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

Nature Energy volume 1, Article number: 16086 (2016) | Download Citation


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.

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  1. 1.

    National Bureau of Statistics Annual Electricity Production (Various Years 2004–2014) (China Statistics Press, 2015).

  2. 2.

    Wind Industry Development Statistics 2015 (National Energy Administration, 2016);

  3. 3.

    China Wind Energy Roadmap 2050 (Energy Research Institute, 2014).

  4. 4.

    , ,  & Potential for wind-generated electricity in China. Science 325, 1378–1380 (2009).

  5. 5.

    Global CFDDA-Based Onshore and Offshore Wind Potential Supply Curves (National Renewable Energy Laboratory, 2013);

  6. 6.

    Energy Research Institute China Wind Power Development Towards 2030 -Feasibility Study on Wind Power Contribution to 10% of Power Demand in China (Energy Foundation, 2010).

  7. 7.

     & Offshore wind energy potential in China: under technical, spatial and economic constraints. Energy 36, 4482–4491 (2011).

  8. 8.

    et al. China: An Emerging Offshore Wind Development Hotspot–with a New Assessment of China’s Offshore Wind Potential (Chinese Wind Energy Association, 2010).

  9. 9.

    , , ,  & Optimal integration of offshore wind power for a steadier, environmentally friendlier, supply of electricity in China. Energy Policy 62, 131–138 (2013).

  10. 10.

    ,  & Non-Fossil Energy Development Objective and Realizing Route in China (China Electric Power Press, 2013).

  11. 11.

     & Air emissions due to wind and solar power. Environ. Sci. Technol. 43, 253–258 (2009).

  12. 12.

    ,  & Development effects of electrification: evidence from the topographic placement of hydropower plants in Brazil. Am. Econ. J. Appl. Econ. 5, 200–231 (2013).

  13. 13.

    , , ,  & An Integrated Assessment of China’s Wind Energy Potential (MIT Joint Program on the Science and Policy of Global Change, 2014).

  14. 14.

    et al. MERRA: NASA’s Modern-Era Retrospective Analysis for Research and Applications. J. Clim. 24, 3624–3648 (2011).

  15. 15.

    ,  & Global potential for wind-generated electricity. Proc. Natl Acad. Sci. USA 106, 10933–10938 (2009).

  16. 16.

    Shuttle Radar Topography Mission (US Geological Survey, 2004).

  17. 17.

    , ,  & Land-cover classification of China: integrated analysis of AVHRR imagery and geophysical data. Int. J. Remote Sens. 24, 2485–2500 (2003).

  18. 18.

    The World Database on Protected Areas (IUCN and UNEP-WCMC, 2013);

  19. 19.

    NASA Land Processes Distributed Active Archive Center MCD12Q1: Land Cover Type Yearly L3 Global 500 m SIN Grid (NASA, 2010).

  20. 20.

     & Documenting wind speed and power deficits behind a utility-scale wind turbine. J. Appl. Meteorol. Climatol. 52, 39–46 (2013).

  21. 21.

    Comparing the costs of intermittent and dispatchable electricity generating technologies. Am. Econ. Rev. 101, 238–241 (2011).

  22. 22.

    Notice of Completing Onshore Wind and Solar Benchmark On-Grid Tariff (National Development and Reform Commission, 2015); preprint at

  23. 23.

    ,  & A review of the international experience with integrating wind energy generation. Electr. J. 20, 48–59 (2007).

  24. 24.

    ,  & The political economy of electricity dispatch reform in China. Energy Policy 53, 361–369 (2013).

  25. 25.

    , ,  & To what extent does wind power deployment affect vested interests? A case study of the Northeast China Grid. Energy Policy 63, 814–822 (2013).

  26. 26.

    National Bureau of Statistics Monthly Electricity Production (Various Years) (CEIC Data, 2014).

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We thank the consortium of founding sponsors of the MIT-Tsinghua China Energy and Climate Project Eni S.p.A., the French Development Agency (AFD), ICF International, and Shell International Limited for funding this work at MIT. We are grateful to the National Science Foundation of China (Grant No. 71573152), the Ministry of Science and Technology of China, the National Development and Reform Commission of China, the National Energy Administration of China, Rio Tinto, and Total for supporting this research at Tsinghua University. We further thank the Energy Information Administration of the US Department of Energy for support to MIT through a cooperative agreement. At MIT the China Energy and Climate Project is part of the MIT Joint Program on the Science and Policy of Global Change, which is funded through a consortium of industrial sponsors and Federal grants, including the US Department of Energy Office of Science (Grant No. DE-FG02-94ER61937).

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Author notes

    • Michael R. Davidson
    •  & Da Zhang

    These authors contributed equally to this work.


  1. China Energy and Climate Project, Joint Program on the Science and Policy of Global Change, Massachusetts Institute of Technology, Cambridge, Massachusetts 02138, USA

    • Michael R. Davidson
    • , Da Zhang
    •  & Valerie J. Karplus
  2. China Energy and Climate Project, Institute of Energy, Environment, and Economy, Tsinghua University, Beijing 100084, China

    • Da Zhang
    • , Weiming Xiong
    •  & Xiliang Zhang
  3. Research Center for Contemporary Management, Tsinghua University, Beijing 100084, China

    • Xiliang Zhang
  4. Sloan School of Management, Massachusetts Institute of Technology, Cambridge, Massachusetts 02138, USA

    • Valerie J. Karplus


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All authors conceived the research. M.R.D. and D.Z. constructed the simulation model. M.R.D., W.X., D.Z. and X.Z. provided the data. M.R.D., W.X. and D.Z. performed the analysis. M.R.D., V.J.K. and D.Z. drew the figures. M.R.D., V.J.K., W.X. and D.Z. wrote the paper. All authors contributed to the interpretation of the findings. M.R.D. and D.Z. contributed equally to this work. V.J.K. and X.Z. jointly supervised this work. Author contributions are listed here in alphabetical order.

Competing interests

The authors declare no competing financial interests.

Corresponding authors

Correspondence to Xiliang Zhang or Valerie J. Karplus.

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    Supplementary Information

    Supplementary Notes 1–7, Supplementary Tables 1–21, Supplementary Figures 1–11, Supplementary References.

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