Skip to main content

Advertisement

SpringerLink
Log in

Home charge timing choice behaviors of plug-in hybrid electric vehicle users under a dynamic electricity pricing scheme

  • Published:
Transportation Aims and scope Submit manuscript

Abstract

This paper examines choice behaviors pertaining to the time at which users of plug-in hybrid electric vehicle with 24 km electric range charge their vehicles after arriving at home under a dynamic electricity pricing scheme. The following mutually exclusive alternatives are presented: no charging, charging immediately after arriving at home, charging at the cheapest time, and charging at other times. Four versions of a mixed logit model with unobserved heterogeneity are applied to panel data on vehicle usage from 9 households with 2226 observations in Toyota City. Estimation results suggest that users’ willingness to charge become stronger with increasing driving distance when the driving distance is less than the electric range of 24 km, while tend not to charge when the driving distance is longer than the electric range. Users who return home at the cheapest time or during the day are willing to charge immediately after arriving at home. Electricity prices significantly affect choices to charge at the cheapest time for all users, and stay-at-home mother users and users returning home in the evening tend to charge at the cheapest time. Users returning home in the evening also tend to charge at other times, and being accustomed to charge at a certain time increases the probability of charging at other times. In addition, considerable variations are found across individuals with respect to their preferences for charge timing alternatives as well as for electricity prices.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4

Similar content being viewed by others

References

  • Axsen, J., Kurani, K.S.: Anticipating plug-in hybrid vehicle energy impacts in California: constructing consumer-informed recharge profiles. Transp. Res. Part D Transp. Environ. 15(4), 212–219 (2010)

    Article  Google Scholar 

  • Ben-Akiva, M., Bolduc, D.: Multinomial probit with a logit kernel and a general parametric specification of the covariance structure. Working Paper, Department of Civil Engineering, MIT (1996)

  • Bhat, C.R.: Quasi-random maximum simulated likelihood estimation of the mixed multinomial logit model. Transp. Res. Part B Methodol. 35(7), 677–693 (2001)

    Article  Google Scholar 

  • Biviji, M., Uckun, C., Bassett, G., Wang, J.: Patterns of electric vehicle charging with time of use rates: case studies in California and Portland. In: Innovative Smart Grid Technologies Conference, pp. 1–5. IEEE. (2014)

  • Cronbach, L.J.: Coefficient alpha and the internal structure of tests. Psychometrika 16(3), 297–334 (1951)

    Article  Google Scholar 

  • Daina, N., Polak, J. W., Sivakumar, A.: Patent and latent predictors of electric vehicle charging behavior. In: Transportation Research Record: Journal of the Transportation Research Board, No. 2502, Transportation Research Board of the National Academies, Washington, D.C., 2015, pp. 116–123

  • Daina, N., Sivakumar, A., Polak, J.W.: Electric vehicle charging choices: modelling and implications for smart charging services. Transp. Res Part C Emerg. Technol. 81, 36–56 (2017a)

    Article  Google Scholar 

  • Daina, N., Sivakumar, A., Polak, J.W.: Modelling electric vehicles use: a survey on the methods. Renew. Sustain. Energy Rev. 68, 447–460 (2017b)

    Article  Google Scholar 

  • Elgowainy, A., Zhou, Y., Vyas, A.D., Mahalik, M., Santini, D., Wang, M.: Impacts of charging choices for plug-in hybrid electric vehicles in 2030 scenario. Transp. Res. Rec. 2287, 9–17 (2012)

    Article  Google Scholar 

  • Fetene, G.M., Kaplan, S., Sebald, A.C., Prato, C.G.: Myopic loss aversion in the response of electric vehicle owners to the scheduling and pricing of vehicle charging. Transp. Res. Part D Transp. Environ. 50, 345–356 (2017)

    Article  Google Scholar 

  • Geweke, J.: Monte Carlo simulation and numerical integration. Staff Report No. 192, Federal Reserve Bank of Minneapolis (1995)

  • ECOtality: How do PEV owners respond to time-of-use rates while charging vehicles? https://avt.inl.gov/sites/default/files/pdf/EVProj/125348-714937.pev-driver.pdf (2013)

  • Hadley, S.W: Impact of plug-in hybrid vehicles on the electric grid. ORNL/TM-2006/554. Oak Ridge National Laboratory (2006)

  • Halton, J.H.: On the efficiency of certain quasi-random sequences of points in evaluating multi-dimensional integrals. Numer. Math. 2(1), 84–90 (1960)

    Article  Google Scholar 

  • Jabeen, F., Olaru, D., Smith, B., Braunl, T., Speidel, S.: Electric vehicle battery charging behaviour: findings from a driver survey. In: Australasian Transport Research Forum (ATRF), 36th, 2013, Brisbane, Queensland, Australia

