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Modeling the impact of EVs in the Chinese power system: Pathways for implementing emissions reduction commitments in the power and transportation sectors

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  • Li, Bo
  • Ma, Ziming
  • Hidalgo-Gonzalez, Patricia
  • Lathem, Alex
  • Fedorova, Natalie
  • He, Gang
  • Zhong, Haiwang
  • Chen, Minyou
  • Kammen, Daniel M.

Abstract

The deployment of renewable electricity and electric vehicles (EVs) provides a synergistic opportunity to accelerate the decarbonization of both China's power and transportation sectors. Here, we evaluate the potential impacts of EVs by utilizing the SWITCH-China model designed to meet emissions constraints within its power sector while integrating the electrified transportation sector. We focus on how various EV stocks, and charging strategies (unmanaged versus smart charging) impact the power sector, in terms of generation and hourly grid operation, the capacity mix, and achieving the Paris Agreement goals. Large-scale deployment of EVs increases the need for generation capacity, while the implementation of smart charging requires 6.8%–14% less additional storage capacity. We calculate that power system integration costs to incorporate EVs range from $228 - $352 per EV. We show that a smart charging strategy saves between $43 and $123 per vehicle more annually in 2050 than a case with the same EV stock where the charging is unmanaged. Our results suggest that a 140 GW annual growth of renewables from 2020 to 2050, coupled with an aggressive EVs deployment using smart charging can put China solidly on a path to meet its ambitious carbon cap targets.

Suggested Citation

  • Li, Bo & Ma, Ziming & Hidalgo-Gonzalez, Patricia & Lathem, Alex & Fedorova, Natalie & He, Gang & Zhong, Haiwang & Chen, Minyou & Kammen, Daniel M., 2021. "Modeling the impact of EVs in the Chinese power system: Pathways for implementing emissions reduction commitments in the power and transportation sectors," Energy Policy, Elsevier, vol. 149(C).
    • Handle: RePEc:eee:enepol:v:149:y:2021:i:c:s030142152030673x
    DOI: 10.1016/j.enpol.2020.111962
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    5. Wu, Kunming & Li, Qiang & Chen, Ziyu & Lin, Jiayang & Yi, Yongli & Chen, Minyou, 2021. "Distributed optimization method with weighted gradients for economic dispatch problem of multi-microgrid systems," Energy, Elsevier, vol. 222(C).
    6. Jun Dong & Dongran Liu & Xihao Dou & Bo Li & Shiyao Lv & Yuzheng Jiang & Tongtao Ma, 2021. "Key Issues and Technical Applications in the Study of Power Markets as the System Adapts to the New Power System in China," Sustainability, MDPI, vol. 13(23), pages 1-29, December.
    7. Luo, Shihua & Hu, Weihao & Liu, Wen & Zhang, Zhenyuan & Bai, Chunguang & Huang, Qi & Chen, Zhe, 2022. "Study on the decarbonization in China's power sector under the background of carbon neutrality by 2060," Renewable and Sustainable Energy Reviews, Elsevier, vol. 166(C).
    8. Choi, Hyunhong & Lee, Jeongeun & Koo, Yoonmo, 2023. "Value of different electric vehicle charging facility types under different availability situations: A South Korean case study of electric vehicle and internal combustion engine vehicle owners," Energy Policy, Elsevier, vol. 174(C).

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