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Electric bus coordinated charging strategy considering V2G and battery degradation

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

Abstract

The trend for the decarbonization of the transportation sector, contributing to climate change mitigation, has driven the accelerated deployment of electric buses in cities. However, higher upfront costs, charging infrastructure deployment and operational issues are the main obstacles to their massive adoption. This work develops an optimization model to deal with the charging schedule of a fleet of battery electric buses. This approach aims to minimize the charging costs of electric bus fleets also considering the ageing of the batteries and the participation in vehicle to grid schemes. We developed a case study using real-world data from a small electric bus fleet of eleven electric buses in a medium-size Portuguese city. Further, we performed a sensitivity analysis to assess the possibilities of energy trading with the grid. The results indicate that below a battery replacement cost threshold of 100 €/kWh, it may become economically attractive for public transportation operators to sell back energy to the grid for a given remuneration scheme. Considering battery degradation and energy selling, our study indicates that operation costs could be 38% lower in 2030. The approach presented in this article provides a tool that can be employed by public transportation operators to assist decision making in the electrification of bus systems.

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  • Manzolli, Jônatas Augusto & Trovão, João Pedro F. & Henggeler Antunes, Carlos, 2022. "Electric bus coordinated charging strategy considering V2G and battery degradation," Energy, Elsevier, vol. 254(PA).
    • Handle: RePEc:eee:energy:v:254:y:2022:i:pa:s0360544222011550
    DOI: 10.1016/j.energy.2022.124252
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    6. Wen, Shuang & Lin, Ni & Huang, Shengxu & Wang, Zhenpo & Zhang, Zhaosheng, 2023. "Lithium battery health state assessment based on vehicle-to-grid (V2G) real-world data and natural gradient boosting model," Energy, Elsevier, vol. 284(C).

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