definitions (3)

  • Definition 1: Mechanism
  • Definition 2: Vickrey--Clarke--Groves mechanism
  • proof