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User behaviour and electric vehicle charging infrastructure: An agent-based model assessment

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  • Pagani, M.
  • Korosec, W.
  • Chokani, N.
  • Abhari, R.S.

Abstract

The transition to electric mobility is accelerating, and, thus it is increasingly important to be able to anticipate and adapt future development of the electric vehicle charging infrastructure. A novel agent-based simulation framework coupled with a detailed geo-referenced digital model of the built infrastructure is developed and applied. The charging behaviour of individual electric vehicle users as well as the spatial distributions of electric vehicles are accounted for in the simulation framework. More than 2500 scenarios of the transition to electric mobility in a mid-size city in Switzerland are assessed. The time to break-even of the electric vehicle charging infrastructure is up to 50% shorter when users are charged on the basis of parking fees rather than power sales. However, the revenues from parking fees are shown to be more sensitive to the behaviours and preferences of the users. At today’s low penetrations of electric vehicles, the profitability of the charging infrastructure is very uncertain, and thus entrants into the marketplace will have substantial financial exposure until the penetrations are of order 10%. Additionally, it is shown that, at specific transformers, public charging considerably increases grid loads by up to 78% during peak hours; these local increases, rather than the average city-wide increase in load, are the critical determinant of the required upgrades to the distribution grid. Overall, this novel simulation framework facilitates the planning of electric vehicle charging infrastructure that will support a successful transition to electric mobility.

