Extending electric bus charging infrastructure considering charging scheduling and energy pricing
Document Type
Journal Article
Publication Date
2025
Subject Area
place - asia, place - north america, place - urban, mode - bus, technology - alternative fuels, infrastructure - fleet management, planning - methods, planning - environmental impact, planning - integration
Keywords
Electric buses, Energy grid, Charging scheduling, Charging station location selection, Mixed-integer programming
Abstract
The transition to fully electrified public transport is a pivotal step towards sustainable urban mobility. However, the efficient deployment of charging infrastructure poses significant challenges, particularly in optimizing charger placement to meet operational and economic constraints. This article introduces a novel strategic planning model designed to calculate the optimal locations for extending an existing charging station network that supports the daily operations of an electric bus fleet. The planning model is a bi-objective mixed integer-linear program that considers both the operational needs of the fleet operator and the energy pricing schema as imposed by energy management authorities. By accounting for parameters such as charging station installation costs, Time-of-Use tariffs and peak demand charges, the model addresses an integrated planning problem with two objectives: the minimization of the monetary cost required for the operation of the bus fleet and the buses’ deadhead times. An implementation in a network using data from Manhattan, New York and a case study in Limassol, Cyprus, demonstrate the model’s efficacy in providing actionable insights for urban planners and transport authorities, ensuring cost-effectiveness and reduced environmental impact.
Rights
Permission to publish the abstract has been given by Elsevier, copyright remains with them.
Recommended Citation
Rizopoulos, D., & Gkiotsalitis, K. (2025). Extending electric bus charging infrastructure considering charging scheduling and energy pricing. Transportation Research Part C: Emerging Technologies, 176, 105141.

Comments
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