Distributed Control for Large-Scale EV Charging Ecosystems with Coordinated Charging

Abstract

The rapid growth of electric vehicle adoption is turning charging infrastructure into a tightly coupled energy-service network that affects feeder loading, station utilization, and charging service quality. Existing studies have addressed smart charging, coordinated charging, hierarchical control, distributed energy management, and multi-agent scheduling, showing that coordination can improve charging efficiency and reduce congestion. However, these approaches are often fragmented across local optimization or feeder-level mitigation, leaving a gap in scalable frameworks that jointly support local autonomy, regional coordination, and grid-aware supervisory control. To address this gap, this article presents a distributed control and coordination framework for largescale EV charging ecosystems based on station-level intelligence, regional coordination signals, and a supervisory operating layer. The methodology defines the main control variables, coordination logic, and fairness-aware charging strategy, while the results show improved load balancing, reduced grid stress, and controlled charging delay under increasing EV penetration. Overall, the study demonstrates that distributed and hierarchical coordination offers a practical foundation for scalable EV charging management in high-demand environments.