The increasing deployment of electric vehicles (EVs) across the United States has introduced many new opportunities and challenges with regards to energy management and control. In smart and connected communities (SCCs), where advanced communication infrastructures are in place, optimal coordination of EVs can significantly impact EV owners, power systems, and charging station owners. This paper develops two scheduling frameworks (static and dynamic) for optimal coordination of a fleet of cooperative EVs in a community with many charging stations and potentially different types of chargers (e.g., level 1, level 2, and DC fast). The scheduling problems are formulated as mixed-integer multi-objective optimization models and then multi-objective solution methods are utilized to find the optimal solution for each of the two scheduling frameworks. Numerical experiments simulated based on the State of Florida verify the usefulness of smart charging for better energy management and satisfying key players' objectives and constraints.
- electric vehicles
- multi-objective mixed-integer programming
- optimal coordination
- Smart & connected communities
- smart control
ASJC Scopus subject areas
- Computer Science(all)