IDEAS home Printed from https://ideas.repec.org/a/eee/enepol/v130y2019icp111-129.html
   My bibliography  Save this article

Who can drive electric? Segmentation of car drivers based on longitudinal GPS travel data

Author

Listed:
  • Sodenkamp, Mariya
  • Wenig, Jürgen
  • Thiesse, Frédéric
  • Staake, Thorsten

Abstract

Current research on the driving performance and energy consumption of electric vehicles (EVs) and plug-in hybrid electric vehicles (PHEVs) considers several criteria, including electric reachability, load to the electric grid, and the share of distances that can be driven electrically. However, prior studies do not distinguish between different driver segments but treat the entirety of drivers as a coherent whole. These aggregated results are hence limited to a macro-level perspective or to an isolated assessment of the recruited driver sample, which reduces the validity of forecasts with respect to specific groups of adopters and their regional impact to the grid. In contrast, the present study outlines a procedure for a segment-wise analysis of drivers using GPS mobility data. The proposed approach allows for both, comparative usability analyses between distinct groups and predictions of the load to the electrical grid on a segment-by-segment basis. We illustrate our approach by the example of a dataset collected from 982 drivers in Italy over two years. The results support decision makers regarding the identification of segment-specific vehicle and infrastructure requirements. Moreover, the insights about benefits and obstacles of EV and PHEV adoption per segment help users take more informed purchasing decisions.

