Grid-Aware Charging and Operational Optimization for Mixed-Fleet Public Transit

Rishav Sen, Amutheezan Sivagnanam, Aron Laszka, Ayan Mukhopadhyay, Abhishek Dubey

2024 IEEE 27th International Conference on Intelligent Transportation Systems (ITSC) 2024

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Why This Matters

Transit agencies are rapidly transitioning to electric fleets but lack integrated optimization approaches that handle both the operational complexity and the new economic reality of time-of-use electricity pricing. This work is important because it explicitly models the interplay between scheduling decisions, vehicle assignment, charging logistics, and dynamic pricing—factors often overlooked in traditional transit optimization. The hierarchical approach makes the problem tractable while capturing the essential trade-offs between vehicle efficiency, charging logistics, and electricity costs.

What We Did

This paper presents a comprehensive approach to optimize mixed-fleet public transit systems with both electric and diesel buses under dynamic electricity pricing and charging constraints. The work formulates a hierarchical mixed-integer linear programming model that explicitly addresses the unique challenges of mixed-fleet management including variable charging times, electricity pricing that changes throughout the day, and operational constraints around vehicle range and charging station access. The solution approach decomposes the problem into manageable sub-problems by first assigning blocks to higher-efficiency buses and then optimizing energy consumption for remaining vehicles.

Key Results

The optimization approach demonstrates significant cost savings compared to traditional methods that ignore dynamic pricing effects. Testing on realistic instances shows average improvements of 2.58% in operational cost through hierarchical optimization, with additional 6.25% improvements from considering time-of-use electricity pricing. The results show that properly accounting for electricity pricing structures and mixed-fleet constraints can substantially reduce transit operating costs while managing the complexity of modern fleets.

Full Abstract

Cite This Paper

@inproceedings{rishavITSC2024,
  author = {Sen, Rishav and Sivagnanam, Amutheezan and Laszka, Aron and Mukhopadhyay, Ayan and Dubey, Abhishek},
  booktitle = {2024 IEEE 27th International Conference on Intelligent Transportation Systems (ITSC)},
  title = {Grid-Aware Charging and Operational Optimization for Mixed-Fleet Public Transit},
  year = {2024},
  abstract = {The rapid growth of urban populations and the increasing need for sustainable transportation solutions have prompted a shift towards electric buses in public transit systems. However, the effective management of mixed fleets consisting of both electric and diesel buses poses significant operational chal- lenges. One major challenge is coping with dynamic electricity pricing, where charging costs vary throughout the day. Transit agencies must optimize charging assignments in response to such dynamism while accounting for secondary considerations such as seating constraints. This paper presents a comprehensive mixed-integer linear programming (MILP) model to address these challenges by jointly optimizing charging schedules and trip assignments for mixed (electric and diesel bus) fleets while considering factors such as dynamic electricity pricing, vehicle capacity, and route constraints. We address the potential computational intractability of the MILP formulation, which can arise even with relatively small fleets, by employing a hierarchical approach tailored to the fleet composition. By using real-world data from the city of Chattanooga, Tennessee, USA, we show that our approach can result in significant savings in the operating costs of the mixed transit fleets.},
  contribution = {lead},
  keywords = {transit optimization, mixed-fleet operations, electric vehicles, dynamic pricing, energy consumption, vehicle scheduling, hierarchical optimization, transportation planning}
}
Quick Info
Year 2024
Keywords
transit optimization mixed-fleet operations electric vehicles dynamic pricing energy consumption vehicle scheduling hierarchical optimization transportation planning
Research Areas
transit energy planning scalable AI
Search Tags

Grid, Aware, Charging, Operational, Optimization, Mixed, Fleet, Public, Transit, transit optimization, mixed-fleet operations, electric vehicles, dynamic pricing, energy consumption, vehicle scheduling, hierarchical optimization, transportation planning, transit, energy, planning, scalable AI, 2024, Sen, Sivagnanam, Laszka, Mukhopadhyay, Dubey