LAPSE:2023.20229
Published Article
LAPSE:2023.20229
Scheduling Optimization of IEHS with Uncertainty of Wind Power and Operation Mode of CCP
Yuxing Liu, Linjun Zeng, Jie Zeng, Zhenyi Yang, Na Li, Yuxin Li
March 17, 2023
With the gradual depletion of fossil energy sources and the improvement in environmental protection attention, efficient use of energy and reduction in carbon emissions have become urgent issues. The integrated electricity and heating energy system (IEHS) is a significant solution to reduce the proportion of fossil fuel and carbon emissions. In this paper, a stochastic optimization model of the IEHS considering the uncertainty of wind power (WP) output and carbon capture power plants (CCPs) is proposed. The WP output in the IEHS is represented by stochastic scenarios, and the scenarios are reduced by fast scenario reduction to obtain typical scenarios. Then, the conventional thermal power plants are modified with CCPs, and the CCPs are equipped with flue gas bypass systems and solution storage to form the integrated and flexible operation mode of CCPs. Furthermore, based on the different load demand responses (DRs) in the IEHS, the optimization model of the IEHS with a CCP is constructed. Finally, the results show that with the proposed optimization model and shunt-type CCP, the integrated operation approach allows for a better reduction in carbon capture costs and carbon emissions.
Keywords
carbon capture power plant, integrated electricity and heating energy system, Optimization, uncertainty
Suggested Citation
Liu Y, Zeng L, Zeng J, Yang Z, Li N, Li Y. Scheduling Optimization of IEHS with Uncertainty of Wind Power and Operation Mode of CCP. (2023). LAPSE:2023.20229
Author Affiliations
Liu Y: College of Electrical and Information Engineering, Hunan University, Changsha 410082, China [ORCID]
Zeng L: School of Energy and Power Engineering, Changsha University of Science and Technology, Changsha 410114, China
Zeng J: State Grid Hunan Electric Power Corporation Limited Loudi Power Supply Company, Loudi 417000, China
Yang Z: State Grid Hunan Electric Power Corporation Limited Loudi Power Supply Company, Loudi 417000, China
Li N: State Grid Hunan Electric Power Corporation Limited Loudi Power Supply Company, Loudi 417000, China
Li Y: Department of Electricity Supply Services, Changsha Electric Power Technical College, Changsha 410131, China
Journal Name
Energies
Volume
16
Issue
5
First Page
2157
Year
2023
Publication Date
2023-02-23
Published Version
ISSN
1996-1073
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PII: en16052157, Publication Type: Journal Article
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LAPSE:2023.20229
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doi:10.3390/en16052157
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Mar 17, 2023
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