Mobility-Aware Smart Charging of Electric Bus Fleets

TL;DR

This paper presents a mixed integer linear programming approach for optimizing route assignment and charging schedules of electric bus fleets to maximize solar energy use and minimize costs, validated through a real-world case study.

Contribution

It introduces a novel MILP model for joint route and charge scheduling considering real-world constraints and solar forecasts, improving operational cost efficiency.

Findings

Significant cost savings demonstrated in case study.

Effective integration of solar energy into bus charging schedules.

Validated approach for large-scale electric bus fleet management.

Abstract

We study the joint route assignment and charge scheduling problem of a transit system dispatcher operating a fleet of electric buses in order to maximize solar energy integration and reduce energy costs. Specifically, we consider a complex bus transit system with preexisting routes, limited charging infrastructure, limited number of electric buses, and time-varying electricity rates. We present a mixed integer linear program (MILP) that yields the minimal cost daily operation strategy for the fleet (i.e., route assignments and charging schedules using daily solar forecasts). We present numerical results from a real-world case study with Stanford University's Marguerite Shuttle (a large-scale electric bus fleet) to demonstrate the validity of our solution and highlight the significant cost savings compared to the status quo.