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The diffusion of electric vehicles: An agent-based microsimulation

Author

Listed:
  • McCoy, Daire
  • Lyons, Sean

Abstract

We implement an agent-based, threshold model of innovation diffusion to simulate the adoption of electric vehicles among Irish households. We use detailed survey microdata to develop a nationally representative, heterogeneous agent population. We then calibrate our agent population to reflect the aggregate socioeconomic characteristics of a number of geographic areas of interest. Our data allow us to create agents with socioeconomic characteristics and environmental preferences. Agents are placed within social networks through which the diffusion process propagates. We find that even if overall adoption is relatively low, mild peer effects could result in large clusters of adopters forming in certain areas. This may put pressure on electricity distribution networks in these areas.

Suggested Citation

  • McCoy, Daire & Lyons, Sean, 2014. "The diffusion of electric vehicles: An agent-based microsimulation," MPRA Paper 54560, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:54560
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    File URL: https://mpra.ub.uni-muenchen.de/54633/1/MPRA_paper_54633.pdf
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    References listed on IDEAS

    as
    1. Tran, Martino, 2012. "Technology-behavioural modelling of energy innovation diffusion in the UK," Applied Energy, Elsevier, vol. 95(C), pages 1-11.
    2. Palmer, J. & Sorda, G. & Madlener, R., 2015. "Modeling the diffusion of residential photovoltaic systems in Italy: An agent-based simulation," Technological Forecasting and Social Change, Elsevier, vol. 99(C), pages 106-131.
    3. Anna Kowalska-Pyzalska & Katarzyna Maciejowska & Katarzyna Sznajd-Weron & Rafal Weron, 2013. "Going green: Agent-based modeling of the diffusion of dynamic electricity tariffs," HSC Research Reports HSC/13/05, Hugo Steinhaus Center, Wroclaw University of Technology.
    4. Axsen, Jonn & Mountain, Dean C. & Jaccard, Mark, 2009. "Combining stated and revealed choice research to simulate the neighbor effect: The case of hybrid-electric vehicles," Institute of Transportation Studies, Working Paper Series qt02n9j6cv, Institute of Transportation Studies, UC Davis.
    5. Tao Zhang & William J. Nuttall, 2012. "An Agent-Based Simulation of Smart Metering Technology Adoption," International Journal of Agent Technologies and Systems (IJATS), IGI Global, vol. 4(1), pages 17-38, January.
    6. Axsen, Jonn & Mountain, Dean C. & Jaccard, Mark, 2009. "Combining stated and revealed choice research to simulate the neighbor effect: The case of hybrid-electric vehicles," Resource and Energy Economics, Elsevier, vol. 31(3), pages 221-238, August.
    7. Foley, Aoife & Tyther, Barry & Calnan, Patrick & Ó Gallachóir, Brian, 2013. "Impacts of Electric Vehicle charging under electricity market operations," Applied Energy, Elsevier, vol. 101(C), pages 93-102.
    8. Jonn Axsen & Kenneth S Kurani, 2012. "Interpersonal influence within car buyers' social networks: applying five perspectives to plug-in hybrid vehicle drivers," Environment and Planning A, Pion Ltd, London, vol. 44(5), pages 1047-1065, May.
    9. Bryan Bollinger & Kenneth Gillingham, 2012. "Peer Effects in the Diffusion of Solar Photovoltaic Panels," Marketing Science, INFORMS, vol. 31(6), pages 900-912, November.
    10. Campbell, Amy R. & Ryley, Tim & Thring, Rob, 2012. "Identifying the early adopters of alternative fuel vehicles: A case study of Birmingham, United Kingdom," Transportation Research Part A: Policy and Practice, Elsevier, vol. 46(8), pages 1318-1327.
    11. Saarenpää, Jukka & Kolehmainen, Mikko & Niska, Harri, 2013. "Geodemographic analysis and estimation of early plug-in hybrid electric vehicle adoption," Applied Energy, Elsevier, vol. 107(C), pages 456-464.
    12. Eppstein, Margaret J. & Grover, David K. & Marshall, Jeffrey S. & Rizzo, Donna M., 2011. "An agent-based model to study market penetration of plug-in hybrid electric vehicles," Energy Policy, Elsevier, vol. 39(6), pages 3789-3802, June.
    13. Ozaki, Ritsuko & Sevastyanova, Katerina, 2011. "Going hybrid: An analysis of consumer purchase motivations," Energy Policy, Elsevier, vol. 39(5), pages 2217-2227, May.
    Full references (including those not matched with items on IDEAS)

    More about this item

    Keywords

    Electric vehicles; Agent-based modelling; Spatial microsimulation;

    JEL classification:

    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • D1 - Microeconomics - - Household Behavior
    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes
    • R41 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics - - - Transportation: Demand, Supply, and Congestion; Travel Time; Safety and Accidents; Transportation Noise

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