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Analysis and Modeling of Value Creation Opportunities and Governing Factors for Electric Vehicle Proliferation

Author

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  • Abhinav Tiwari

    (Department of Electrical Engineering and Computer Science, York University, 4700 Keele Street, Toronto, ON M3J 1P3, Canada)

  • Hany Farag

    (Department of Electrical Engineering and Computer Science, York University, 4700 Keele Street, Toronto, ON M3J 1P3, Canada)

Abstract

This research presents a comprehensive analysis of electric vehicle (EV) proliferation factors and various monetary and non-monetary value streams emerging in the EV domain. A comprehensive mathematical model is implemented to study EV proliferation and the resulting market share applicable to any geography and jurisdictional regime. Further, a novel framework is presented to analyze the interdependency between EV proliferation factors and value streams. The proposed model and framework can be leveraged to quantifiably evaluate the timeline available for grid operators to accommodate EV growth while utilizing those as Distributed Energy Resources (DERs) to improve grid reliability, commercial value, and environmental benefits. Compared to the previous studies, the analysis indicated that if all the factors which impact EV proliferation are addressed simultaneously, EV market share can surpass the internal combustion engine vehicle (ICV) in as quickly as 15–20 years. The study also highlighted the importance of policy making around EVs, which can offset EV market share by up to 10% between two countries following similar sustainability goals. Therefore, the study also helps aid decision making around policies and technology investments by public and private sector organizations in the space of EV.

Suggested Citation

  • Abhinav Tiwari & Hany Farag, 2022. "Analysis and Modeling of Value Creation Opportunities and Governing Factors for Electric Vehicle Proliferation," Energies, MDPI, vol. 16(1), pages 1-26, December.
    • Handle: RePEc:gam:jeners:v:16:y:2022:i:1:p:438-:d:1020409
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    References listed on IDEAS

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    1. Shahid Hussain & Mohamed A. Ahmed & Ki-Beom Lee & Young-Chon Kim, 2020. "Fuzzy Logic Weight Based Charging Scheme for Optimal Distribution of Charging Power among Electric Vehicles in a Parking Lot," Energies, MDPI, vol. 13(12), pages 1-27, June.
    2. Powell, Siobhan & Kara, Emre Can & Sevlian, Raffi & Cezar, Gustavo Vianna & Kiliccote, Sila & Rajagopal, Ram, 2020. "Controlled workplace charging of electric vehicles: The impact of rate schedules on transformer aging," Applied Energy, Elsevier, vol. 276(C).
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