  • Nunnaly, J.: Psychometric theory. McGraw-Hill, New York (1978)

    Google Scholar 

  • Revelt, D., Train, K.: Mixed logit with repeated choices: households’ choices of appliance efficiency level. Rev. Econ. Stat. 80(4), 647–657 (1998)

    Article  Google Scholar 

  • Revelt, D., Train, K.: Customer-specific taste parameters and Mixed Logit: households’ choice of electricity supplier. Department of Economics, UCB (2000)

    Google Scholar 

  • Shao, S., Pipattanasomporn, M., Rahman, S.: Challenges of PHEV penetration to the residential distribution network. In: Power and Energy Society General Meeting, 2009. PES’09. IEEE, pp. 1–8. IEEE (2009)

  • Sun, X.-H., Yamamoto, T., Morikawa, T.: Charge timing choice behavior of battery electric vehicle users. Transp. Res. Part D Transp. Environ. 37, 97–107 (2015)

    Article  Google Scholar 

  • Tal, G., Nicholas, M.A., Davies, J., Woodjack, J.: Charging behavior impacts on electric vehicle miles traveled: Who is not plugging in? Transp. Res. Rec. 2454, 53–60 (2014)

    Article  Google Scholar 

  • Taubman-Ben-Ari, O.: Couple similarity for driving style. Transp. Res. Part F Traffic Psychol. Behav. 9(3), 185–193 (2006)

    Article  Google Scholar 

  • Taubman-Ben-Ari, O., Mikulincer, M., Gillath, O.: From parents to children—similarity in parents and offspring driving styles. Transp. Res. Part F Traffic Psychol. Behav. 8(1), 19–29 (2005)

    Article  Google Scholar 

  • Toyota City Low-carbon Society Verification Project (Smart Melit). http://jscp.nepc.or.jp/en/toyota/index.shtml

  • Train, K.: Halton sequences for mixed logit. Department of Economics, UCB (2000)

    Google Scholar 

  • Train, K.E.: Discrete choice methods with simulation. Cambridge University Press, Cambridge (2009)

    Book  Google Scholar 

  • Waraich, R.A., Galus, M.D., Dobler, C., Balmer, M., Andersson, G., Axhausen, K.W.: Plug-in hybrid electric vehicles and smart grids: investigations based on a microsimulation. Transp. Res Part C Emerg. Technol. 28, 74–86 (2013)

    Article  Google Scholar 

  • Zoepf, S., MacKenzie, D., Keith, D., Chernicoff, W.: Charging choices and fuel displacement in a large-Scale demonstration of plug-in hybrid electric vehicles. In: Transportation Research Record: Journal of the Transportation Research Board, No. 2385, Transportation Research Board of the National Academies, Washington, D.C., 2013, pp. 1–10

Download references

Acknowledgements

This paper presents results obtained through research activities conducted in collaboration with Toyota Motor Corporation. This study was also supported by Grant-in-Aid for Scientific Research (No. 25289164) from the Ministry of Education, Culture, Sports, Science and Technology, Japan and the Japan Society for the Promotion of Science, as well as Foundation of Xinjiang University (No. BS160252). The authors also would like to thank Mr. Jun Koreishi and the anonymous reviewers for their valuable comments and suggestions to improve the quality of this paper.

Author information

Authors and Affiliations

  1. School of Civil Engineering and Architecture, Xinjiang University, No. 1230, Yan’an Road, Ürümqi, 830047, Xinjiang, China

    Xiao-Hui Sun

  2. Institute of Materials and Systems for Sustainability, Nagoya University, Furo-cho, Chikusa-ku, Nagoya, 464-8603, Japan

    Toshiyuki Yamamoto

  3. Graduate School of Environmental Studies, Nagoya University, Furo-cho, Chikusa-ku, Nagoya, 464-8603, Japan

    Kazuhiro Takahashi

  4. Institute of Innovation for Future Society, Nagoya University, Furo-cho, Chikusa-ku, Nagoya, 464-8603, Japan

    Takayuki Morikawa

Authors
  1. Xiao-Hui Sun
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Toshiyuki Yamamoto
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Kazuhiro Takahashi
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Takayuki Morikawa
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Xiao-Hui Sun.

Ethics declarations

Conflict of interest

All authors declare that they have no conflict of interest.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Sun, XH., Yamamoto, T., Takahashi, K. et al. Home charge timing choice behaviors of plug-in hybrid electric vehicle users under a dynamic electricity pricing scheme. Transportation 45, 1849–1869 (2018). https://doi.org/10.1007/s11116-018-9948-6

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11116-018-9948-6

Keywords

Search

Navigation