Bidding for Preferred Timing: An Auction Design for Electric Vehicle Charging Station Scheduling
Year: 2019
Type: article
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.
Authors: Luyang Hou, Chun Wang, Jun Yan
Institution: Concordia University
Language: English
Subfield: Electrical and Electronic Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: green
Awards: G2131855727, Soutien à la recherche pour l'établissement de la relève professorale — Réseaux électriques, Exploration de données (Data mining), G4214431443, G4550914251, Cyber-Physical Security for Critical Internet-of-Things Infrastructures, Dynamic Scheduling Mechanism Design in Multi-Agent Systems, G814497173, G8748828179
OpenAlex ID: W2963540437