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Electric bus fleet charging management: A robust optimisation framework addressing battery ageing, time-of-use tariffs, and energy consumption uncertainty

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  • Manzolli, Jônatas Augusto
  • Trovão, João Pedro F.
  • Henggeler Antunes, Carlos

Abstract

The large-scale adoption of electric buses offers sustainable and reliable transportation, but it poses challenges in designing appropriate charging strategies to accommodate the operation requirements of the fleets. The optimisation of those strategies is crucial to avoid disrupting daily operations due to insufficient energy for trips, aiming to minimise operational costs and grid overload because of coincident peak demand. This work introduces a robust optimisation model to provide solutions accounting for uncertainties in energy consumption, enabling operators to establish cost-effective and resilient charging plans. The model includes features such as battery ageing, time-of-use tariffs, vehicle-to-grid (V2G), and operational constraints. We propose a reformulation approach to solve the model and deal with its computational complexity. An illustrative case study is conducted using real-world data from a mid-sized city in Portugal. The findings indicate significant cost reductions through coordinated charging, with deterministic and robust models achieving 37 % and 12 % reductions, respectively, compared to a business-as-usual charging scenario. Further, V2G activities generate additional revenue, also emphasizing the importance of considering degradation costs to reduce battery capacity fade. Additionally, the effectiveness of the robust approach in addressing energy consumption uncertainty is demonstrated, offering operators a flexible method to adapt to various operational contexts and improve bus transportation service reliability.

Suggested Citation

  • Manzolli, Jônatas Augusto & Trovão, João Pedro F. & Henggeler Antunes, Carlos, 2025. "Electric bus fleet charging management: A robust optimisation framework addressing battery ageing, time-of-use tariffs, and energy consumption uncertainty," Applied Energy, Elsevier, vol. 381(C).
  • Handle: RePEc:eee:appene:v:381:y:2025:i:c:s0306261924025212
    DOI: 10.1016/j.apenergy.2024.125137
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    References listed on IDEAS

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