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Title: Robust planning of dynamic wireless charging infrastructure for battery electric buses

Battery electric buses with zero tailpipe emissions have great potential in improving environmental sustainability and livability of urban areas. However, the problems of high cost and limited range associated with on-board batteries have substantially limited the popularity of battery electric buses. The technology of dynamic wireless power transfer (DWPT), which provides bus operators with the ability to charge buses while in motion, may be able to effectively alleviate the drawbacks of electric buses. In this paper, we address the problem of simultaneously selecting the optimal location of the DWPT facilities and designing the optimal battery sizes of electric buses for a DWPT electric bus system. The problem is first constructed as a deterministic model in which the uncertainty of energy consumption and travel time of electric buses is neglected. The methodology of robust optimization (RO) is then adopted to address the uncertainty of energy consumption and travel time. The affinely adjustable robust counterpart (AARC) of the deterministic model is developed, and its equivalent tractable mathematical programming is derived. Both the deterministic model and the robust model are demonstrated with a real-world bus system. The results of our study demonstrate that the proposed deterministic model can effectively determine the allocation ofmore » DWPT facilities and the battery sizes of electric buses for a DWPT electric bus system; and the robust model can further provide optimal designs that are robust against the uncertainty of energy consumption and travel time for electric buses.« less
Authors:
ORCiD logo [1] ;  [1]
  1. Utah State Univ., Logan, UT (United States). Dept. of Civil and Environmental Engineering
Publication Date:
Grant/Contract Number:
EE0007997
Type:
Accepted Manuscript
Journal Name:
Transportation Research Part C: Emerging Technologies
Additional Journal Information:
Journal Volume: 83; Journal Issue: C; Journal ID: ISSN 0968-090X
Publisher:
Elsevier
Research Org:
Pacificorp, Portland, OR (United States)
Sponsoring Org:
USDOE Office of Energy Efficiency and Renewable Energy (EERE); USDOT; Mountain-Plains Consortium (MPC)
Country of Publication:
United States
Language:
English
Subject:
25 ENERGY STORAGE; 29 ENERGY PLANNING, POLICY, AND ECONOMY; 32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION; 33 ADVANCED PROPULSION SYSTEMS; Battery electric bus; Dynamic wireless power transfer; Wireless charging; System optimization; Robust optimization; Affinely adjustable robust counterpart
OSTI Identifier:
1429115

Liu, Zhaocai, and Song, Ziqi. Robust planning of dynamic wireless charging infrastructure for battery electric buses. United States: N. p., Web. doi:10.1016/j.trc.2017.07.013.
Liu, Zhaocai, & Song, Ziqi. Robust planning of dynamic wireless charging infrastructure for battery electric buses. United States. doi:10.1016/j.trc.2017.07.013.
Liu, Zhaocai, and Song, Ziqi. 2017. "Robust planning of dynamic wireless charging infrastructure for battery electric buses". United States. doi:10.1016/j.trc.2017.07.013. https://www.osti.gov/servlets/purl/1429115.
@article{osti_1429115,
title = {Robust planning of dynamic wireless charging infrastructure for battery electric buses},
author = {Liu, Zhaocai and Song, Ziqi},
abstractNote = {Battery electric buses with zero tailpipe emissions have great potential in improving environmental sustainability and livability of urban areas. However, the problems of high cost and limited range associated with on-board batteries have substantially limited the popularity of battery electric buses. The technology of dynamic wireless power transfer (DWPT), which provides bus operators with the ability to charge buses while in motion, may be able to effectively alleviate the drawbacks of electric buses. In this paper, we address the problem of simultaneously selecting the optimal location of the DWPT facilities and designing the optimal battery sizes of electric buses for a DWPT electric bus system. The problem is first constructed as a deterministic model in which the uncertainty of energy consumption and travel time of electric buses is neglected. The methodology of robust optimization (RO) is then adopted to address the uncertainty of energy consumption and travel time. The affinely adjustable robust counterpart (AARC) of the deterministic model is developed, and its equivalent tractable mathematical programming is derived. Both the deterministic model and the robust model are demonstrated with a real-world bus system. The results of our study demonstrate that the proposed deterministic model can effectively determine the allocation of DWPT facilities and the battery sizes of electric buses for a DWPT electric bus system; and the robust model can further provide optimal designs that are robust against the uncertainty of energy consumption and travel time for electric buses.},
doi = {10.1016/j.trc.2017.07.013},
journal = {Transportation Research Part C: Emerging Technologies},
number = C,
volume = 83,
place = {United States},
year = {2017},
month = {10}
}