A Multi-Objective Optimization Approach for Load Smoothing and Rapid PEV Charging in Low-Voltage Networks

Abstract

The widespread adoption of Plug-in Electric Vehicles (PEVs) creates significant challenges for existing low-voltage (LV) distribution networks, including voltage deviations, load imbalance, and increased stress on grid assets. This paper proposes a multi-objective optimization framework for coordinated PEV charging that jointly considers grid load smoothing and rapid charging. An energy management system (EMS) dynamically allocates charging power according to network conditions and user charging requirements. A Pareto-front analysis is used to characterize the trade-off between charging speed and grid performance, while Jain’s Fairness Index and the Gini coefficient assess the equity of charging among users. Simulation results show that the proposed strategy smooths the power profile and maintains fair charging progress across all vehicles. The voltage evaluation further identifies operating points that may lead to voltage violations at the most critical bus under high PEV penetration, highlighting the need for voltage-aware charging coordination in future LV networks.