MULTI-AGENT SYSTEM APPROACH TO OPTIMIZE THE MANAGEMENT OF URBAN ELECTROMOBILITY

The challenge of this paper is to contribute to the creation of sustainable urban transport systems, reduce air pollution, and mitigate the effects of climate change through the use of intelligent agents’ tools. This framework proposes a multi-agent system tool able to optimize the charging schedules of electric vehicles to match renewable energy availability. Precisely, the software tool developed, which models and simulates complex interactions between vehicles, charging stations, the grid, and the environment, is used to explore different scenarios and evaluate the impact of policy interventions on the sustainable charging behavior of drivers. This solution represents a robust, scalable, and adaptable approach to managing electromobility. It explores how multi-agent systems can be used to enhance grid resilience, particularly through vehicle-to-grid technologies, which can balance energy supply and demand. Moreover, emphasizes the need for a unified framework that integrates various domains and stakeholders to achieve a more efficient and sustainable urban transportation system.