Effect of Battery Size on Emission Reduction of Predictive Electric Vehicle Charging Control

As electric vehicle (EV) adoption accelerates, the grid's ability to support widespread charging in a clean and cost effective manner is facing increasing strain. Software-controlled charging of EVs may be the key solution to integrate large numbers of EVs into renewable energy systems, distributing load temporally to align with renewable generation, reducing peak demand, and thus minimizing carbon emissions. The effectiveness of controlled charging, however, is in many circumstances moderated by the EV battery capacity, which is an oftenoverlooked factor in discussions of EV-grid integration. This paper investigates the effect of battery capacity on the potential of software-controlled charging to reduce carbon emissions from charging processes. Using a model predictive control (MPC) based smart charging framework, and data from the UK National Grid to simulate 800 distinct domestic charging scenarios, we demonstrate that larger battery capacities can, under certain conditions, lead to improved emission reductions in controlled charging processes. Achievable reductions, however, depend on the length of prediction horizons, user preferences, and daily energy consumption. Nudging drivers towards aligning smart charger settings with actual daily energy consumption may equally lead to enhanced emission reduction.