This paper proposes a 24/7 Carbon-Free Electric Fleet digital twin framework for modeling, controlling, and analyzing an electric bus fleet, co-located solar photovoltaic arrays, and a battery energy storage system. The framework consists of forecasting modules for marginal grid emissions factors, solar generation, and bus energy consumption that are input to the optimization module, which determines bus and battery operations at minimal electricity and emissions costs. We present a digital platform based on this framework. For a case study of Stanford Universityâ€™s Marguerite Shuttle, the platform reduced peak charging demand by 99%, electric utility bill by $2779, and associated carbon emissions by 100% for one week of simulated operations for 38 buses. When accounting for operational uncertainty, the platform still reduced the utility bill by $784 and emissions by 63%.
Keywords decarbonization, electric buses, digital twin, charging scheduling, battery storage, optimal planning