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Planning for electric vehicle needs by coupling charging profiles with urban mobility

Author

Listed:
  • Yanyan Xu

    (Massachusetts Institute of Technology)

  • Serdar Çolak

    (Massachusetts Institute of Technology
    Lawrence Berkeley National Laboratory)

  • Emre C. Kara

    (SLAC National Accelerator Laboratory)

  • Scott J. Moura

    (University of California)

  • Marta C. González

    (Massachusetts Institute of Technology
    Lawrence Berkeley National Laboratory
    University of California)

Abstract

The rising adoption of plug-in electric vehicles (PEVs) leads to the temporal alignment of their electricity and mobility demands. However, mobility demand has not yet been considered in electricity planning and management. Here, we present a method to estimate individual mobility of PEV drivers at fine temporal and spatial resolution, by integrating three unique datasets of mobile phone activity of 1.39 million Bay Area residents, census data and the PEV drivers survey data. Through coupling the uncovered patterns of PEV mobility with the charging activity of PEVs in 580,000 session profiles obtained in the same region, we recommend changes in PEV charging times of commuters at their work stations and shave the pronounced peak in power demand. Informed by the tariff of electricity, we calculate the monetary gains to incentivize the adoption of the recommendations. These results open avenues for planning for the future of coupled transportation and electricity needs using personalized data.

Suggested Citation

  • Yanyan Xu & Serdar Çolak & Emre C. Kara & Scott J. Moura & Marta C. González, 2018. "Planning for electric vehicle needs by coupling charging profiles with urban mobility," Nature Energy, Nature, vol. 3(6), pages 484-493, June.
    • Handle: RePEc:nat:natene:v:3:y:2018:i:6:d:10.1038_s41560-018-0136-x
    DOI: 10.1038/s41560-018-0136-x
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    Citations

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    Cited by:

