MILP-Based Optimization of Electric Bus Charging Considering Battery Degradation and Environmental Factors Under TOU Pricing

The transition from conventional fossil-fueled buses to electric buses (EBs) is accelerating in the global public transportation sector. However, owing to the limitations of battery lifespan and capacity, EBs have a shorter driving range than conventional buses, and their power consumption is highly variable depending on the ambient temperature. In addition, battery lifespans are affected by charging and discharging cycles and battery age over time in all situations, which requires a method of operation that considers these factors. In this study, we estimated the driving, heating, and cooling energy consumptions based on the dispatch schedule and actual power consumption of EBs. The estimated energy consumption was then used as an input to plan the amount of charging power by time of day to optimize the charging and battery degradation costs. The optimization methodology employed mixed-integer linear programming (MILP), which facilitates discrete charging decision-making and ensures an optimum solution for operation costs by taking cost factors into account. In this phase, the scenarios were configured according to the time-of-use (TOU) charging cost and whether or not battery degradation. Battery degradation can be divided into cycle and calendar aging. The scenarios that considered both TOU and battery degradation reduced the average operating costs by approximately 1.43, 12.3, and 5.69% in spring/fall, summer, and winter, respectively, compared with scenarios that did not consider either.