Suggested Citation

  • Pagani, M. & Korosec, W. & Chokani, N. & Abhari, R.S., 2019. "User behaviour and electric vehicle charging infrastructure: An agent-based model assessment," Applied Energy, Elsevier, vol. 254(C).
  • Handle: RePEc:eee:appene:v:254:y:2019:i:c:s0306261919313674
    DOI: 10.1016/j.apenergy.2019.113680
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    1. Xiang, Yue & Liu, Junyong & Li, Ran & Li, Furong & Gu, Chenghong & Tang, Shuoya, 2016. "Economic planning of electric vehicle charging stations considering traffic constraints and load profile templates," Applied Energy, Elsevier, vol. 178(C), pages 647-659.
    2. Micari, Salvatore & Polimeni, Antonio & Napoli, Giuseppe & Andaloro, Laura & Antonucci, Vincenzo, 2017. "Electric vehicle charging infrastructure planning in a road network," Renewable and Sustainable Energy Reviews, Elsevier, vol. 80(C), pages 98-108.
    3. Kazemi, Mohammad Amin & Sedighizadeh, Mostafa & Mirzaei, Mohammad Javad & Homaee, Omid, 2016. "Optimal siting and sizing of distribution system operator owned EV parking lots," Applied Energy, Elsevier, vol. 179(C), pages 1176-1184.
    4. Sadeghi-Barzani, Payam & Rajabi-Ghahnavieh, Abbas & Kazemi-Karegar, Hosein, 2014. "Optimal fast charging station placing and sizing," Applied Energy, Elsevier, vol. 125(C), pages 289-299.
    5. Fischer, David & Harbrecht, Alexander & Surmann, Arne & McKenna, Russell, 2019. "Electric vehicles’ impacts on residential electric local profiles – A stochastic modelling approach considering socio-economic, behavioural and spatial factors," Applied Energy, Elsevier, vol. 233, pages 644-658.
    6. Eser, P. & Chokani, N. & Abhari, R., 2019. "Impact of Nord Stream 2 and LNG on gas trade and security of supply in the European gas network of 2030," Applied Energy, Elsevier, vol. 238(C), pages 816-830.
    7. Shepero, Mahmoud & Munkhammar, Joakim, 2018. "Spatial Markov chain model for electric vehicle charging in cities using geographical information system (GIS) data," Applied Energy, Elsevier, vol. 231(C), pages 1089-1099.
    8. Luo, Lizi & Gu, Wei & Zhou, Suyang & Huang, He & Gao, Song & Han, Jun & Wu, Zhi & Dou, Xiaobo, 2018. "Optimal planning of electric vehicle charging stations comprising multi-types of charging facilities," Applied Energy, Elsevier, vol. 226(C), pages 1087-1099.
    9. Eser, Patrick & Singh, Antriksh & Chokani, Ndaona & Abhari, Reza S., 2016. "Effect of increased renewables generation on operation of thermal power plants," Applied Energy, Elsevier, vol. 164(C), pages 723-732.
    10. Zhang, Li & Shaffer, Brendan & Brown, Tim & Scott Samuelsen, G., 2015. "The optimization of DC fast charging deployment in California," Applied Energy, Elsevier, vol. 157(C), pages 111-122.
    11. Schroeder, Andreas & Traber, Thure, 2012. "The economics of fast charging infrastructure for electric vehicles," Energy Policy, Elsevier, vol. 43(C), pages 136-144.
    12. Morrissey, Patrick & Weldon, Peter & O’Mahony, Margaret, 2016. "Future standard and fast charging infrastructure planning: An analysis of electric vehicle charging behaviour," Energy Policy, Elsevier, vol. 89(C), pages 257-270.
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    1. Huang, Xingjun & Lin, Yun & Lim, Ming K. & Zhou, Fuli & Liu, Feng, 2022. "Electric vehicle charging station diffusion: An agent-based evolutionary game model in complex networks," Energy, Elsevier, vol. 257(C).
    2. Fu, Zhengtang & Dong, Peiwu & Ju, Yanbing & Gan, Zhenkun & Zhu, Min, 2022. "An intelligent green vehicle management system for urban food reliably delivery:A case study of Shanghai, China," Energy, Elsevier, vol. 257(C).
    3. Mehdizadeh, Milad & Nordfjaern, Trond & Klöckner, Christian A., 2022. "A systematic review of the agent-based modelling/simulation paradigm in mobility transition," Technological Forecasting and Social Change, Elsevier, vol. 184(C).
    4. Yuan-Yuan Wang & Yuan-Ying Chi & Jin-Hua Xu & Jia-Lin Li, 2021. "Consumer Preferences for Electric Vehicle Charging Infrastructure Based on the Text Mining Method," Energies, MDPI, vol. 14(15), pages 1-20, July.
    5. Cláudia A. Soares Machado & Harmi Takiya & Charles Lincoln Kenji Yamamura & José Alberto Quintanilha & Fernando Tobal Berssaneti, 2020. "Placement of Infrastructure for Urban Electromobility: A Sustainable Approach," Sustainability, MDPI, vol. 12(16), pages 1-18, August.
    6. Mangipinto, Andrea & Lombardi, Francesco & Sanvito, Francesco Davide & Pavičević, Matija & Quoilin, Sylvain & Colombo, Emanuela, 2022. "Impact of mass-scale deployment of electric vehicles and benefits of smart charging across all European countries," Applied Energy, Elsevier, vol. 312(C).
    7. Nazari-Heris, Morteza & Loni, Abdolah & Asadi, Somayeh & Mohammadi-ivatloo, Behnam, 2022. "Toward social equity access and mobile charging stations for electric vehicles: A case study in Los Angeles," Applied Energy, Elsevier, vol. 311(C).
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    10. Graham Town & Seyedfoad Taghizadeh & Sara Deilami, 2022. "Review of Fast Charging for Electrified Transport: Demand, Technology, Systems, and Planning," Energies, MDPI, vol. 15(4), pages 1-30, February.
    11. Anselma, Pier Giuseppe, 2022. "Electrified powertrain sizing for vehicle fleets of car makers considering total ownership costs and CO2 emission legislation scenarios," Applied Energy, Elsevier, vol. 314(C).
    12. Singh, Kamini & Singh, Anoop, 2022. "Behavioural modelling for personal and societal benefits of V2G/V2H integration on EV adoption," Applied Energy, Elsevier, vol. 319(C).
    13. Mandev, Ahmet & Plötz, Patrick & Sprei, Frances & Tal, Gil, 2022. "Empirical charging behavior of plug-in hybrid electric vehicles," Applied Energy, Elsevier, vol. 321(C).
    14. Pagani, M. & Maire, P. & Korosec, W. & Chokani, N. & Abhari, R.S., 2020. "District heat network extension to decarbonise building stock: A bottom-up agent-based approach," Applied Energy, Elsevier, vol. 272(C).
    15. Chen, Jiahui & Wang, Fang & He, Xiaoyi & Liang, Xinyu & Huang, Junling & Zhang, Shaojun & Wu, Ye, 2022. "Emission mitigation potential from coordinated charging schemes for future private electric vehicles," Applied Energy, Elsevier, vol. 308(C).
    16. Chen, Yu & Lin, Boqiang, 2022. "Are consumers in China’s major cities happy with charging infrastructure for electric vehicles?," Applied Energy, Elsevier, vol. 327(C).
    17. Aleksandr Saprykin & Ndaona Chokani & Reza S. Abhari, 2021. "Uncertainties of Sub-Scaled Supply and Demand in Agent-Based Mobility Simulations with Queuing Traffic Model," Networks and Spatial Economics, Springer, vol. 21(2), pages 261-290, June.
    18. Song, Yanqiu & Shangguan, Lingzhi & Li, Guijun, 2021. "Simulation analysis of flexible concession period contracts in electric vehicle charging infrastructure public-private-partnership (EVCI-PPP) projects based on time-of-use (TOU) charging price strateg," Energy, Elsevier, vol. 228(C).
    19. Graber, Giuseppe & Calderaro, Vito & Mancarella, Pierluigi & Galdi, Vincenzo, 2020. "Two-stage stochastic sizing and packetized energy scheduling of BEV charging stations with quality of service constraints," Applied Energy, Elsevier, vol. 260(C).
    20. Christos Karolemeas & Stefanos Tsigdinos & Panagiotis G. Tzouras & Alexandros Nikitas & Efthimios Bakogiannis, 2021. "Determining Electric Vehicle Charging Station Location Suitability: A Qualitative Study of Greek Stakeholders Employing Thematic Analysis and Analytical Hierarchy Process," Sustainability, MDPI, vol. 13(4), pages 1-21, February.
    21. Helmus, Jurjen R. & Lees, Michael H. & van den Hoed, Robert, 2022. "A validated agent-based model for stress testing charging infrastructure utilization," Transportation Research Part A: Policy and Practice, Elsevier, vol. 159(C), pages 237-262.
    22. Florian Maurer & Christian Rieke & Ralf Schemm & Dominik Stollenwerk, 2023. "Analysis of an Urban Grid with High Photovoltaic and e-Mobility Penetration," Energies, MDPI, vol. 16(8), pages 1-18, April.
    23. Alexandra Märtz & Uwe Langenmayr & Sabrina Ried & Katrin Seddig & Patrick Jochem, 2022. "Charging Behavior of Electric Vehicles: Temporal Clustering Based on Real-World Data," Energies, MDPI, vol. 15(18), pages 1-26, September.
    24. Xin Wang & Jinfeng Wang & Chunqiu Xu & Ke Zhang & Guo Li, 2023. "Electric Vehicle Charging Infrastructure Policy Analysis in China: A Framework of Policy Instrumentation and Industrial Chain," Sustainability, MDPI, vol. 15(3), pages 1-16, February.

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