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A generic cost-utility-emission optimization for electric bus transit infrastructure planning and charging scheduling

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  • Foda, Ahmed
  • Abdelaty, Hatem
  • Mohamed, Moataz
  • El-Saadany, Ehab

Abstract

Implementing battery electric buses (BEB) in transit operation is a promising avenue for reducing greenhouse gas (GHG) emissions. However, challenges are associated with the interdependency of several BEB system parameters during system planning and operation. This study develops a generic optimization model for BEB cost, utility impact, and GHG emissions. The model optimizes the sizing/location of the charging infrastructure, onboard battery capacity, and charging schedule. Furthermore, a trip-level energy consumption model is embedded in the optimization process to accommodate the varying energy consumption rates at the trip level. The optimization model is applied to a mid-size multi-hubs transit network. The results indicate that both en-route and depot charging approaches are required, with varying power capacities (heterogeneous infrastructure) and the number of chargers (poles). Furthermore, the temporal variation of the electricity time-of-use and GHG emissions intensity play significant roles in the resultant charging strategy and, thus, the system cost. Overall, the results indicate that the inclusion of all design parameters as decision variables in the model, as proposed in this study, is essential to account for the intertwined synergy of the BEB system's components.

Suggested Citation

  • Foda, Ahmed & Abdelaty, Hatem & Mohamed, Moataz & El-Saadany, Ehab, 2023. "A generic cost-utility-emission optimization for electric bus transit infrastructure planning and charging scheduling," Energy, Elsevier, vol. 277(C).
    • Handle: RePEc:eee:energy:v:277:y:2023:i:c:s0360544223009866
    DOI: 10.1016/j.energy.2023.127592
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    Cited by:

    1. Ahmed Foda & Moataz Mohamed & Hany Farag & Ehab El-Saadany, 2023. "A resilient battery electric bus transit system configuration," Nature Communications, Nature, vol. 14(1), pages 1-15, December.
    2. Harasis, Salman & Khan, Irfan & Massoud, Ahmed, 2024. "Enabling large-scale integration of electric bus fleets in harsh environments: Possibilities, potentials, and challenges," Energy, Elsevier, vol. 300(C).
    3. Wang, Hongfei & Guan, Hongzhi & Qin, Huanmei & Zhao, Pengfei, 2024. "Assessing the sustainability of time-dependent electric demand responsive transit service through deep reinforcement learning," Energy, Elsevier, vol. 296(C).
    4. Zhou, Yu & Wang, Hua & Wang, Yun & Yu, Bin & Tang, Tianpei, 2024. "Charging facility planning and scheduling problems for battery electric bus systems: A comprehensive review," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 183(C).
    5. Foda, Ahmed & Mohamed, Moataz, 2024. "The impacts of optimization approaches on BEB system configuration in transit," Transport Policy, Elsevier, vol. 151(C), pages 12-23.
    6. Wang, Yiran & Chen, Jingxu & Tang, Tianli & Liu, Zhiyuan, 2024. "A holistic approach to multi-depot electric bus scheduling for energy saving considering limitations in charging facilities," Energy, Elsevier, vol. 303(C).
    7. Shehabeldeen, Ali & Foda, Ahmed & Mohamed, Moataz, 2024. "A multi-stage optimization of battery electric bus transit with battery degradation," Energy, Elsevier, vol. 299(C).
    8. Zoutendijk, M. & Mitici, M., 2024. "Fleet scheduling for electric towing of aircraft under limited airport energy capacity," Energy, Elsevier, vol. 294(C).

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