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Author:

Li, W. (Li, W..) | He, Y. (He, Y..) | Hu, S. (Hu, S..) | He, Z. (He, Z..) | Ratti, C. (Ratti, C..)

Indexed by:

EI Scopus SCIE

Abstract:

To address the battery-related shortcomings of battery electric buses (BEBs), dynamic wireless charging (DWC) technology that allows BEBs to charge while in motion has emerged, thereby extending the driving range and reducing the size of onboard batteries. The introduction of DWC technology raises a critical problem, namely, the deployment of DWC facilities. To resolve the infrastructure planning problem, this study first proposes a (higher-level) strategic planning model that optimizes the deployment of DWC facilities and battery capacity of BEBs, and then establishes a (lower-level) tactical planning model of optimal charging scheduling under the time-of-use (TOU) tariff mechanism considering the interdependence between infrastructure design and charging activities of BEBs. Mixed-integer nonlinear programming (MINLP) is proposed to optimize the model, aiming to minimize the overall cost associated with charging facilities, batteries, and charging. The proposed optimization model is tested and evaluated using a real-world bus system network, and the results demonstrate that the model effectively determines the DWC facility locations and battery sizes and optimizes the charging scheduling considering the TOU tariff for BEBs. The proposed model in this study provides a comprehensive guideline for relevant practitioners and further promotes the application of DWC technology in BEBs. © 2023 Elsevier Ltd

Keyword:

Dynamic wireless charging Integrated optimization Battery electric bus Charging scheduling Infrastructure planning

Author Community:

  • [ 1 ] [Li W.]Beijing Key Laboratory of Traffic Engineering, Beijing University of Technology, China
  • [ 2 ] [He Y.]National Renewable Energy Laboratory, United States
  • [ 3 ] [Hu S.]Senseable City Lab, Massachusetts Institute of Technology, United States
  • [ 4 ] [He Z.]Senseable City Lab, Massachusetts Institute of Technology, United States
  • [ 5 ] [Ratti C.]Senseable City Lab, Massachusetts Institute of Technology, United States

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Source :

Transportation Research Part C: Emerging Technologies

ISSN: 0968-090X

Year: 2024

Volume: 159

8 . 3 0 0

JCR@2022

Cited Count:

WoS CC Cited Count: 0

SCOPUS Cited Count: 9

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 8

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