OPTIMIZED KINETICS

This project developed a system level optimization framework to support cost effective transit fleet electrification. Electrifying bus fleets requires coordinated planning across vehicle procurement, charging infrastructure deployment, grid capacity, and daily operations. Conventional approaches often rely on fixed bus to charger ratios or heuristic decision making, which can lead to oversized infrastructure and unnecessary capital costs.

To address this challenge, the project created a mixed integer linear programming model that integrates fleet operations, charging opportunities, grid constraints, distributed energy resources, techno economic analysis, and life cycle air quality impacts including PM2.5 and CO2e. General Transit Feed Specification data were converted into a discrete time operational format to simulate route level energy consumption and charging feasibility. The model minimizes total system cost, including both financial and air quality related costs, while meeting operational and physical constraints.

The framework was validated through a case study in San Bernardino, California, demonstrating significant reductions in infrastructure investment and overall electrification costs compared to a baseline plan. The resulting tool provides a scalable, repeatable, and data driven approach to transit electrification planning.

Figure 1. Available grid capacity in San Bernardino, California. Abbreviations: megawatt (MW).

Figure 2. Change to net health damages by switching from compressed natural gas to electric buses in San Bernardino, California. Negative health damages indicate a net benefit to human health. Abbreviations: United States Dollars (USD). Base map layer attributed to © Mapbox, © OpenStreetMap, and Improve this map.

Figure 3. Comparison of heuristic plan and optimal plan for charging deployment including a) charger count, b) procurement and installation cost, and c) total charging capacity. The charger power levels considered are 7.7-kilowatts (kW), 19.2-kW, 50-kW, 150-kW, 350-kW, and 500-kW. Abbreviations: megawatt (MW), million (M).

Figure 4. System cashflow for the heuristic plan (left) and optimal plan (right) from 2025 to 2040. The black dotted line indicates the yearly expenses of continued compressed natural gas only use. Abbreviations: battery electric vehicle (BEV); electric vehicle supply equipment (EVSE), photovoltaics with battery energy storage (PV + Battery), internal combustion engine vehicle (ICEV).

Figure 5. Net present system cost from 2025 to 2040 for the scenarios of no electrification (CNG only), heuristic plan, and optimal plan. Abbreviations: battery electric vehicle (BEV); electric vehicle supply equipment (EVSE), photovoltaics with battery energy storage (PV + Battery), internal combustion engine vehicle (ICEV).

Figure 6. Total energy flow across system for electric vehicle (EV) charging, onsite battery storage, and onsite solar for optimal scenario in 2040. Positive energy flow draws from the energy source and negative values supply the power. The dotted black line represents the energy needed to be supplied by the grid for each 15-minute timestep. Abbreviations: kilowatt-hour (kWh).

Figure 7. Transit service-blocks using electric buses in a) 2025, b) 2030, c) 2035, and d) 2040 based on the optimized plan transitioning from compressed natural gas buses. Base map layer attributed to © Mapbox, © OpenStreetMap, and Improve this map.