Bidding for Preferred Timing: An Auction Design for Electric Vehicle Charging Station Scheduling

Abstract

This paper considers an electric vehicle charging scheduling setting where vehicle users can reserve charging time in advance at a charging station. In this setting, users are allowed to explicitly express their preferences over different start times and the length of charging periods for charging their vehicles. The goal is to compute optimal charging schedules that maximize the social welfare of all users given their time preferences and the state of charge of their vehicles. Assuming that users are self-interested agents who may behave strategically to advance their own benefits rather than the social welfare of all agents, we propose an iterative auction, which computes high-quality schedules and, at the same time, preserves users' privacy by progressively eliciting their preferences as necessary. We conduct a game theoretical analysis on the proposed iterative auction to prove its individual rationality and the best response for agents. Through extensive experiments, we demonstrate that the iterative auction can achieve high-efficiency solutions with a partial value information. Additionally, we explore the relationship between scheduling efficiency and information revelation in the auction.

An iterative combinatorialauctionmechanism formulti-agentparallel machinescheduling

“…Amir, Sharon, and Stern (2015) handled the situation where many bundles are submitted by each agent in the multi-agent pathfinding problem. Hou, Wang, and Yan (2019) allowed users to bid for different preferred time windows at one time in electric vehicle charging scheduling problem. The similar ideas are also discussed in other decentralised decision-making problems (L. Liu, Wang, and Wang 2019;Bansal, Uzsoy, and Kempf 2020;Sen, Bagchi, and Chakraborty 2020;Ahn, Kim, and Kim 2021).…”

Optimal Game-Based Energy Management with Renewable Energy for Secure Electric Vehicles Charging in Internet of Things

“…where F re (p re (t), p tr (t)) is the subsidy function for selling RE and C re (D re (t)) is the investment function for RE generation. According to [6,8], we define that…”

“…EVs play a significant role on the transportation in IoT [5]. With consideration of EVs' limited capacity, they have to charge their batteries frequently, which bring about the unfavorable effect on the applications of EVs [6]. Fortunately, fixed charging stations (FCSs) can solve the charging problem in a convenient way.…”

“…us, when EVs arrive at an overload FCS, they have to wait for a long time to be served due to the large amount of energy demand, including the time spent in the driving route. Besides, a potential shortcoming for charging EVs is the high fast-charging requirement to improve the number of supplying EVs per hour [6,8]. ough energy operators supply the fastcharging service to EV users, the high payment in designing the charging stations is nonnegligible.…”

Reducing Waiting Times at Charging Stations with Adaptive Electric Vehicle Route Planning

“…Most of these systems have a first-come-first-serve policy, but some can also prioritize reservations, leading to cases where high priority vehicles can charge before others even if they arrive later at the charging station [24]. Hou et al [25] use a scheduler that allocates reservations based on user given information about their time preferences. Due to the assumption that users are selfish and do not want to reveal their true time preferences to avoid unfavorable time slots, they propose an iterative auction which, by progressively eliciting the users' preferences as necessary, preserves their privacy.…”