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

Joint Program Reprint • Journal Article
 • China Energy & Climate Project
Modelling the potential for wind energy integration on China's coal-heavy electricity grid
Davidson, M.R., D. Zhang, W. Xiong, X. Zhang & V.J. Karplus (2016)
Nature Energy, 1: Article #16086

Reprint 2016-14 [Read Full Article]

Abstract/Summary:

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.

China, the world’s largest energy consumer and greenhouse gas emitter, has made deploying wind-generated electricity a cornerstone of long-term plans to mitigate climate change, air pollution and other energy-related environmental impacts. Following rapid expansion in recent years, especially in remote, less populous areas, wind has faced significant challenges integrating into the coal-heavy power grid owing to its fundamental operational differences compared to conventional energy sources. We present the first assessment of China’s wind energy potential and its regional distribution that incorporates an operational model of the grid and undertakes systematic exploration of key uncertainties.

Citation:

Davidson, M.R., D. Zhang, W. Xiong, X. Zhang & V.J. Karplus (2016): Modelling the potential for wind energy integration on China's coal-heavy electricity grid. Nature Energy, 1: Article #16086 (http://www.nature.com/articles/nenergy201686)
  • Joint Program Reprint
  • Journal Article
China Project
Modelling the potential for wind energy integration on China's coal-heavy electricity grid

Davidson, M.R., D. Zhang, W. Xiong, X. Zhang & V.J. Karplus

2016-14
1: Article #16086

Abstract/Summary: 

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.

China, the world’s largest energy consumer and greenhouse gas emitter, has made deploying wind-generated electricity a cornerstone of long-term plans to mitigate climate change, air pollution and other energy-related environmental impacts. Following rapid expansion in recent years, especially in remote, less populous areas, wind has faced significant challenges integrating into the coal-heavy power grid owing to its fundamental operational differences compared to conventional energy sources. We present the first assessment of China’s wind energy potential and its regional distribution that incorporates an operational model of the grid and undertakes systematic exploration of key uncertainties.