Iterated Local Search for the eBuses Charging Location Problem

Quintana, César Loaiza; Climent, Laura; Arbeláez, Alejandro

doi:10.1007/978-3-031-14721-0_24

Cited by 3 publications

References 13 publications

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Smart and Sustainable Scheduling of Charging Events for Electric Buses

Jarvis

Climent

Arbeláez

2022

Springer Proceedings in Political Science and International Relations

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The Irish transportation sector currently accounts for more than 30% of the energy related CO2 emissions of the country. Therefore, in order to reach the sustainable goals, the Irish government is working on multiple incentives to promote Electric Vehicles (EV) and infrastructure to decarbonize the sector, e.g., free domestic charging points, tool reductions, and the implementation of electric Buses (eBuses) in the medium to long term. In particular, eBuses operate with rechargeable batteries with a capacity to store approximately 300 kWh (and up to 600 kWh), equivalent to around 29.9 L of diesel, while reaching approx. 200 km. In order to ensure a proper transition from regular diesel buses to eBuses, charging times must be coordinated to ensure each bus has adequate energy to complete their operational route. In this work, we present a framework for an efficient management of renewable energies to charge a fleet of eBuses without perturbing the quality of service. Our framework starts by building a deep learning model for wind power forecasting to predict clean energy time windows, i.e., periods of time when the production of clean energy exceeds the demand of the country. Then, the optimization phase schedules charging events to reduce the use of non-clean energy to recharge eBuses while passengers are embarking or disembarking. The proposed framework is capable of overcoming the unstable and chaotic nature of wind power generation to operate the fleet without perturbing the quality of service. As expected, the size of the batteries does have a positive impact on the percentage of clean energy required to operate large fleets of eBuses. Methods developed in this paper help to mitigate potentially inaccuracies derived the prediction models. Our extensive empirical validation with real instances from Ireland suggests that our solutions can significantly reduce non-clean energy consumed on large datasets.

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Smart and Sustainable Scheduling of Charging Events for Electric Buses

Jarvis

Climent

Arbeláez

2022

Springer Proceedings in Political Science and International Relations

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A brief review of the techniques used to locate electric bus charging stations

Yánez,

Cindy,

Yánez

et al. 2024

2024 IEEE Eighth Ecuador Technical Chapters Meeting (ETCM)

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Robust eBuses Charging Location Problem

Quintana

Arbeláez²,

Climent³

2022

IEEE Open J. Intell. Transp. Syst.

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The implementation of a sustainable and efficient electric bus (eBus) transportation network requires addressing multiple concerns, such as limited driving range and battery charging/discharging time. Currently, eBuses can travel between 200 to 300 km on a single charge, and fast charging stations can fully recharge a battery in a matter of minutes. However, a failure in a charging station might negatively impact the operation of the system with unnecessary delays for the users. Taking this into account, we propose and implement a model for the Robust eBuses Charging Location problem that takes into account potential vulnerabilities of the transportation system. Our model incorporates a protection mechanism that allows eBuses to reach a backup charging station in case the regular one is down. We propose a MIP model to tackle this problem with minimal disruptions in the regular operation of the eBuses. Furthermore, we also present a Large Neighbourhood Search framework to efficiently tackle the problem. Our empirical evaluation suggests that our framework can operate a robust service with a small number of charging stations for three Irish cities and our Large Neighbourhood Search approach largely outperforms a popular commercial MIP solver.

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Iterated Local Search for the eBuses Charging Location Problem

Cited by 3 publications

References 13 publications

Smart and Sustainable Scheduling of Charging Events for Electric Buses

Smart and Sustainable Scheduling of Charging Events for Electric Buses

A brief review of the techniques used to locate electric bus charging stations

Robust eBuses Charging Location Problem

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