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The effects of electric vehicles on residential households in the city of Indianapolis

Author

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  • Huang, Shisheng
  • Safiullah, Hameed
  • Xiao, Jingjie
  • Hodge, Bri-Mathias S.
  • Hoffman, Ray
  • Soller, Joan
  • Jones, Doug
  • Dininger, Dennis
  • Tyner, Wallace E.
  • Liu, Andrew
  • Pekny, Joseph F.

Abstract

There is an increasing impetus to transform the U.S transportation sector and transition away from the uncertainties of oil supply. One of the most viable current solutions is the adoption of electric vehicles (EVs). These vehicles allow for a transportation system that would be flexible in its fuel demands. However, utilities may need to address questions such as distribution constraints, electricity tariffs and incentives and public charging locations before large scale electric vehicle adoption can be realized. In this study, the effect of electric vehicles on households in Indianapolis is examined. A four-step traffic flow model is used to characterize the usage characteristics of vehicles in the Indianapolis metropolitan area. This data is then used to simulate EV usage patterns which can be used to determine household electricity usage characteristics. These results are differentiated by the zones with which the households are associated. Economic costs are then calculated for the individual households. Finally, possible public charging locations are examined.

Suggested Citation

  • Huang, Shisheng & Safiullah, Hameed & Xiao, Jingjie & Hodge, Bri-Mathias S. & Hoffman, Ray & Soller, Joan & Jones, Doug & Dininger, Dennis & Tyner, Wallace E. & Liu, Andrew & Pekny, Joseph F., 2012. "The effects of electric vehicles on residential households in the city of Indianapolis," Energy Policy, Elsevier, vol. 49(C), pages 442-455.
    • Handle: RePEc:eee:enepol:v:49:y:2012:i:c:p:442-455
    DOI: 10.1016/j.enpol.2012.06.039
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    References listed on IDEAS

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    Cited by:

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    2. Satre-Meloy, Aven, 2019. "Investigating structural and occupant drivers of annual residential electricity consumption using regularization in regression models," Energy, Elsevier, vol. 174(C), pages 148-168.
    3. Sujie Shao & Shaoyong Guo & Xuesong Qiu, 2017. "A Mobile Battery Swapping Service for Electric Vehicles Based on a Battery Swapping Van," Energies, MDPI, vol. 10(10), pages 1-21, October.
    4. Martos, A. & Pacheco-Torres, R. & Ordóñez, J. & Jadraque-Gago, E., 2016. "Towards successful environmental performance of sustainable cities: Intervening sectors. A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 57(C), pages 479-495.
    5. Liu, Wen & Hu, Weihao & Lund, Henrik & Chen, Zhe, 2013. "Electric vehicles and large-scale integration of wind power – The case of Inner Mongolia in China," Applied Energy, Elsevier, vol. 104(C), pages 445-456.
    6. Jung, Jaesung & Cho, Yongju & Cheng, Danling & Onen, Ahmet & Arghandeh, Reza & Dilek, Murat & Broadwater, Robert P., 2013. "Monte Carlo analysis of Plug-in Hybrid Vehicles and Distributed Energy Resource growth with residential energy storage in Michigan," Applied Energy, Elsevier, vol. 108(C), pages 218-235.
    7. Requia, Weeberb J. & Adams, Matthew D. & Arain, Altaf & Koutrakis, Petros & Ferguson, Mark, 2017. "Carbon dioxide emissions of plug-in hybrid electric vehicles: A life-cycle analysis in eight Canadian cities," Renewable and Sustainable Energy Reviews, Elsevier, vol. 78(C), pages 1390-1396.
    8. Xiao, Jingjie, 2013. "Grid integration and smart grid implementation of emerging technologies in electric power systems through approximate dynamic programming," MPRA Paper 58696, University Library of Munich, Germany.
    9. Muhammad Naveed Iqbal & Lauri Kütt & Matti Lehtonen & Robert John Millar & Verner Püvi & Anton Rassõlkin & Galina L. Demidova, 2021. "Travel Activity Based Stochastic Modelling of Load and Charging State of Electric Vehicles," Sustainability, MDPI, vol. 13(3), pages 1-14, February.

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