Renewable and Low-Carbon Electric Power: Potentials, Grid Integration, and Environmental Effects

The Project developed a new assessment of wind power potentials in China, expressed as capacity factors of typical 1.5 MW wind turbines, screening out areas with unsuitable land uses and topography. The study appeared as the cover article of Science on September 11, 2009 (McElroy et al. 2009). This research is led by Project Chair Michael McElroy and research associate LU Xi. It takes advantage of NASA global assimilated meteorological datasets that have been validated by hundreds of studies of atmospheric chemistry and transport, and that drive the China Project's atmospheric model described here. A discussion of the study's implications appeared in MIT's Technology Review. It was also reported by China Daily, Associated Press, Reuters, Agence France-Presse, Bloomberg, Guardian, CBC, ClimateWire, Discovery, Public Radio International, and other sources (some requiring a subscription). 

A research article applying the methodology in a global wind assessment appeared in Proceedings of the National Academy of Sciences (Lu, McElroy, and Kiviluoma 2009), covered by Time Magazine, The Boston Globe, ABC News, The Telegraph, New Scientist, and National Public Radio. An introduction to this research, with application to the U.S., appeared in Harvard Magazine.

The team continued to exploit meteorological databases to develop new methodological approaches to the challenges of integrating large-scale wind power into energy systems of both China and the U.S. Lu, McElroy, and Sluzas (2011b) examines the costs and CO2 benefits of wind power deployment in the Texas electric power system. Lu et al. (2011a) evaluates the effect of the U.S. Production Tax Credit policy on profitability of wind power in the U.S., differentiated by geography. 

The researchers have also explored the shift to natural gas-fired power generation in the U.S. due to the shale gas revolution, investigating the effects of reduced gas prices on emissions of CO2 and conventional air pollutants in the U.S. in Lu et al. (2012a) and Lu et al. (2012b). This work laid groundwork for a study by Guo et al. (submitted, 2016) on prospects for shale gas development in China, focusing on constraints of water resources. 

The team has also applied insights from research on the U.S. power system in new research on China, joining with experts on China's electric grid led by KANG Chongqing of the Department of Electrical Engineering at Tsinghua University. Lu and McElroy led a study assessing the benefits of interconnecting offshore wind power deployments off the coast of China (Lu et al. 2013), and another study of the effects of offshore wind generation on coal use and carbon emissions (Lu et al. 2014). With visiting scholar CHEN Xinyu of Tsinghua, they assessed the prospects for using electrified space heating in Beijing as a form of energy storage, easing grid integration of renewable power and reducing carbon emissions and air pollution (Chen et al. 2014). Working with visiting scholar ZHANG Ning of Tsinghua, the team has also researched the benefits of coupling wind power generation with pumped hydro storage in Inner Mongolia (Zhang et al. in press, 2016). 

As both a Ph.D. student and postdoc, HUANG Junling has co-led with McElroy investigations of fundamental geophysical constraints and opportunities for wind power development in the U.S., China, and the world (Huang et al. 2014), including under climate change (Huang and McElroy 2014Huang and McElroy 2015aHuang and McElroy 2015b). 

More recently, Lu, now a professor at the School of Environment of Tsinghua University, has led with McElroy a Project study comparing causes of wind curtailment in the U.S. and China (Lu et al. submitted, 2016)Chen, graduated from Tsinghua and now returned to the China Project as a postdoc, is helping to take this research stream in new directions, including the potential role of electrified transportation fleets on grid integration of renewable power in China (Chen et al. submitted, 2016).

Acknowledgment: Some of the material summarized here is based on work supported by the National Science Foundation under Grants No. ATM-1019134 or ATM-0635548 (indicated by acknowledgments in the papers themselves). Any opinions, findings and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation (NSF).