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Modelling the potential for wind energy integration on China’s coal-heavy electricity grid

Author

Listed:
  • Michael R. Davidson

    (China Energy and Climate Project, Joint Program on the Science and Policy of Global Change, Massachusetts Institute of Technology)

  • Da Zhang

    (China Energy and Climate Project, Joint Program on the Science and Policy of Global Change, Massachusetts Institute of Technology
    China Energy and Climate Project, Institute of Energy, Environment, and Economy, Tsinghua University)

  • Weiming Xiong

    (China Energy and Climate Project, Institute of Energy, Environment, and Economy, Tsinghua University)

  • Xiliang Zhang

    (China Energy and Climate Project, Institute of Energy, Environment, and Economy, Tsinghua University
    Research Center for Contemporary Management, Tsinghua University)

  • Valerie J. Karplus

    (China Energy and Climate Project, Joint Program on the Science and Policy of Global Change, Massachusetts Institute of Technology
    Sloan School of Management, Massachusetts Institute of Technology)

Abstract

Expanding the use of wind energy for electricity generation forms an integral part of China’s efforts to address degraded air quality and climate change. However, the integration of wind energy into China’s coal-heavy electricity system presents significant challenges owing to wind’s variability and the grid’s system-wide inflexibilities. Here we develop a model to predict how much wind energy can be generated and integrated into China’s electricity mix, and estimate a potential production of 2.6 petawatt-hours (PWh) per year in 2030. Although this represents 26% of total projected electricity demand, it is only 10% of the total estimated physical potential of wind resources in the country. Increasing the operational flexibility of China’s coal fleet would allow wind to deliver nearly three-quarters of China’s target of producing 20% of primary energy from non-fossil sources by 2030.

Suggested Citation

  • Michael R. Davidson & Da Zhang & Weiming Xiong & Xiliang Zhang & Valerie J. Karplus, 2016. "Modelling the potential for wind energy integration on China’s coal-heavy electricity grid," Nature Energy, Nature, vol. 1(7), pages 1-7, July.
    • Handle: RePEc:nat:natene:v:1:y:2016:i:7:d:10.1038_nenergy.2016.86
    DOI: 10.1038/nenergy.2016.86
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    Cited by:

    1. Ding, Tao & Sun, Yuge & Huang, Can & Mu, Chenlu & Fan, Yuqi & Lin, Jiang & Qin, Yining, 2022. "Pathways of clean energy heating electrification programs for reducing carbon emissions in Northwest China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 166(C).
    2. Qiu, Lihua & He, Li & Kang, Yu & Liang, Dongzhe, 2022. "Assessment of the potential of enhanced geothermal systems in Asia under the impact of global warming," Renewable Energy, Elsevier, vol. 194(C), pages 636-646.
    3. Nycander, Elis & Morales-España, Germán & Söder, Lennart, 2022. "Power-based modelling of renewable variability in dispatch models with clustered time periods," Renewable Energy, Elsevier, vol. 186(C), pages 944-956.
    4. Li, Aitong & Sun, Ying & Song, Xiaobin, 2023. "Gradual improvement and reactive intervention: China's policy pathway for developing the wind power industry," Renewable Energy, Elsevier, vol. 216(C).
    5. Wang, Yadong & Wang, Delu & Shi, Xunpeng, 2023. "Sustainable development pathways of China's wind power industry under uncertainties: Perspective from economic benefits and technical potential," Energy Policy, Elsevier, vol. 182(C).
    6. Tu, Qiang & Mo, Jianlei & Liu, Zhuoran & Gong, Chunxu & Fan, Ying, 2021. "Using green finance to counteract the adverse effects of COVID-19 pandemic on renewable energy investment-The case of offshore wind power in China," Energy Policy, Elsevier, vol. 158(C).
    7. Ahmad, Munir & Khan, Irfan & Shahzad Khan, Muhammad Qaiser & Jabeen, Gul & Jabeen, Hafiza Samra & Işık, Cem, 2023. "Households' perception-based factors influencing biogas adoption: Innovation diffusion framework," Energy, Elsevier, vol. 263(PE).
    8. Zhang, Xiaodong & Patino-Echeverri, Dalia & Li, Mingquan & Wu, Libo, 2022. "A review of publicly available data sources for models to study renewables integration in China's power system," Renewable and Sustainable Energy Reviews, Elsevier, vol. 159(C).
    9. Ding, Qingguo & Wang, Jianxiao & Zhang, Bing & Yu, Yang, 2023. "Economic burden of China's fairness regulations on power generation sector," Energy, Elsevier, vol. 278(C).
    10. Liu, Fa & Sun, Fubao & Wang, Xunming, 2023. "Impact of turbine technology on wind energy potential and CO2 emission reduction under different wind resource conditions in China," Applied Energy, Elsevier, vol. 348(C).
    11. E, Jiaqiang & Zhang, Bin & Zeng, Yan & Wen, Ming & Wei, Kexiang & Huang, Zhonghua & Chen, Jingwei & Zhu, Hao & Deng, Yuanwang, 2022. "Effects analysis on active equalization control of lithium-ion batteries based on intelligent estimation of the state-of-charge," Energy, Elsevier, vol. 238(PB).
    12. Liu, Changyi & Wang, Yang & Zhu, Rong, 2017. "Assessment of the economic potential of China's onshore wind electricity," Resources, Conservation & Recycling, Elsevier, vol. 121(C), pages 33-39.
    13. Zuo, Hongyan & Zhang, Bin & Huang, Zhonghua & Wei, Kexiang & Zhu, Hong & Tan, Jiqiu, 2022. "Effect analysis on SOC values of the power lithium manganate battery during discharging process and its intelligent estimation," Energy, Elsevier, vol. 238(PB).
    14. Xu, Jialong & Moslehpour, Massoud & Tran, Trung Kien & Dinh, Khai Cong & Ngo, Thanh Quang & Huy, Pham Quang, 2023. "The role of institutional quality, renewable energy development and trade openness in green finance: Empirical evidence from South Asian countries," Renewable Energy, Elsevier, vol. 207(C), pages 687-692.
    15. Liu, Ying, 2023. "How does economic recovery impact green finance and renewable energy in Asian economies," Renewable Energy, Elsevier, vol. 208(C), pages 538-545.
    16. Li, Mingquan & Shan, Rui & Virguez, Edgar & Patiño-Echeverri, Dalia & Gao, Shuo & Ma, Haichao, 2022. "Energy storage reduces costs and emissions even without large penetration of renewable energy: The case of China Southern Power Grid," Energy Policy, Elsevier, vol. 161(C).
    17. Jianxiao Wang & Liudong Chen & Zhenfei Tan & Ershun Du & Nian Liu & Jing Ma & Mingyang Sun & Canbing Li & Jie Song & Xi Lu & Chin-Woo Tan & Guannan He, 2023. "Inherent spatiotemporal uncertainty of renewable power in China," Nature Communications, Nature, vol. 14(1), pages 1-11, December.

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