Multi-objective Strategic Behavioural Optimization via Consensus and Game Theory for Electric Vehicle Daily Charging

As the number of Electric Vehicles (EVs) rises, optimizing the charging process becomes essential to efficiently utilize resources and minimize charging fees, thereby improving customer satisfaction. While various methods have been proposed, they typically target either charging stations or home charging independently. In this paper, we assess the entire daily charging behavior of users, including both daytime public charging and nighttime home charging, each with a distinct approach. A Consensus Distributed Algorithm is used to allocate Photovoltaic (PV) resources for daytime public charging, while a Game Theory-based algorithm leveraging Vehicle-to-Grid (V2G) technology is applied for nighttime home charging. Our results show a reduction in daytime and nighttime charging costs by up to 11.3% and 41% compared to conventional methods, alongside a flatter load profile where the peak dropped by 46.3% at night.