A Game Theory Approach to Optimizing Electric Vehicle Charging Infrastructure in Urban Areas

Abstract

The growing demand for electric vehicles (EVs) presents significant challenges for urban charging infrastructure, particularly in balancing user demand, operational efficiency, and grid stability. This study applies non-cooperative and cooperative game theory models to analyze the interactions between EV users, charging station operators, and grid managers. The non-cooperative model shows that self-interested behavior leads to congestion at high-demand stations, inefficient pricing dynamics, and grid overloads during peak hours. Stakeholders reach a Nash Equilibrium, but the resulting system inefficiencies-uneven station utilization and high grid loads-highlight the need for coordinated strategies. In contrast, the cooperative game theory model fosters collaboration among stakeholders, leading to significant improvements in system performance. Through dynamic pricing strategies and off-peak charging incentives, the cooperative model achieves more balanced demand across stations and ensures grid stability by preventing peak-hour overloads. Simulations demonstrate that this approach reduces congestion and stabilizes pricing while maintaining grid loads well below maximum capacity. The research underscores the value of cooperative strategies in creating a sustainable and scalable EV charging network. Key challenges include the need for data sharing, stakeholder alignment, and user behavior adjustment. Addressing these issues will be essential for the widespread implementation of cooperative charging systems. Future research should focus on real-world trials and policy development to support large-scale adoption of these solutions.