Reducing Carbon Emissions of EV Charging via User Behavior and Carbon Intensity Analysis

Abstract

The increased adoption of electric vehicles (EVs) has the potential to significantly reduce carbon emissions by decreasing reliance on fossil fuels. However, as more EVs populate our roads, there will be a heightened demand for electricity from the grid, leading to increased carbon emissions due to EV charging. Currently, most EV owners do not align their charging behavior with periods of low carbon intensity in the power grid. To reduce the carbon emissions resulting from EV charging, it is essential to alter the charging behavior of EV users. To tackle this problem, we propose a solution that leverages user charging behavior data with carbon intensity data to identify optimal charging times for EVs, resulting in reduced carbon emissions. Our simulation results using 10,000 EVs demonstrate that the proposed carbon-aware EV charging algorithm can reduce 9.3% of carbon emissions by optimizing EV charging times.