• Optimizing electric bus charging infrastructure and charging scheduling jointly. • Integrating shared micromobility and renewable energy with public transport. • Presenting a bi-level mixed-integer linear programming model. • Performing a large-scale case study in Gothenburg, Sweden. Public transport electrification contributes to the net-zero goal in the transport sector. However, high-power bus charging during peak hours places additional strain on the grid, while under-utilization of charging infrastructure limits its potential economic and social benefits. This study focuses on these challenges through integrated and shared optimization of battery electric buses (BEB) and shared micromobility systems (SMS) incorporating solar photovoltaic. We present a bi-level mixed-integer linear programming model (B-MILM) to jointly optimize BEB charging infrastructure, BEB charging schedules, solar PV installed capacity, and SMS charging schedule. The B-MILM is solved using a value-function-based exact approach. We derive a group of inequalities based on the problem characteristics to reduce solution time. A large-scale case study in Gothenburg, Sweden, demonstrates that solar photovoltaic and shared charging services yield annual cost savings 110% - 120% above investment costs for public transit agencies, even when the service fee revenue is excluded. Charging dispatching costs for e-scooter operators are reduced by up to 54%, and daily BEB charging grid loads decrease by 3% to 34% across seasons. The greenhouse emissions from electricity consumption of BEBs and e-scooters are reduced by 3%. The results offer new insights for sustainable charging and energy infrastructure planning and management for electric public transit.
Liu et al. (Wed,) studied this question.