Abstract

In this work, a generalized mathematical formulation is proposed to model a generic public transport system, and a mixed-integer linear programming (MILP) optimization is used to determine the optimal design of the system in terms of charging infrastructure deployment (with on-route and off-route charging), battery sizing, and charging schedules for each route in the network. Three case studies are used to validate the proposed model while demonstrating its universal applicability. First, the design of three individual routes with different characteristics is demonstrated. Then, a large-scale generic transport system with 180 routes, consisting of urban and suburban routes with varying characteristics is considered and the optimal design is obtained. Afterwards, the use of the proposed model for a long-term transport system planning problem is demonstrated by adapting the system to a 2030 scenario based on forecasted technological advancements. The proposed formulation is shown to be highly versatile in modeling a wide variety of components in an electric bus (EB) transport system and in achieving an optimal design with minimal TOC.

Highlights

  • IntroductionWith the increasing popularity of electric vehicles (EVs) as a highly versatile distributed energy resource (DER), the transport sector becomes a strategic priority in VOLUME 8, 2020 energy systems research and development

  • Investment stability is mostly guaranteed in the public transportation sector, which facilitates the acquisition of new electric bus (EB) technologies [8]

  • Published works [29]–[32] have investigated the use of intelligent control algorithms to enhance the driving strategies, with the objective of decreasing losses due to frequent breaking in urban settings. The incorporation of such algorithms is recommended for incorporation in this model in future follow-up work, in order to analyze the cost-efficiency of acquiring these technologies on the design of the EB transport systems

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Summary

Introduction

With the increasing popularity of electric vehicles (EVs) as a highly versatile distributed energy resource (DER), the transport sector becomes a strategic priority in VOLUME 8, 2020 energy systems research and development. There have been numerous research studies aiming at harnessing the benefits of consumer-owned EVs for modern smart grids (SGs) through the use of modern control strategies [3]–[5]. Electric buses (EBs) seem to be less often investigated, which can be used to bring about techno-economic benefits in SG operation if optimized [6], [7]. In the context of public transport systems, the transition to a fully electric fleet is quite easy to carry out for three main reasons: First, due to heavy usage, public transport buses are frequently replaced and EBs can gradually replace conventional buses in the fleet without causing any interruption. In addition to the aforementioned facts, EB fleets have been shown to have a lower total ownership cost (TOC) compared to their conventional counterparts [9]

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