Optimization of Carbon Dioxide in Electric Vehicles Using Charging Stations with Renewable Sources

The transition to electric vehicles (EVs) is widely promoted as a strategy to reduce greenhouse gas emissions from transportation. However, the environmental benefits of EVs depend strongly on the electricity mix used for charging. If charging is predominantly supplied by fossil-fuel-based grid electricity, the resulting carbon dioxide (CO2) emissions may remain substantial. Renewable-powered charging stations offer a solution, yet their spatial distribution creates a trade-off: if they are located further from the driver than their grid counterparts, then more CO2 might be emitted along the way. This study developed and validated a framework for quantifying this trade-off. A mathematical model was first constructed, in which charging stations were spatially distributed following a Poisson process, and renewable availability was described by a Gaussian distribution. Emissions were measured in terms of mCO2, the mass of CO2 emitted by driving and charging. The model was then tested by comparing it with a MATLAB-based computer simulation incorporating stochastic station distributions and vehicle energy states. Both approaches identified a distinct minimum in the emission–distance curve. The mathematical model located the optimum at 3.737 km, while the computer simulation confirmed the result within an interval of 2.844–4.266 km. These findings prove the existence of an optimal charging distance. The results highlight the value of considering various parameters during EV infrastructure planning and offer practical guidance to reduce life-cycle emissions in sustainable mobility systems.