The promotion of electric mobility is a key objective of energy transition, and it is aimed at significantly reducing greenhouse gas emissions, with road transport being understood as a major contributor. Despite its potential, the adoption of electric vehicles (EVs) in logistics faces critical challenges, including limited battery range, charging time, and the availability of charging infrastructure. Moreover, deploying charging stations must be carefully coordinated with the public grid to ensure seamless integration. This paper proposes a novel methodology for the optimal design and management of EV fleets in logistics. Our approach introduces innovations such as leveraging self-produced electricity and incorporating time-varying energy prices that can be tailored to individual nodes. This marks an important step toward a comprehensive interdisciplinary framework that integrates technical solutions with public policy considerations. Through case studies, we explore how various parameters and resource distributions influence optimal decisions. The findings demonstrate significant potential for cost reduction and enhanced efficiency when applying this methodology to EV-based logistics, thereby offering actionable insights for advancing sustainable transportation.
Optimal Management of Commercial Electric Vehicle Fleets with Recharging Stations and Time-Varying Electricity Prices
Coppo, Massimiliano
;Agostini, Marco;De Matteis, Giulia;Bertolini, Marina
2025
Abstract
The promotion of electric mobility is a key objective of energy transition, and it is aimed at significantly reducing greenhouse gas emissions, with road transport being understood as a major contributor. Despite its potential, the adoption of electric vehicles (EVs) in logistics faces critical challenges, including limited battery range, charging time, and the availability of charging infrastructure. Moreover, deploying charging stations must be carefully coordinated with the public grid to ensure seamless integration. This paper proposes a novel methodology for the optimal design and management of EV fleets in logistics. Our approach introduces innovations such as leveraging self-produced electricity and incorporating time-varying energy prices that can be tailored to individual nodes. This marks an important step toward a comprehensive interdisciplinary framework that integrates technical solutions with public policy considerations. Through case studies, we explore how various parameters and resource distributions influence optimal decisions. The findings demonstrate significant potential for cost reduction and enhanced efficiency when applying this methodology to EV-based logistics, thereby offering actionable insights for advancing sustainable transportation.File | Dimensione | Formato | |
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Descrizione: Optimal Management of Commercial Electric Vehicle Fleets with Recharging Stations and Time-Varying Electricity Prices
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