A Multi-Criterion Approach to Smart EV Charging with CO2 Emissions and Cost Minimization

In this work, we propose a novel three-step framework for smart electric vehicle (EV) charging that jointly minimizes charging costs and CO2 emissions. Drawing inspiration from the classical Unit Commitment Problem (UCP), we first design a linear model to determine the optimal power generation mix over a 24-hour horizon, using real-world data from Vietnam, a country with a highly carbon intensive energy system. This allows us to estimate time-varying CO2 emissions and translate them into an emission cost signal. We then incorporate this environmental cost into a smart charging optimization model, formulated as a linear program (LP). Numerical simulations confirm that the proposed strategy significantly outperforms a baseline First-In-First-Served (FIFS) approach, achieving notable reductions in both CO2 emissions and charging costs also compared to another optimization approach. The results demonstrate the potential of this multiobjective optimization framework to support more sustainable and cost-efficient EV charging strategies.