Pareto-Based Power Management for Reconfigurable Multi-Point Multi-Power EV Charging Stations

Abstract

The increasing adoption of electric vehicles (EVs) is driving the need for more efficient, scalable, and flexible charging infrastructures. Among the most promising solutions are reconfigurable multi-point multi-power (MPMP) charging stations, which enable dynamic power allocation across multiple charging points operating at discrete power levels. This paper introduces a novel power management strategy for MPMP stations based on Pareto optimization, aiming to minimize the average charging time while ensuring fairness and efficiency. The method dynamically allocates power among charging points to minimize the average charging time across all connected EVs, while adhering to system constraints and the varying charging profiles required to preserve battery health. The proposed approach was validated through simulations in a dynamic scenario involving six EVs with heterogeneous battery capacities and charging profiles. Results demonstrated that the Pareto-based strategy achieved a significantly lower expected average charging time when compared to the first-come first-served strategy (FCFS).