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A framework for evaluating the role of electric vehicles in transportation network infrastructure under travel demand variability

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  • Gardner, Lauren M.
  • Duell, Melissa
  • Waller, S. Travis

Abstract

The introduction of plug-in electric vehicles (PEVs) represents an unprecedented interaction between the road network and electricity grid. By replacing the traditional fuel source, petrol, with electricity, PEVs will increase the demand for electric power in a region and change emission profiles. Overall, the impacts depend on the eventual penetration of PEV ownership, but the true market share of PEVs in the future is highly unclear and radically different scenarios are possible. This added forecasting volatility makes long-term transport models that explicitly consider travel demand uncertainty even more critical. This work utilizes transport modeling tools in order to quantify the relationship between the travel patterns of PEV drivers and PEV energy consumption rates, as well as the corresponding environmental impact (measured by emissions savings relative to traditional internal combustion engine vehicles). Furthermore, this research explicitly addresses the relationship between long term travel demand uncertainty and system level energy consumption variability, an essential issue for regional energy providers and planners. Results and implications are discussed on both a small demonstration network and the Sioux Falls network.

Suggested Citation

  • Gardner, Lauren M. & Duell, Melissa & Waller, S. Travis, 2013. "A framework for evaluating the role of electric vehicles in transportation network infrastructure under travel demand variability," Transportation Research Part A: Policy and Practice, Elsevier, vol. 49(C), pages 76-90.
    • Handle: RePEc:eee:transa:v:49:y:2013:i:c:p:76-90
    DOI: 10.1016/j.tra.2013.01.031
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    References listed on IDEAS

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    1. Karplus, Valerie J. & Paltsev, Sergey & Reilly, John M., 2010. "Prospects for plug-in hybrid electric vehicles in the United States and Japan: A general equilibrium analysis," Transportation Research Part A: Policy and Practice, Elsevier, vol. 44(8), pages 620-641, October.
    2. Musti, Sashank & Kockelman, Kara M., 2011. "Evolution of the household vehicle fleet: Anticipating fleet composition, PHEV adoption and GHG emissions in Austin, Texas," Transportation Research Part A: Policy and Practice, Elsevier, vol. 45(8), pages 707-720, October.
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    Cited by:

    1. Arslan, Okan & Yıldız, Barış & Ekin Karaşan, Oya, 2014. "Impacts of battery characteristics, driver preferences and road network features on travel costs of a plug-in hybrid electric vehicle (PHEV) for long-distance trips," Energy Policy, Elsevier, vol. 74(C), pages 168-178.
    2. Wenwei Zhang & Hui Zhao, 2021. "Modal choice analysis for a linear monocentric city with battery electric vehicles and park-charge-ride services," Transportation, Springer, vol. 48(4), pages 1895-1929, August.
    3. Xiang Zhang & David Rey & S. Travis Waller & Nathan Chen, 2019. "Range-Constrained Traffic Assignment with Multi-Modal Recharge for Electric Vehicles," Networks and Spatial Economics, Springer, vol. 19(2), pages 633-668, June.
    4. Kai Liu & Sijia Luo & Jing Zhou, 2020. "En-Route Battery Management and a Mixed Network Equilibrium Problem Based on Electric Vehicle Drivers’ En-Route Recharging Behaviors," Energies, MDPI, vol. 13(16), pages 1-14, August.
    5. Heidrich, Oliver & Hill, Graeme A. & Neaimeh, Myriam & Huebner, Yvonne & Blythe, Philip T. & Dawson, Richard J., 2017. "How do cities support electric vehicles and what difference does it make?," Technological Forecasting and Social Change, Elsevier, vol. 123(C), pages 17-23.
    6. Wang, Hua & Zhao, De & Meng, Qiang & Ong, Ghim Ping & Lee, Der-Horng, 2020. "Network-level energy consumption estimation for electric vehicles considering vehicle and user heterogeneity," Transportation Research Part A: Policy and Practice, Elsevier, vol. 132(C), pages 30-46.
    7. Cui, Shaohua & Yao, Baozhen & Chen, Gang & Zhu, Chao & Yu, Bin, 2020. "The multi-mode mobile charging service based on electric vehicle spatiotemporal distribution," Energy, Elsevier, vol. 198(C).
    8. Sajjad Shafiei & Ziyuan Gu & Hanna Grzybowska & Chen Cai, 2023. "Impact of self-parking autonomous vehicles on urban traffic congestion," Transportation, Springer, vol. 50(1), pages 183-203, February.
    9. Anders F. Jensen & Thomas K. Rasmussen & Carlo G. Prato, 2020. "A Route Choice Model for Capturing Driver Preferences When Driving Electric and Conventional Vehicles," Sustainability, MDPI, vol. 12(3), pages 1-18, February.
    10. Inbal Haas & Shlomo Bekhor, 2017. "An Alternative Approach for Solving the Environmentally-Oriented Discrete Network Design Problem," Networks and Spatial Economics, Springer, vol. 17(3), pages 963-988, September.
    11. He, Fang & Yin, Yafeng & Lawphongpanich, Siriphong, 2014. "Network equilibrium models with battery electric vehicles," Transportation Research Part B: Methodological, Elsevier, vol. 67(C), pages 306-319.
    12. H. M. Abdul Aziz & Satish V. Ukkusuri & Xianyuan Zhan, 2017. "Determining the Impact of Personal Mobility Carbon Allowance Schemes in Transportation Networks," Networks and Spatial Economics, Springer, vol. 17(2), pages 505-545, June.

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