An electric commuter bus battery-swapping and charging–discharging schedules collaborative optimization strategy based on the collaborative operation of electric buses and renewable energy stations

• An EBS-CDS-CO model is proposed. • A feasibility assessment method for battery-swapping schedules is proposed. • An IALNS-PSO algorithm is introduced. • Verify and analyze strategy performance by comparing to a range of cases. Cities such as Beijing and Shanghai in China have almost fully electrified their commuter buses. These electric buses (EBs) collaborate with distributed renewable energy stations (RESs) near the city to form stakeholders. By charging the lithium batteries of EBs through RESs, one can improve the utilization rate of distributed energy and alleviate the load pressure on the distribution network. Compared with traditional methods that focus solely on optimizing the charging side of EBs, this study establishes an EB battery-swapping and charging–discharging schedule collaborative optimization model. To achieve the objective of maximizing the benefits while optimizing the battery charging–discharging schedule, one should adjust the battery-swapping schedule accordingly, which, in turn, requires modifications to the EBs’ operational schedule to maintain coordination. As it is necessary to determine whether the swapping schedule meets the daily operational tasks of the EBs, a feasibility assessment method is proposed that incorporates EB operational schedule adjustments. To solve this nonlinear discrete dynamic programming model, this study proposes a heuristic algorithm that combines improved adaptive large neighborhood search (ALNS) and particle swarm optimization. Moreover, a new operator category—time operator—is introduced into the ALNS algorithm to enhance performance. Simulations were conducted to validate this approach. Finally, the approach was applied at a real bus station and partnering wind farm in Beijing. Compared with the regular operation of the wind farm, our optimized approach increases the daily income by ¥1440.76. Thus, it can achieve enhanced cooperation between bus stations and RESs.