Dynamic modelling and simulation of a post-combustion CO<sub>2</sub> capture process for coal-fired power plants

doi:10.1007/s11705-021-2057-7

Front. Chem. Sci. Eng.

2022, Vol. 16

Issue (2) : 198-209 https://doi.org/10.1007/s11705-021-2057-7

RESEARCH ARTICLE

Dynamic modelling and simulation of a post-combustion CO₂ capture process for coal-fired power plants

Jianlin Li, Ti Wang, Pei Liu(

), Zheng Li

State Key Lab of Power Systems, International Joint Laboratory on Low Carbon Clean Energy, Innovation, Department of Energy and Power Engineering, Tsinghua University, Beijing 100084, China

Download: PDF(1070 KB) HTML
Export: BibTeX | EndNote | Reference Manager | ProCite | RefWorks

Abstract

Solvent-based post-combustion capture technologies have great potential for CO₂ mitigation in traditional coal-fired power plants. Modelling and simulation provide a low-cost opportunity to evaluate performances and guide flexible operation. Composed by a series of partial differential equations, first-principle post-combustion capture models are computationally expensive, which limits their use in real time process simulation and control. In this study, we propose a first-principle approach to develop the basic structure of a reduced-order model and then the dominant factor is used to fit properties and simplify the chemical and physical process, based on which a universal and hybrid post-combustion capture model is established. Model output at steady state and trend at dynamic state are validated using experimental data obtained from the literature. Then, impacts of liquid-to-gas ratio, reboiler power, desorber pressure, tower height and their combination on the absorption and desorption effects are analyzed. Results indicate that tower height should be designed in conjunction with the flue gas flow, and the gas-liquid ratio can be optimized to reduce the reboiler power under a certain capture target.

Keywords CO₂ capture post-combustion capture simulation dominant factor

Corresponding Author(s): Pei Liu

Online First Date: 13 July 2021 Issue Date: 10 January 2022

Cite this article:

Jianlin Li,Ti Wang,Pei Liu, et al. Dynamic modelling and simulation of a post-combustion CO₂ capture process for coal-fired power plants[J]. Front. Chem. Sci. Eng., 2022, 16(2): 198-209.

URL:

https://academic.hep.com.cn/fcse/EN/10.1007/s11705-021-2057-7
https://academic.hep.com.cn/fcse/EN/Y2022/V16/I2/198

Fig.1 Structure of a chemical absorption system.

Tab.1 Parameters of the main chemical reaction for monoethanolamine to absorb CO₂

Fig.2 Fitting results of CO₂ mole fraction.

Fig.3 Fitting results of saturated vapor pressure of H₂O.

Tab.2 Input data for working conditions of experimental PCC plant

Fig.4 Steady state validation.

Fig.5 Dynamic changes of model capture rate (Star-up, sudden increase in smoke).

Fig.6 PCC performance under different amine solution flow. (a) CO₂ capture rate under different amine flow rates; (b) Temperature distribution inside absorber under four different amine flow rates.

Fig.7 Desorption under different reboiler power. (a) CO₂ removal efficiency inside desorber under different reboiler power; (b) CO₂ desorption distribution; (c) H₂O condensation distribution; (d) Temperature distribution inside desorber under four different reboiler power.

Fig.8 Desorption under different pressure. (a) CO₂ removal efficiency under different desorber pressure; (b) CO₂ desorption distribution; (c) H₂O condensation distribution; (d) Temperature distribution inside desorber under four different desorber pressure.

Fig.9 CO₂ capture rate under different tower heights and flow rates.

Fig.10 Working conditions (90% capture rate) under different parameters. (a) Reboiler power under different lean load (15 m); (b) amine flow rate under different lead load (15 m); (c) reboiler power under different lean load (10 m); (d) amine flow rate under different lead load (10 m).

