The diffusion of electric vehicles: An agent-based microsimulation

McCoy, Daire and Lyons, Sean (2014): The diffusion of electric vehicles: An agent-based microsimulation.

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.

• Item Type: MPRA Paper
• Language: English
• Keywords: Electric vehicles; Agent-based modelling; Spatial microsimulation
• Subjects: C - Mathematical and Quantitative Methods > C6 - Mathematical Methods ; Programming Models ; Mathematical and Simulation Modeling > C63 - Computational Techniques ; Simulation Modeling; D - Microeconomics > D1 - Household Behavior and Family Economics; O - Economic Development, Innovation, Technological Change, and Growth > O3 - Innovation ; Research and Development ; Technological Change ; Intellectual Property Rights > O33 - Technological Change: Choices and Consequences ; Diffusion Processes; R - Urban, Rural, Regional, Real Estate, and Transportation Economics > R4 - Transportation Economics > R41 - Transportation: Demand, Supply, and Congestion ; Travel Time ; Safety and Accidents ; Transportation Noise

References

[1] A. Foley, B. Tyther, P. Calnan, B. Gallachir, Impacts of electric vehicle charging under electricity market operations, Applied Energy 101 (2013) 93{102. doi:10.1016/j.apenergy.2012.06.052. URL http://dx.doi.org/10.1016/j.apenergy.2012.06.052

[2] K. Schneider, C. Gerkensmeyer, M. Kintner-Meyer, R. Fletcher, Impact assessment of plug-in hybrid vehicles on pacific northwest distribution systems, Institute of Electrical and Electronics Engineers, 2008, pp. 1{6. doi:10.1109/PES.2008.4596392. URL http://dx.doi.org/10.1109/PES.2008.4596392

[3] S. Shao, M. Pipattanasomporn, S. Rahman, Challenges of PHEV penetration to the residential distribution network, Institute of Electrical and Electronics Engineers, 2009, pp. 1-8.doi:10.1109/PES.2009.5275806. URL http://dx.doi.org/10.1109/PES.2009.5275806

[4] P. Richardson, D. Flynn, A. Keane, Impact assessment of varying penetrations of electric vehicles on low voltage distribution systems, Institute of Electrical and Electronics Engineers, 2010, pp. 1{6. doi:10.1109/PES.2010.5589940. URL http://dx.doi.org/10.1109/PES.2010.5589940

[5] K. Parks, P. Denholm, A. J. Markel, Costs and emissions associated with plug-in hybrid electric vehicle charging in the xcel energy colorado service territory, Tech. Rep. NREL/TP-640-41410, National Renewable Energy Laboratory (May 2007).

[6] B. Bollinger, K. Gillingham, Peer effects in the diffusion of solar photovoltaic panels, Marketing Science 31 (6) (2012) 900{912. 25

[7] D. S. Noonan, L.-H. C. Hsieh, D. Matiso, Spatial effects in energy-efficient residential HVAC technology adoption, Environment and Behavior 45 (4) (2013) 476{503doi:10.1177/0013916511421664. URL http://dx.doi.org/10.1177/0013916511421664

[8] J. Axsen, D. C. Mountain, M. Jaccard, Combining stated and revealed choice research to simulate the neighbor effect: The case of hybrid-electric vehicles, Resource and Energy Economics 31 (3) (2009) 221{238. doi:10.1016/j.reseneeco.2009.02.001. URL http://dx.doi.org/10.1016/j.reseneeco.2009.02.001

[9] J. Axsen, K. S. Kurani, Interpersonal influence within car buyers social networks: applying five perspectives to plug-in hybrid vehicle drivers, Environment and Planning A 44 (5) (2012) 1047{1065. doi:10.1068/a43221. URL http://dx.doi.org/10.1068/a43221

[10] S. Linder, Spatial diffusion of electric vehicles in the german metropolitan region of stuttgart, in: ERSA conference papers, no. ersa11p557, European Regional Science Association, 2011.

[11] M. Tran, Agent-behaviour and network influence on energy innovation diffusion, Communications in Nonlinear Science and Numerical Simulation 17 (9) (2012) 3682{3695. doi:10.1016/j.cnsns.2012.01.016. URL http://dx.doi.org/10.1016/j.cnsns.2012.01.016

[12] M. Tran, Technology-behavioral modelling of energy innovation diffusion in the UK, Applied Energy 95 (2012) 1{11. doi:10.1016/j.apenergy.2012.01.018. URL http://dx.doi.org/10.1016/j.apenergy.2012.01.018

[13] M. J. Eppstein, D. K. Grover, J. S. Marshall, D. M. Rizzo, An agent-based model to study market penetration of plug-in hybrid electric vehicles, Energy Policy 39 (6) (2011) 3789{3802. doi:10.1016/j.enpol.2011.04.007. URL http://dx.doi.org/10.1016/j.enpol.2011.04.007

[14] D. J. Hamilton, W. J. Nuttall, F. A. Roques, Agent based simulation of technology adoption, Tech. rep., EPRG Working Paper 0923, Electricity Policy Research Group, University of Cambridge (2009).26

[15] T. Zhang, W. J. Nuttall, An agent based simulation of smart metering technology adoption, Tech. rep., EPRG Working Paper 0727, Electricity Policy Research Group, University of Cambridge (December 2007).