    1. Manfren, Massimiliano & Nastasi, Benedetto & Groppi, Daniele & Astiaso Garcia, Davide, 2020. "Open data and energy analytics - An analysis of essential information for energy system planning, design and operation," Energy, Elsevier, vol. 213(C).
    2. Milan Straka & Rui Carvalho & Gijs van der Poel & v{L}ubov{s} Buzna, 2020. "Explaining the distribution of energy consumption at slow charging infrastructure for electric vehicles from socio-economic data," Papers 2006.01672, arXiv.org, revised Jun 2020.
    3. Shi, Shuyang & Wang, Lin & Wang, Xiaofan, 2022. "Uncovering the spatiotemporal motif patterns in urban mobility networks by non-negative tensor decomposition," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 606(C).
    4. Liu, Xiaochen & Fu, Zhi & Qiu, Siyuan & Zhang, Tao & Li, Shaojie & Yang, Zhi & Liu, Xiaohua & Jiang, Yi, 2023. "Charging private electric vehicles solely by photovoltaics: A battery-free direct-current microgrid with distributed charging strategy," Applied Energy, Elsevier, vol. 341(C).
    5. Tu, Wei & Santi, Paolo & Zhao, Tianhong & He, Xiaoyi & Li, Qingquan & Dong, Lei & Wallington, Timothy J. & Ratti, Carlo, 2019. "Acceptability, energy consumption, and costs of electric vehicle for ride-hailing drivers in Beijing," Applied Energy, Elsevier, vol. 250(C), pages 147-160.
    6. Yan, Jie & Zhang, Jing & Liu, Yongqian & Lv, Guoliang & Han, Shuang & Alfonzo, Ian Emmanuel Gonzalez, 2020. "EV charging load simulation and forecasting considering traffic jam and weather to support the integration of renewables and EVs," Renewable Energy, Elsevier, vol. 159(C), pages 623-641.
    7. Mowry, Andrew M. & Mallapragada, Dharik S., 2021. "Grid impacts of highway electric vehicle charging and role for mitigation via energy storage," Energy Policy, Elsevier, vol. 157(C).
    8. Adeline Gu'eret & Wolf-Peter Schill & Carlos Gaete-Morales, 2024. "Not flexible enough? Impacts of electric carsharing on a power sector with variable renewables," Papers 2402.19380, arXiv.org.
    9. Li, Xiaohui & Wang, Zhenpo & Zhang, Lei & Sun, Fengchun & Cui, Dingsong & Hecht, Christopher & Figgener, Jan & Sauer, Dirk Uwe, 2023. "Electric vehicle behavior modeling and applications in vehicle-grid integration: An overview," Energy, Elsevier, vol. 268(C).
    10. Alexandra von Meier & Elizabeth L. Ratnam & Kyle Brady & Keith Moffat & Jaimie Swartz, 2020. "Phasor-Based Control for Scalable Integration of Variable Energy Resources," Energies, MDPI, vol. 13(1), pages 1-14, January.
    11. Siobhan Powell & Gustavo Vianna Cezar & Liang Min & Inês M. L. Azevedo & Ram Rajagopal, 2022. "Charging infrastructure access and operation to reduce the grid impacts of deep electric vehicle adoption," Nature Energy, Nature, vol. 7(10), pages 932-945, October.
    12. Sheng, Yujie & Zeng, Hongtai & Guo, Qinglai & Yu, Yang & Li, Qiang, 2023. "Impact of customer portrait information superiority on competitive pricing of EV fast-charging stations," Applied Energy, Elsevier, vol. 348(C).
    13. Xuefang Li & Chenhui Liu & Jianmin Jia, 2019. "Ownership and Usage Analysis of Alternative Fuel Vehicles in the United States with the 2017 National Household Travel Survey Data," Sustainability, MDPI, vol. 11(8), pages 1-16, April.
    14. Lizana, Jesus & Friedrich, Daniel & Renaldi, Renaldi & Chacartegui, Ricardo, 2018. "Energy flexible building through smart demand-side management and latent heat storage," Applied Energy, Elsevier, vol. 230(C), pages 471-485.
    15. Maxwell Woody & Gregory A. Keoleian & Parth Vaishnav, 2023. "Decarbonization potential of electrifying 50% of U.S. light-duty vehicle sales by 2030," Nature Communications, Nature, vol. 14(1), pages 1-12, December.
    16. Pavić, Ivan & Pandžić, Hrvoje & Capuder, Tomislav, 2020. "Electric vehicle based smart e-mobility system – Definition and comparison to the existing concept," Applied Energy, Elsevier, vol. 272(C).
    17. Lukáš Dvořáček & Martin Horák & Michaela Valentová & Jaroslav Knápek, 2020. "Optimization of Electric Vehicle Charging Points Based on Efficient Use of Chargers and Providing Private Charging Spaces," Energies, MDPI, vol. 13(24), pages 1-28, December.
    18. Mingdong Sun & Chunfu Shao & Chengxiang Zhuge & Pinxi Wang & Xiong Yang & Shiqi Wang, 2022. "Uncovering travel and charging patterns of private electric vehicles with trajectory data: evidence and policy implications," Transportation, Springer, vol. 49(5), pages 1409-1439, October.
    19. Zhang, Jing & Yan, Jie & Liu, Yongqian & Zhang, Haoran & Lv, Guoliang, 2020. "Daily electric vehicle charging load profiles considering demographics of vehicle users," Applied Energy, Elsevier, vol. 274(C).
    20. Liu, Xiaochen & Fu, Zhi & Qiu, Siyuan & Li, Shaojie & Zhang, Tao & Liu, Xiaohua & Jiang, Yi, 2023. "Building-centric investigation into electric vehicle behavior: A survey-based simulation method for charging system design," Energy, Elsevier, vol. 271(C).
    21. Powell, Siobhan & Vianna Cezar, Gustavo & Apostolaki-Iosifidou, Elpiniki & Rajagopal, Ram, 2022. "Large-scale scenarios of electric vehicle charging with a data-driven model of control," Energy, Elsevier, vol. 248(C).
    22. Cui, Dingsong & Wang, Zhenpo & Liu, Peng & Wang, Shuo & Zhang, Zhaosheng & Dorrell, David G. & Li, Xiaohui, 2022. "Battery electric vehicle usage pattern analysis driven by massive real-world data," Energy, Elsevier, vol. 250(C).
    23. Ajit Kumar Mohanty & Perli Suresh Babu & Surender Reddy Salkuti, 2022. "Optimal Allocation of Fast Charging Station for Integrated Electric-Transportation System Using Multi-Objective Approach," Sustainability, MDPI, vol. 14(22), pages 1-22, November.
    24. Crozier, Constance & Morstyn, Thomas & McCulloch, Malcolm, 2020. "The opportunity for smart charging to mitigate the impact of electric vehicles on transmission and distribution systems," Applied Energy, Elsevier, vol. 268(C).
    25. Kang, Zixuan & Ye, Zhongnan & Lam, Chor-Man & Hsu, Shu-Chien, 2023. "Sustainable electric vehicle charging coordination: Balancing CO2 emission reduction and peak power demand shaving," Applied Energy, Elsevier, vol. 349(C).

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