Suggested Citation

  • Sodenkamp, Mariya & Wenig, Jürgen & Thiesse, Frédéric & Staake, Thorsten, 2019. "Who can drive electric? Segmentation of car drivers based on longitudinal GPS travel data," Energy Policy, Elsevier, vol. 130(C), pages 111-129.
    • Handle: RePEc:eee:enepol:v:130:y:2019:i:c:p:111-129
    DOI: 10.1016/j.enpol.2019.03.048
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0301421519302216
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.enpol.2019.03.048?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. De Gennaro, Michele & Paffumi, Elena & Martini, Giorgio, 2015. "Customer-driven design of the recharge infrastructure and Vehicle-to-Grid in urban areas: A large-scale application for electric vehicles deployment," Energy, Elsevier, vol. 82(C), pages 294-311.
    2. Pasaoglu, G. & Fiorello, D. & Martino, A. & Zani, L. & Zubaryeva, A. & Thiel, C., 2014. "Travel patterns and the potential use of electric cars – Results from a direct survey in six European countries," Technological Forecasting and Social Change, Elsevier, vol. 87(C), pages 51-59.
    3. He, Xiaoyi & Wu, Ye & Zhang, Shaojun & Tamor, Michael A. & Wallington, Timothy J. & Shen, Wei & Han, Weijian & Fu, Lixin & Hao, Jiming, 2016. "Individual trip chain distributions for passenger cars: Implications for market acceptance of battery electric vehicles and energy consumption by plug-in hybrid electric vehicles," Applied Energy, Elsevier, vol. 180(C), pages 650-660.
    4. Zachary A. Needell & James McNerney & Michael T. Chang & Jessika E. Trancik, 2016. "Potential for widespread electrification of personal vehicle travel in the United States," Nature Energy, Nature, vol. 1(9), pages 1-7, September.
    5. Clastres, Cédric, 2011. "Smart grids: Another step towards competition, energy security and climate change objectives," Energy Policy, Elsevier, vol. 39(9), pages 5399-5408, September.
    6. Khan, Mobashwir & Kockelman, Kara M., 2012. "Predicting the market potential of plug-in electric vehicles using multiday GPS data," Energy Policy, Elsevier, vol. 46(C), pages 225-233.
    7. Björnsson, Lars-Henrik & Karlsson, Sten, 2015. "Plug-in hybrid electric vehicles: How individual movement patterns affect battery requirements, the potential to replace conventional fuels, and economic viability," Applied Energy, Elsevier, vol. 143(C), pages 336-347.
    8. Cédric Clastres, 2011. "Smart grids : Another step towards competition, energy security and climate change objectives," Post-Print halshs-00617702, HAL.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Manel Arribas-Ibar & Petra A. Nylund & Alexander Brem, 2021. "The Risk of Dissolution of Sustainable Innovation Ecosystems in Times of Crisis: The Electric Vehicle during the COVID-19 Pandemic," Sustainability, MDPI, vol. 13(3), pages 1-14, January.
    2. Hauslbauer, Andrea L. & Schade, Jens & Petzoldt, Tibor, 2022. "The identification of mobility types on a national level," Transport Policy, Elsevier, vol. 125(C), pages 289-298.
    3. Ahmadian, Amirhossein & Ghodrati, Vahid & Gadh, Rajit, 2023. "Artificial deep neural network enables one-size-fits-all electric vehicle user behavior prediction framework," Applied Energy, Elsevier, vol. 352(C).
    4. Powell, Siobhan & Cezar, Gustavo Vianna & Rajagopal, Ram, 2022. "Scalable probabilistic estimates of electric vehicle charging given observed driver behavior," Applied Energy, Elsevier, vol. 309(C).
    5. Powell, Siobhan & Vianna Cezar, Gustavo & Apostolaki-Iosifidou, Elpiniki & Rajagopal, Ram, 2022. "Large-scale scenarios of electric vehicle charging with a data-driven model of control," Energy, Elsevier, vol. 248(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Tu, Wei & Santi, Paolo & Zhao, Tianhong & He, Xiaoyi & Li, Qingquan & Dong, Lei & Wallington, Timothy J. & Ratti, Carlo, 2019. "Acceptability, energy consumption, and costs of electric vehicle for ride-hailing drivers in Beijing," Applied Energy, Elsevier, vol. 250(C), pages 147-160.
    2. Kang, Jia-Ning & Wei, Yi-Ming & Liu, Lan-Cui & Han, Rong & Yu, Bi-Ying & Wang, Jin-Wei, 2020. "Energy systems for climate change mitigation: A systematic review," Applied Energy, Elsevier, vol. 263(C).
    3. Nallapaneni Manoj Kumar & Aneesh A. Chand & Maria Malvoni & Kushal A. Prasad & Kabir A. Mamun & F.R. Islam & Shauhrat S. Chopra, 2020. "Distributed Energy Resources and the Application of AI, IoT, and Blockchain in Smart Grids," Energies, MDPI, vol. 13(21), pages 1-42, November.
    4. Kovacic, Zora & Giampietro, Mario, 2015. "Empty promises or promising futures? The case of smart grids," Energy, Elsevier, vol. 93(P1), pages 67-74.
    5. Shi, Xiao & Pan, Jian & Wang, Hewu & Cai, Hua, 2019. "Battery electric vehicles: What is the minimum range required?," Energy, Elsevier, vol. 166(C), pages 352-358.
    6. Sun, Hao & Yang, Jun & Yang, Chao, 2019. "A robust optimization approach to multi-interval location-inventory and recharging planning for electric vehicles," Omega, Elsevier, vol. 86(C), pages 59-75.
    7. Martínez-Lao, Juan & Montoya, Francisco G. & Montoya, Maria G. & Manzano-Agugliaro, Francisco, 2017. "Electric vehicles in Spain: An overview of charging systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 77(C), pages 970-983.
    8. Ponce, Pedro & Polasko, Kenneth & Molina, Arturo, 2016. "End user perceptions toward smart grid technology: Acceptance, adoption, risks, and trust," Renewable and Sustainable Energy Reviews, Elsevier, vol. 60(C), pages 587-598.
    9. Kokou Amega & Yendoubé Laré & Ramchandra Bhandari & Yacouba Moumouni & Aklesso Y. G. Egbendewe & Windmanagda Sawadogo & Saidou Madougou, 2022. "Solar Energy Powered Decentralized Smart-Grid for Sustainable Energy Supply in Low-Income Countries: Analysis Considering Climate Change Influences in Togo," Energies, MDPI, vol. 15(24), pages 1-24, December.
    10. Timothé Beaufils & Pierre-Olivier Pineau, 2018. "Structures tarifaires et spirale de la mort : État des lieux des pratiques de tarification dans la distribution d’électricité résidentielle," CIRANO Working Papers 2018s-27, CIRANO.
    11. Yanshan Yu & Jin Yang & Bin Chen, 2012. "The Smart Grids in China—A Review," Energies, MDPI, vol. 5(5), pages 1-18, May.
    12. Mabee, Warren E. & Mannion, Justine & Carpenter, Tom, 2012. "Comparing the feed-in tariff incentives for renewable electricity in Ontario and Germany," Energy Policy, Elsevier, vol. 40(C), pages 480-489.
    13. Kumar, Yogesh & Ringenberg, Jordan & Depuru, Soma Shekara & Devabhaktuni, Vijay K. & Lee, Jin Woo & Nikolaidis, Efstratios & Andersen, Brett & Afjeh, Abdollah, 2016. "Wind energy: Trends and enabling technologies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 53(C), pages 209-224.
    14. Maarten Wolsink, 2020. "Framing in Renewable Energy Policies: A Glossary," Energies, MDPI, vol. 13(11), pages 1-31, June.
    15. Weiwei Liu & Yuan Tao & Zhile Yang & Kexin Bi, 2019. "Exploring and Visualizing the Patent Collaboration Network: A Case Study of Smart Grid Field in China," Sustainability, MDPI, vol. 11(2), pages 1-18, January.
    16. Clastres, Cédric & Khalfallah, Haikel, 2021. "Dynamic pricing efficiency with strategic retailers and consumers: An analytical analysis of short-term market interactions," Energy Economics, Elsevier, vol. 98(C).
    17. Fatih Issi & Orhan Kaplan, 2018. "The Determination of Load Profiles and Power Consumptions of Home Appliances," Energies, MDPI, vol. 11(3), pages 1-18, March.
    18. Jacqueline Corbett, 2013. "Using information systems to improve energy efficiency: Do smart meters make a difference?," Information Systems Frontiers, Springer, vol. 15(5), pages 747-760, November.
    19. Kendel, Adnane & Lazaric, Nathalie & Maréchal, Kevin, 2017. "What do people ‘learn by looking’ at direct feedback on their energy consumption? Results of a field study in Southern France," Energy Policy, Elsevier, vol. 108(C), pages 593-605.
    20. Buryk, Stephen & Mead, Doug & Mourato, Susana & Torriti, Jacopo, 2015. "Investigating preferences for dynamic electricity tariffs: The effect of environmental and system benefit disclosure," Energy Policy, Elsevier, vol. 80(C), pages 190-195.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:enepol:v:130:y:2019:i:c:p:111-129. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/enpol .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.