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Spatiotemporal model for estimating electric vehicles adopters

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  • Rodrigues, João L.
  • Bolognesi, Hugo M.
  • Melo, Joel D.
  • Heymann, Fabian
  • Soares, F.J.

Abstract

The use of fossil fuel vehicles is one of the factors responsible for the degradation of air quality in urban areas. In order to reduce levels of air pollution in metropolitan areas, several countries have encouraged the use of electric vehicles in the cities. However, due to the high investment costs in this class of vehicles, it is expected that the spatial distribution of electric vehicles' adopters will be heterogeneous. The additional charging power required by electric vehicles' batteries can change operation and expansion planning of power distribution utilities. In addition, urban planning agencies should analyze the most suitable locations for the construction of electric vehicle recharging stations. Thus, in order to provide information for the planning of electric mobility services in the city, this paper presents a spatiotemporal model for estimating the rate of electric vehicles' adopters per subareas. Results are spatial databases that can be viewed in geographic information systems to observe regions with greater expectancy of residential electric vehicle adopters. These outcomes can help utilities to develop new services that ground on the rising availability of electric mobility in urban zones.

Suggested Citation

  • Rodrigues, João L. & Bolognesi, Hugo M. & Melo, Joel D. & Heymann, Fabian & Soares, F.J., 2019. "Spatiotemporal model for estimating electric vehicles adopters," Energy, Elsevier, vol. 183(C), pages 788-802.
  • Handle: RePEc:eee:energy:v:183:y:2019:i:c:p:788-802
    DOI: 10.1016/j.energy.2019.06.117
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    as
    1. Lin, Haiyang & Liu, Yiling & Sun, Qie & Xiong, Rui & Li, Hailong & Wennersten, Ronald, 2018. "The impact of electric vehicle penetration and charging patterns on the management of energy hub – A multi-agent system simulation," Applied Energy, Elsevier, vol. 230(C), pages 189-206.
    2. Egbue, Ona & Long, Suzanna, 2012. "Barriers to widespread adoption of electric vehicles: An analysis of consumer attitudes and perceptions," Energy Policy, Elsevier, vol. 48(C), pages 717-729.
    3. De Gennaro, Michele & Paffumi, Elena & Scholz, Harald & Martini, Giorgio, 2014. "GIS-driven analysis of e-mobility in urban areas: An evaluation of the impact on the electric energy grid," Applied Energy, Elsevier, vol. 124(C), pages 94-116.
    4. Daina, Nicolò & Sivakumar, Aruna & Polak, John W., 2017. "Modelling electric vehicles use: a survey on the methods," Renewable and Sustainable Energy Reviews, Elsevier, vol. 68(P1), pages 447-460.
    5. Hamamoto, Mitsutsugu, 2019. "An empirical study on the behavior of hybrid-electric vehicle purchasers," Energy Policy, Elsevier, vol. 125(C), pages 286-292.
    6. Frank M. Bass, 2004. "Comments on "A New Product Growth for Model Consumer Durables The Bass Model"," Management Science, INFORMS, vol. 50(12_supple), pages 1833-1840, December.
    7. Javid, Roxana J. & Nejat, Ali, 2017. "A comprehensive model of regional electric vehicle adoption and penetration," Transport Policy, Elsevier, vol. 54(C), pages 30-42.
    8. Jacques-Francois Thisse, 2014. "The New Science of Cities by Michael Batty: The Opinion of an Economist," Journal of Economic Literature, American Economic Association, vol. 52(3), pages 805-819, September.
    9. Chen, T. Donna & Wang, Yiyi & Kockelman, Kara M., 2015. "Where are the electric vehicles? A spatial model for vehicle-choice count data," Journal of Transport Geography, Elsevier, vol. 43(C), pages 181-188.
    10. Kim, Yunmi & Kim, Tae-Hwan & Ergün, Tolga, 2015. "The instability of the Pearson correlation coefficient in the presence of coincidental outliers," Finance Research Letters, Elsevier, vol. 13(C), pages 243-257.
    11. Bryan Bollinger & Kenneth Gillingham, 2012. "Peer Effects in the Diffusion of Solar Photovoltaic Panels," Marketing Science, INFORMS, vol. 31(6), pages 900-912, November.
    12. Byun, Hyunsuk & Shin, Jungwoo & Lee, Chul-Yong, 2018. "Using a discrete choice experiment to predict the penetration possibility of environmentally friendly vehicles," Energy, Elsevier, vol. 144(C), pages 312-321.
    13. Yong, Jia Ying & Ramachandaramurthy, Vigna K. & Tan, Kang Miao & Mithulananthan, N., 2015. "A review on the state-of-the-art technologies of electric vehicle, its impacts and prospects," Renewable and Sustainable Energy Reviews, Elsevier, vol. 49(C), pages 365-385.
    14. Priessner, Alfons & Sposato, Robert & Hampl, Nina, 2018. "Predictors of electric vehicle adoption: An analysis of potential electric vehicle drivers in Austria," Energy Policy, Elsevier, vol. 122(C), pages 701-714.
    15. Seixas, J. & Simões, S. & Dias, L. & Kanudia, A. & Fortes, P. & Gargiulo, M., 2015. "Assessing the cost-effectiveness of electric vehicles in European countries using integrated modeling," Energy Policy, Elsevier, vol. 80(C), pages 165-176.
    16. Mu, Yunfei & Wu, Jianzhong & Jenkins, Nick & Jia, Hongjie & Wang, Chengshan, 2014. "A Spatial–Temporal model for grid impact analysis of plug-in electric vehicles," Applied Energy, Elsevier, vol. 114(C), pages 456-465.
    17. Hainmueller, Jens & Hopkins, Daniel J. & Yamamoto, Teppei, 2014. "Causal Inference in Conjoint Analysis: Understanding Multidimensional Choices via Stated Preference Experiments," Political Analysis, Cambridge University Press, vol. 22(1), pages 1-30, January.
    18. Gnann, Till & Stephens, Thomas S. & Lin, Zhenhong & Plötz, Patrick & Liu, Changzheng & Brokate, Jens, 2018. "What drives the market for plug-in electric vehicles? - A review of international PEV market diffusion models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 93(C), pages 158-164.
    19. Andersson, Erik & McPhearson, Timon & Kremer, Peleg & Gomez-Baggethun, Erik & Haase, Dagmar & Tuvendal, Magnus & Wurster, Daniel, 2015. "Scale and context dependence of ecosystem service providing units," Ecosystem Services, Elsevier, vol. 12(C), pages 157-164.
    20. Wang, Sinan & Zhao, Fuquan & Liu, Zongwei & Hao, Han, 2018. "Impacts of a super credit policy on electric vehicle penetration and compliance with China's Corporate Average Fuel Consumption regulation," Energy, Elsevier, vol. 155(C), pages 746-762.
    21. Daniel P. McMillen, 2013. "Quantile Regression for Spatial Data," SpringerBriefs in Regional Science, Springer, edition 127, number 978-3-642-31815-3, November.
    22. Frank M. Bass, 2004. "A New Product Growth for Model Consumer Durables," Management Science, INFORMS, vol. 50(12_supple), pages 1825-1832, December.
    23. Shafiullah, Md & Rahman, Syed Masiur & Mortoja, Md. Golam & Al-Ramadan, Baqer, 2016. "Role of spatial analysis technology in power system industry: An overview," Renewable and Sustainable Energy Reviews, Elsevier, vol. 66(C), pages 584-595.
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