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Potential Co-benefit effect analysis of orderly charging and discharging of electric vehicles in China

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  • Zhou, Chao-bo
  • Qi, Shao-zhou
  • Zhang, Ji-hong
  • Tang, Si-yan

Abstract

As a flexible power grid load regulation facility, the orderly participation of electric vehicles (EVs) in power grid load regulation is conducive to the low-carbon transformation of energy system. To measure the co-benefit effect of orderly charging and discharging of EVs on carbon reduction, power grid security and economy, We build the calculation model of orderly charging and discharging of China’s EVs and compare the co-benefit effect of economic incentive orderly charging strategy, economic incentive + technology control orderly charging strategy under different penetration rates of EVs. Results show that in the Central China power grid, the peak load of can be reduced and valley load of can be improved by orderly charging and discharging with economic incentive + technology control strategy. With this method, 440 thousand EVs can reduce 31.2 thousand tons of coal consumption and 86.2 thousand tons of carbon emissions, save 4.29 billion yuan of project investment and increase 1.137 million KW grid margin. A 100% penetration rate of EVs can reduce 964.8 thousand tons of coal consumption and 2.25 million tons of carbon emissions, save 21.87 billion yuan of project investment, and increase grid margin by 5.79 million KW.

Suggested Citation

  • Zhou, Chao-bo & Qi, Shao-zhou & Zhang, Ji-hong & Tang, Si-yan, 2021. "Potential Co-benefit effect analysis of orderly charging and discharging of electric vehicles in China," Energy, Elsevier, vol. 226(C).
    • Handle: RePEc:eee:energy:v:226:y:2021:i:c:s0360544221006010
    DOI: 10.1016/j.energy.2021.120352
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    References listed on IDEAS

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    Cited by:

    1. Muhammad Usman & Wajahat Ullah Khan Tareen & Adil Amin & Haider Ali & Inam Bari & Muhammad Sajid & Mehdi Seyedmahmoudian & Alex Stojcevski & Anzar Mahmood & Saad Mekhilef, 2021. "A Coordinated Charging Scheduling of Electric Vehicles Considering Optimal Charging Time for Network Power Loss Minimization," Energies, MDPI, vol. 14(17), pages 1-16, August.
    2. 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).

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