Renewable and Low-Carbon Electric Power and Grid Integration

Led by Michael McELROY (Chair, Harvard-China Project), LU Xi (Tsinghua School of Environment), and postdoc CHEN Xinyu (Harvard-China Project), Project researchers have explored the status and prospects for renewable and low carbon electric power in China, including the challenges of and solutions to integration of variable renewable sources into an inflexible, coal-dominated power system.

From assessing wind power potentials using meteorological data and the geophysical constraints, to exploring energy storage and other strategies to ease grid integration of variable power sources, this research has deepened understanding of the role that expanding renewable power capacities can play in reducing emissions of air pollutants and carbon dioxide in China.

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Acknowledgment: Some of the papers cited here are 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).

Related Publications

Xi Lu, Liang Cao, Haikun Wang, Wei Peng, Jia Xing, Shuxiao Wang, Siyi Cai, Bo Shen, Qing Yang, Chris P. Nielsen, and Michael B. McElroy. 2019. “Gasification of coal and biomass as a net carbon-negative power source for environment-friendly electricity generation in China.” Proceedings of the National Academy of Sciences, 116, 17, Pp. 8206-8213. Publisher's Version Abstract

PNAS paper.pdf

Realizing the goal of the Paris Agreement to limit global warming to 2 °C by the end of this century will most likely require deployment of carbon-negative technologies. It is particularly important that China, as the world’s top carbon emitter, avoids being locked into carbon-intensive, coal-fired power-generation technologies and undertakes a smooth transition from high- to negative-carbon electricity production. We focus here on deploying a combination of coal and biomass energy to produce electricity in China using an integrated gasification cycle system combined with carbon capture and storage (CBECCS). Such a system will also reduce air pollutant emissions, thus contributing to China’s near-term goal of improving air quality. We evaluate the bus-bar electricity-generation prices for CBECCS with mixing ratios of crop residues varying from 0 to 100%, as well as associated costs for carbon mitigation and cobenefits for air quality. We find that CBECCS systems employing a crop residue ratio of 35% could produce electricity with net-zero life-cycle emissions of greenhouse gases, with a levelized cost of electricity of no more than 9.2 US cents per kilowatt hour. A carbon price of approximately $52.0 per ton would make CBECCS cost-competitive with pulverized coal power plants. Therefore, our results provide critical insights for designing a CBECCS strategy in China to harness near-term air-quality cobenefits while laying the foundation for achieving negative carbon emissions in the long run.

Qing Yang, Hewen Zhou, Pietro Bartocci, Francesco Fantozzi, Ondřej Mašek, Foster Agblevor, Zhiyu Wei, Haiping Yang, Hanping Chen, Xi Lu, Guoqian Chen, Chuguang Zheng, Chris Nielsen, and Michael McElroy. In Press. “Prospective contributions of biomass pyrolysis to China’s 2050 carbon reduction and renewable energy goals.” Nature Communications.

Jing Cao, Mun S Ho, and Rong Ma. In Press. “Analyzing Carbon Pricing Policies using a General Equilibrium Model with Production Parameters Estimated using Firm Data.” Energy Economics. Publisher's Version Abstract

Policy simulation results of Computable General Equilibrium (CGE) models largely hinge on the choices of substitution elasticities among key input factors. Currently, most CGE models rely on the common elasticities estimated from aggregated data, such as the GTAP model elasticity parameters. Using firm level data, we apply the control function method to estimate CES production functions with capital, labor and energy inputs and find significant heterogeneity in substitution elasticities across different industries. Our capital-labor substitution elasticities are much lower than the GTAP values while our energy elasticities are higher. We then incorporate these estimated elasticities into a CGE model to simulate China's carbon pricing policies and compare with the results using GTAP parameters. Our less elastic K-L substitution lead to lower base case GDP growth, but our more elastic energy substitution lead to lower coal use and carbon emissions. In the carbon tax policy exercises, we find that our elasticities lead to easier reductions in coal use and carbon emissions.

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Renewable and Low-Carbon Electric Power and Grid Integration

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