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. 

Click on "More Publications" below for a full list of publications supported by the Harvard-China Project in this research area.
 
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

Xingning Han, Xinyu Chen, Michael B. McElroy, Shiwu Liao, Chris P. Nielsen, and Jinyu Wen. 2019. “Modeling Formulation and Validation for Accelerated Simulation and Flexibility Assessment on Large Scale Power Systems under Higher Renewable Penetrations.” Applied Energy, 237, Pp. 145-154. Publisher's VersionAbstract
Deploying high penetration of variable renewables represents a critical pathway for decarbonizing the power sector. Hydro power (including pumped-hydro), batteries, and fast responding thermal units are essential in providing system flexibility at elevated renewable penetration. How to quantify the merit of flexibility from these sources in accommodating variable renewables, and to evaluate the operational costs considering system flexibility constraints have been central challenges for future power system planning. This paper presents an improved linear formulation of the unit commitment model adopting unit grouping techniques to expedite evaluation of the curtailment of renewables and operational costs for large-scale power systems. All decision variables in this formulation are continuous, and all chronological constraints are formulated subsequently. Tested based on actual data from a regional power system in China, the computational speed of the model is more than 20,000 times faster than the rigorous unit commitment model, with less than 1% difference in results. Hourly simulation for an entire year takes less than 3 min. The results demonstrate strong potential to apply the proposed model to long term planning related issues, such as flexibility assessment, wind curtailment analysis, and operational cost evaluation, which could set a methodological foundation for evaluating the optimal combination of wind, solar and hydro investments.
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