Abstract Manager

Electrifying urban buses is a global initiative toward achieving sustainable transportation. Effective bus electrification requires tactical planning strategies to ensure significant reductions in greenhouse gas emissions. This study presents an integrated optimization model that simultaneously addresses charging infrastructure placement, battery type selection, and charging scheduling. We incorporate the impact of time-of-day electricity pricing, enabling a realistic assessment of charging costs under varying energy rates. To address the computational complexity of large-scale network problems, we develop an algorithm that divides the problem into three interrelated subproblems, enhancing efficiency while preserving accuracy. The first subproblem, the preparation phase, focuses on preprocessing and structuring input data from widely available GTFS (General Transit Feed Specification) feeds to identify trips, routes, and potential charging locations. The second subproblem involves determining the optimal location of equipped terminals where charging facilities should be placed and calculating the upper bounds of battery levels for each bus based on operational constraints. This phase refines the solution space by identifying the most strategic locations for charging infrastructure. Finally, in the third subproblem, the algorithm optimizes battery type allocation and charging schedules for buses, accounting for factors such as time-of-day electricity pricing and operational efficiency. We consider a stylized network and analyze GTFS data from 5 transit agencies to evaluate the effectiveness of the proposed heuristic algorithm. A comparison between exact and heuristic solutions shows that the maximum percentage error is approximately 2.2%, demonstrating the heuristic algorithm's ability to find near-optimal results. Sensitivity analysis reveals that energy consumption rates significantly influence optimal solutions. However, improving charging efficiency requires complementary strategies beyond simply adjusting charging rates. Additionally, we examine 20 cities to derive actionable insights. In Calgary, about 20% of buses cannot be electrified even when utilizing charging facilities during all layover periods, highlighting the need for scheduling adjustments. Cities such as Brooklyn, Washington, and Philadelphia can achieve high electrification with limited reliance on additional on-route charging infrastructure, emphasizing the feasibility of prioritizing overnight charging in their transition to electric buses. Conversely, cities like Los Angeles, Houston, and Calgary demonstrate a steep rise in charging demands as electrification levels increase, reflecting a significant dependency on on-route charging infrastructure.