Wu, X., Wang, M. and Lee, K.Y. (2020) Flexible operation of supercritical coal-fired power plant integrated with solvent-based CO2 capture through collaborative predictive control. Energy, 206. 118105. ISSN 0360-5442
Abstract
This paper presents a controller design study for the supercritical coal fired power plant (CFPP) integrated with solvent-based post-combustion CO2 capture (PCC) system. The focus of the study is on the steam drawn-off from turbine to the re-boiler, which is the key interaction between the CFPP and PCC plants. The simulation study of a 660 MW supercritical CFPP-PCC unit model has shown that the impact of re-boiler steam change on the power generation of CFPP is more than 100 times faster than that on the PCC operation. Considering this finding, a collaborative predictive control strategy is proposed for the CFPP-PCC system where the re-boiler steam flowrate is manipulated for the CFPP load ramping and then gradually set to the required value for CO2 capture. The PCC is thereby exploited as an energy storage device, which can quickly store/release extra energy for the CFPP in addition to the primary function of carbon emission reduction. The simulation results show that the proposed collaborative predictive controller can effectively improve the load ramping performance of CFPP without much performance degradation on the PCC operation.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2020 Elsevier Ltd. This is an author produced version of a paper subsequently published in Energy. Uploaded in accordance with the publisher's self-archiving policy. Article available under the terms of the CC-BY-NC-ND licence (https://creativecommons.org/licenses/by-nc-nd/4.0/). |
Keywords: | Supercritical coal-fired power plant; Solvent-based post-combustion carbon capture; Transient performance analysis; Flexible operation; Collaborative operation; Model predictve control |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Chemical and Biological Engineering (Sheffield) |
Funding Information: | Funder Grant number ROYAL SOCIETY NIF\R1\181257 |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 08 Jul 2020 13:32 |
Last Modified: | 20 Jun 2021 00:38 |
Status: | Published |
Publisher: | Elsevier BV |
Refereed: | Yes |
Identification Number: | 10.1016/j.energy.2020.118105 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:163031 |
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Filename: 2020_06_04_XiaoWu_Collaborative_Control_CFPP_PCC_R1_V2.pdf
Licence: CC-BY-NC-ND 4.0