Carbon capture power plant scheduling based on information gap decision theory

doi:10.16511/j.cnki.qhdxxb.2022.26.008

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Abstract As one of the most promising carbon reduction methods, solvent-based post-combustion carbon capture is expected to provide clean use of fossil fuels. Low-carbon coal-fired power plants with carbon capture scheduling can significantly advance the goal of "carbon neutrality". However, few studies have considered the impact of electricity price fluctuations and electricity consumption changes on power plant coupled with carbon capture device. This study integrated the characteristics of power plants and their carbon capture into an information gap decision theory (IGDT) model to analyze the uncertainties in the combined system. A deterministic scheduling model for the integrated power plant and carbon capture device was used with IGDT to describe the load demand uncertainty in the real-time market. Two certainty scheduling models were developed based on the users risk adverse attitude with the optimized scheduling decision based on either robustness or opportunity. The scheduling schemes of integrated power plant and carbon capture device with these two risk attitudes were used for a case study to demonstrate the reliability and effectiveness of the model.

Keywords carbon capture system power plant optimized scheduling information gap decision theory risk decision

Issue Date: 18 August 2022

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	YU Xuefei
	ZHANG Shuai
	LIU Linlin
	DU Jian

Cite this article:

YU Xuefei,ZHANG Shuai,LIU Linlin, et al. Carbon capture power plant scheduling based on information gap decision theory[J]. Journal of Tsinghua University(Science and Technology), 2022, 62(9): 1467-1473.

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http://jst.tsinghuajournals.com/EN/10.16511/j.cnki.qhdxxb.2022.26.008 OR http://jst.tsinghuajournals.com/EN/Y2022/V62/I9/1467

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