[16] A. Kowalska-Pyzalska, K. Maciejowska, K. Sznajd-Weron, R. Weron, Going green: Agent-based modeling of the diffusion of dynamic electricity tariffs, Tech. rep., Hugo Steinhaus Center, Wroclaw University of Technology (2013).

[17] S. A. Delre, W. Jager, T. H. A. Bijmolt, M. A. Janssen, Will it spread or not? the effects of social influences and network topology on innovation diffusion, Journal of Product Innovation Management 27 (2) (2010) 267{282. doi:10.1111/j.1540-5885.2010.00714.x. URL http://dx.doi.org/10.1111/j.1540-5885.2010.00714.x

[18] N. J. McCullen, A. M. Rucklidge, C. S. E. Bale, T. J. Foxon, W. F. Gale, Multiparameter models of innovation diffusion on complex networks, SIAM Journal on Applied Dynamical Systems 12 (1) (2013) 515{532. doi:10.1137/120885371. URL http://dx.doi.org/10.1137/120885371

[19] J. Palmer, G. Sorda, R. Madlener, Modeling the diffusion of residential photovoltaic systems in Italy: An agent-based simulation, Tech. rep., EON Energy Research Center, Future Energy Consumer Needs and Behavior (FCN) (2013).

[20] A. R. Campbell, T. Ryley, R. Thring, Identifying the early adopters of alternative fuel vehicles: A case study of birmingham, united kingdom, Transportation Research Part A: Policy and Practice 46 (8) (2012) 1318{1327. doi:10.1016/j.tra.2012.05.004. URL http://dx.doi.org/10.1016/j.tra.2012.05.004

[21] J. Saarenpaa, M. Kolehmainen, H. Niska, Geodemographic analysis and estimation of early plug-in hybrid electric vehicle adoption, Applied Energy 107 (2013) 456-464 doi:10.1016/j.apenergy.2013.02.066. URL http://dx.doi.org/10.1016/j.apenergy.2013.02.066

[22] M. Lai, Y. Poltera, Lecture with computer exercises: Modelling and simulating social systems with matlab, Tech. rep., Swiss Federal Institute of Technology (December 2009). 27

[23] R. Hjorthol, Attitudes, ownership and use of electric vehicles{a review of literature, Tech.rep., 1261/2013, Institute of Transport Economics, Norwegian Centre for Transport Research (2013).

[24] Deloitte, Gaining traction: A customer view of electric vehicle mass adoption in the us auto-motive market, available: http://www.deloitte.com.br (2010).

[25] R. Ozaki, K. Sevastyanova, Going hybrid: An analysis of consumer purchase motivations, Energy Policy 39 (5) (2011) 2217{2227. doi:10.1016/j.enpol.2010.04.024. URL http://dx.doi.org/10.1016/j.enpol.2010.04.024

[26] D. Higham, A. Taylor, Contest (controlable test matrices), university of Strathclyde. URL: http://www.mathstat.strath.ac.uk/outreach/contest (May 2008). URL http://http://www.mathstat.strath.ac.uk/outreach/contest/

[27] S. E. R. G. MIT, Matlab tools for network analysis (2006-2011), uRL: http://strategic.mit.edu/ (November 2011). URL http://strategic.mit.edu

[28] D. J. Watts, S. H. Strogatz, Collective dynamics of small-world networks, Nature 393 (6684) (1998) 440{442.

[29] L. A. N. Amaral, A. Scala, M. Barthelemy, H. E. Stanley, Classes of small-world net- works, Proceedings of the National Academy of Sciences 97 (21) (2000) 11149{11152. doi:10.1073/pnas.200327197. URL http://dx.doi.org/10.1073/pnas.200327197

[30] P. Richardson, D. Flynn, A. Keane, Impact assessment of varying penetrations of electric vehicles on low voltage distribution systems, Institute of Electrical and Electronics Engineers, 2010, pp. 1{6. doi:10.1109/PES.2010.5589940. URL http://dx.doi.org/10.1109/PES.2010.5589940

[31] CER, Commission for energy regulation, 2011b. results of electricity cost-benefit analysis, customer behaviour trials and technology trials. smart metering information paper 4, available: http://www.cer.ie (2011).