Impacts of fleet types and charging modes for electric vehicles on emissions under different penetrations of wind power

Abstract

Current Chinese policy promotes the development of both electricity-propelled vehicles and carbon-free sources of power. Concern has been expressed that electric vehicles on average may emit more CO2 and conventional pollutants in China. Here, we explore the environmental implications of investments in different types of electric vehicle (public buses, taxis and private light-duty vehicles) and different modes (fast or slow) for charging under a range of different wind penetration levels. To do this, we take Beijing in 2020 as a case study and employ hourly simulation of vehicle charging behaviour and power system operation. Assuming the slow-charging option, we find that investments in electric private light-duty vehicles can result in an effective reduction in the emission of CO2 at several levels of wind penetration. The fast-charging option, however, is counter-productive. Electrifying buses and taxis offers the most effective option to reduce emissions of NOx, a major precursor for air pollution.

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Fig. 1: Modelling framework for the integrated energy system optimization.
Fig. 2: Probabilities for physical connection to charging facilities for different vehicles with different charging options.
Fig. 3: Charging consumption profiles for EV fleets and corresponding implications for wind curtailment.
Fig. 4: Relative contributions to emissions of power generation and transportation sectors.

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Acknowledgements

The research was funded in part by the Harvard Global Institute. Additional support was provided by the Hui Fund of the Ash Center of the Harvard Kennedy School of Government. This research is also supported by the State Key Laboratory on Smart Grid Protection and Operation Control of NARI Group, through the open topic project (20171613).

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Correspondence to Xinyu Chen or Michael B. McElroy.

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Supplementary Information

Supplementary Figures 1–6, Supplementary Tables 1–10, Supplementary Notes 1–7 and Supplementary References

Supplementary Data 1

The spreadsheet presents the hourly power demand profiles of Jing-Jin-Tang region and Beijing city, as well as the hourly capacity factors for 12 typical days in each month of the year. Typical coal consumption rates for conventional thermal units and operational characteristics for CHP units are also presented

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Chen, X., Zhang, H., Xu, Z. et al. Impacts of fleet types and charging modes for electric vehicles on emissions under different penetrations of wind power. Nat Energy 3, 413–421 (2018). https://doi.org/10.1038/s41560-018-0133-0

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