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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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).
The authors declare no competing financial interests.
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Davidson, M., Zhang, D., Xiong, W. et al. Modelling the potential for wind energy integration on China’s coal-heavy electricity grid. Nat Energy 1, 16086 (2016). https://doi.org/10.1038/nenergy.2016.86
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