The National Academies

Transit IDEA J-04/IDEA 096 [Completed (IDEA)]

Multi-stage Planning for Electrifying Transit Bus Systems with Multiformat Charging Facilities
[ TCRP J-04 (Innovations Deserving Exploratory Analysis--The Transit IDEA Program) ]

  Project Data
Funds: $100,000
Staff Responsibility: Velvet Fitzpatrick
Research Agency: University of South Florida
Principal Investigator: Yu Zhang
Fiscal Year: 2019

Although electric transit bus systems (ETBS) present significant benefits, it is challenging for a public transit authority to plan the process of electrifying its bus fleet and continue to operate its mixed fleet cost-effectively. This IDEA project developed a decision support tool for public transit authorities for facilitating the process of electrifying their transit buses. Mathematical models of dynamic wireless charging facilities (DWCF) locations for full electrification and partial electrification (multi-objective optimization), and models for route selection and DWCF locations were developed (multi-stage optimization). Solutions algorithms were exploited to solve large scale multi-stage multi-objective optimization problems. Specifically, given the periodic budget and transit network and features, the tool would provide outcomes at different stages, including (1) which routes the acquired electric buses should serve, (2) where to deploy charging facilities (both plug-in at stations and dynamic wireless charging facilities (DWCF) embedded in road pavement), and (3) what should be the right size of the onboard battery for a specific route. The proposed method was applied to a local transit network, HART, in the Tampa Bay area. For a given scenario, i.e., the transit authority needs to choose five routes to electrify in the first stage and another five in the second stage, the tool identified the best routes to electrify and optimal locations of DWCF in both stages. Following the solutions, the transit authority will bear the minimal total cost of constructing DWCF and energy consumptions in a defined planning horizon. Furthermore, the research team developed a Graphic User Interface (GUI) on a Linux system that consolidated data structure design, solution algorithm implementation, economic analysis, and design result visualization. A user manual was produced to help potential users to understand and become familiar with the tool. Users can perform scenario analysis with this tool by changing setting parameters, such as number of routes to be electrified (or budget constraint), cost of DWCF, price of electricity, etc.

The final report is available.

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