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On the Impact of Co-Optimizing Station Locations, Trip Assignment, and Charging Schedules for Electric Buses

Rito Brata Nath, Tarun Rambha, Maximilian Schiffer

Abstract

As many public transportation systems around the world transition to electric buses, the planning and operation of fleets can be improved via tailored decision-support tools. In this work, we study the impact of jointly locating charging facilities, assigning electric buses to trips, and determining when and where to charge the buses. We propose a mixed integer linear program that co-optimizes planning and operational decisions jointly and an iterated local search heuristic to solve large-scale instances. Herein, we use a concurrent scheduler algorithm to generate an initial feasible solution, which serves as a starting point for our iterated local search algorithm. In the sequential case, we first optimize trip assignments and charging locations. Charging schedules are then determined after fixing the optimal decisions from the first level. The joint model, on the other hand, integrates charge scheduling within the local search procedure. The solution quality of the joint and sequential iterated local search models are compared for multiple real-world bus transit networks. Our results demonstrate that joint models can help further improve operating costs by 14.1% and lower total costs by about 4.1% on average compared with sequential models. In addition, energy consumption costs and contracted power capacity costs have been reduced significantly due to our integrated planning approach.

On the Impact of Co-Optimizing Station Locations, Trip Assignment, and Charging Schedules for Electric Buses

Abstract

As many public transportation systems around the world transition to electric buses, the planning and operation of fleets can be improved via tailored decision-support tools. In this work, we study the impact of jointly locating charging facilities, assigning electric buses to trips, and determining when and where to charge the buses. We propose a mixed integer linear program that co-optimizes planning and operational decisions jointly and an iterated local search heuristic to solve large-scale instances. Herein, we use a concurrent scheduler algorithm to generate an initial feasible solution, which serves as a starting point for our iterated local search algorithm. In the sequential case, we first optimize trip assignments and charging locations. Charging schedules are then determined after fixing the optimal decisions from the first level. The joint model, on the other hand, integrates charge scheduling within the local search procedure. The solution quality of the joint and sequential iterated local search models are compared for multiple real-world bus transit networks. Our results demonstrate that joint models can help further improve operating costs by 14.1% and lower total costs by about 4.1% on average compared with sequential models. In addition, energy consumption costs and contracted power capacity costs have been reduced significantly due to our integrated planning approach.
Paper Structure (30 sections, 6 equations, 19 figures, 10 tables, 12 algorithms)

This paper contains 30 sections, 6 equations, 19 figures, 10 tables, 12 algorithms.

Table of Contents

  1. Introduction
  2. Literature Review
  3. Optimizing Charging Locations
  4. Electric Vehicle Scheduling Problem
  5. Charge Scheduling Problem
  6. Joint Models
  7. Problem Description
  8. Charge Scheduling and Joint Models
  9. CSP Model
  10. CLP-EVSP-CSP Model
  11. Surrogate CSPs
  12. Split Charging with Priority
  13. Uniform Charging with Priority
  14. Iterated Local Search
  15. Initial Solutions
  16. ...and 15 more sections

Figures (19)

  • Figure 1: Different tasks involved in strategic and operational planning of electric bus fleets
  • Figure 2: Bus stops and candidate charging locations in the Ann Arbor Area Transportation Authority network, US.
  • Figure 3: Network diagram for the EVSP
  • Figure 4: An illustration of the CEE charging strategy (The green dashed arrows indicate depot trips, black dotted arrows indicate service trips, and blue solid arrows indicate deadhead trips. Charging is allowed at the gray terminals.)
  • Figure 5: Decision variables at charging opportunities with stations at both trip ends
  • ...and 14 more figures