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Technology roadmap for smart electric vehicle-to-grid (V2G) of residential chargers

Author

Listed:
  • Tugrul U. Daim

    (Portland State University)

  • Xiaowen Wang

    (Portland State University)

  • Kelly Cowan

    (Portland State University)

  • Tom Shott

    (Portland State University)

Abstract

Smart grid is defined as the overlaying of a unified communications and control system onto the existing power delivery infrastructure to provide the right information and the right entity at the right time. It helps even out demand spikes and uses resource mix more efficiently. It is a better integration, or “system balancing,” of variable resources, like wind power. Many of the advanced applications of smart grid are expected to develop in an evolutionary manner based on current technologies available and the needs of the market, for example, electric vehicles (EVs) or plug-in hybrid electric vehicles (PHEVs). It is likely that we will see a simpler associated application (i.e., smart battery charger) before the market matures to support a more complex form of the application vehicle-to-grid (V2G). The objective of this paper is to develop a technology roadmapping (TRM) process for smart electric V2G technologies in Oregon and the Pacific Northwest (PNW). The research focuses on the application of V2G in the residential chargers. It introduces the market drivers, products, and technology analysis and also provides research on the necessary resources needed within R&D in the coming years (next 10 years).

Suggested Citation

  • Tugrul U. Daim & Xiaowen Wang & Kelly Cowan & Tom Shott, 2016. "Technology roadmap for smart electric vehicle-to-grid (V2G) of residential chargers," Journal of Innovation and Entrepreneurship, Springer, vol. 5(1), pages 1-13, December.
    • Handle: RePEc:spr:joiaen:v:5:y:2016:i:1:d:10.1186_s13731-016-0043-y
    DOI: 10.1186/s13731-016-0043-y
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    References listed on IDEAS

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    1. Guille, Christophe & Gross, George, 2009. "A conceptual framework for the vehicle-to-grid (V2G) implementation," Energy Policy, Elsevier, vol. 37(11), pages 4379-4390, November.
    2. Kiviluoma, Juha & Meibom, Peter, 2011. "Methodology for modelling plug-in electric vehicles in the power system and cost estimates for a system with either smart or dumb electric vehicles," Energy, Elsevier, vol. 36(3), pages 1758-1767.
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    Cited by:

    1. Carolin Stockkamp & Juliane Schäfer & Jan A. Millemann & Sven Heidenreich, 2021. "Identifying Factors Associated with Consumers’ Adoption of e-Mobility—A Systematic Literature Review," Sustainability, MDPI, vol. 13(19), pages 1-17, October.
    2. Theodoros A. Skouras & Panagiotis K. Gkonis & Charalampos N. Ilias & Panagiotis T. Trakadas & Eleftherios G. Tsampasis & Theodore V. Zahariadis, 2019. "Electrical Vehicles: Current State of the Art, Future Challenges, and Perspectives," Clean Technol., MDPI, vol. 2(1), pages 1-16, December.
    3. Faris Adnan Padhilah & Kyeong-Hwa Kim, 2021. "A Centralized Power Flow Control Scheme of EV-Connected DC Microgrid to Satisfy Multi-Objective Problems under Several Constraints," Sustainability, MDPI, vol. 13(16), pages 1-37, August.
    4. Samaneh Mohebalizadeh & Soroush Ghazinoori, 2021. "Developing a Technology Roadmap for Regenerative Medicine: A Participatory Action Research," Systemic Practice and Action Research, Springer, vol. 34(4), pages 377-397, August.

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