1	D P Hanak, V Manovic. Linking renewables and fossil fuels with carbon capture via energy storage for a sustainable energy future. Frontiers of Chemical Science and Engineering, 2020, 14(3): 453–459 https://doi.org/10.1007/s11705-019-1892-2
2	K A Mumford, W U Yue, K H Smith, G W Stevens. Review of solvent-based carbon-dioxide capture technologies. Frontiers of Chemical Science and Engineering, 2015, 9(2): 125–141 https://doi.org/10.1007/s11705-015-1514-6
3	D Lew, G Brinkman, N Kumar, P Besuner, D D Agan, S Lefton. Impacts of wind and solar on emissions and wear and tear of fossil-fueled generators. In: 2012 IEEE Power and Energy Society General Meeting. San Diego: IEEE, 2012, 1–8
4	G D Guido, M Compagnoni, L A Pellegrini, H Rossetti. Mature versus emerging technologies for CO2 capture in power plants: Key open issues in post-combustion amine scrubbing and in chemical looping combustion. Frontiers of Chemical Science and Engineering, 2018, 12(2): 315–325 https://doi.org/10.1007/s11705-017-1698-z
5	T F Wall. Combustion processes for carbon capture. Proceedings of the Combustion Institute, 2007, 31(1): 31–47 https://doi.org/10.1016/j.proci.2006.08.123
6	S M Cohen, G T Rochelle, M E Webber. Optimal operation of flexible post-combustion CO2 capture in response to volatile electricity prices. Energy Procedia, 2011, 4: 2604–2611 https://doi.org/10.1016/j.egypro.2011.02.159
7	X Wu, M Wang, P Liao, J Shen, Y Li. Solvent-based post-combustion CO2 capture for power plants: a critical review and perspective on dynamic modelling, system identification, process control and flexible operation. Applied Energy, 2020, 257: 257–113941 https://doi.org/10.1016/j.apenergy.2019.113941
8	R E Treybal. Adiabatic gas absorption and stripping in packed towers. Industrial & Engineering Chemistry, 1969, 61(7): 36–41 https://doi.org/10.1021/ie50715a009
9	E Y Kenig, R Schneider, A Górak. Reactive absorption: optimal process design via optimal modelling. Chemical Engineering Science, 2001, 56(2): 343–350 https://doi.org/10.1016/S0009-2509(00)00234-7
10	H M Kvamsdal, J P Jakobsen, K A Hoff. Dynamic modeling and simulation of a CO2 absorber column for post-combustion CO2 capture. Chemical Engineering and Processing, 2009, 48(1): 135–144 https://doi.org/10.1016/j.cep.2008.03.002
11	S A Jayarathna, B Lie, M C Melaaen. Dynamic modelling of the absorber of a post-combustion CO2 capture plant: modelling and simulations. Computers & Chemical Engineering, 2013, 53: 178–189 https://doi.org/10.1016/j.compchemeng.2013.03.002
12	H M Kvamsdal, M Hillestad. Selection of model parameter correlations in a rate-based CO2 absorber model aimed for process simulation. International Journal of Greenhouse Gas Control, 2012, 11: 11–20 https://doi.org/10.1016/j.ijggc.2012.07.013
13	S A Jayarathna, B Lie, M C Melaaen. NEQ rate based modeling of an absorption column for post combustion CO2 capturing. Energy Procedia, 2011, 4(1): 1797–1804 https://doi.org/10.1016/j.egypro.2011.02.056
14	S Ziaii, G T Rochelle, T F Edgar. Dynamic modeling to minimize energy use for CO2 capture in power plants by aqueous monoethanolamine. Industrial & Engineering Chemistry Research, 2009, 48(13): 6105–6111 https://doi.org/10.1021/ie801385q
15	N Enaasen, A Tobiesen, H M Kvamsdal, M Hillestad. Dynamic modeling of the solvent regeneration part of a CO2 capture plant. Energy Procedia, 2013, 37(1): 2058–2065 https://doi.org/10.1016/j.egypro.2013.06.084
16	A Lawal, M Wang, P Stephenson, G Koumpouras, H Yeung. Dynamic modelling and analysis of post-combustion CO2 chemical absorption process for coal-fired power plants. Fuel, 2010, 89(10): 2791–2801 https://doi.org/10.1016/j.fuel.2010.05.030
17	S A Jayarathna, B Lie, M C Melaaen. Amine based CO2 capture plant: dynamic modeling and simulations. International Journal of Greenhouse Gas Control, 2013, 14(5): 282–290 https://doi.org/10.1016/j.ijggc.2013.01.028
18	K Wellner, T Marx-Schubach, G Schmitz. Dynamic behavior of coal-fired power plants with post combustion CO2 capture. Industrial & Engineering Chemistry Research, 2016, 55(46): 12038–12045 https://doi.org/10.1021/acs.iecr.6b02752
19	R Dutta, L O Nord, O Bolland. Selection and design of post-combustion CO2 capture process for 600 MW natural gas fueled thermal power plant based on operability. Energy, 2017, 121: 643–656 https://doi.org/10.1016/j.energy.2017.01.053
20	R M Montañés. S Ó GarÐarsdóttir, F Normann, F Johnsson, L O Nord. Demonstrating load-change transient performance of a commercial-scale natural gas combined cycle power plant with post-combustion CO2 capture. International Journal of Greenhouse Gas Control, 2017, 63: 158–174 https://doi.org/10.1016/j.ijggc.2017.05.011
21	X Wu, M Wang, J Shen, Y Li, A Lawal, K Y Lee. Reinforced coordinated control of coal-fired power plant retrofitted with solvent based CO2 capture using model predictive controls. Applied Energy, 2019, 238: 495–515 https://doi.org/10.1016/j.apenergy.2019.01.082
22	X He, F V Lima. Development and implementation of advanced control strategies for power plant cycling with carbon capture. Computers & Chemical Engineering, 2018, 121: 497–509 https://doi.org/10.1016/j.compchemeng.2018.11.004
23	Q Zhang, R Turton, D Bhattacharyya. Nonlinear model predictive control and H-infinity robust control for a post-combustion CO2 capture process. International Journal of Greenhouse Gas Control, 2019, 82: 138–151
24	C Madeddu, M Errico, R Baratti. Process analysis for the carbon dioxide chemical absorption-regeneration system. Applied Energy, 2018, 251: 532–542 https://doi.org/10.1016/j.apenergy.2018.02.033
25	Y L Moullec, T Neveux, A A Azki, A Chikukwa, K A Hoff. Process modifications for solvent-based post-combustion CO2 capture. International Journal of Greenhouse Gas Control, 2014, 31: 96–112 https://doi.org/10.1016/j.ijggc.2014.09.024
26	N M Dowell, N Shah. The multi-period optimisation of an amine-based CO2 capture process integrated with a super-critical coal-fired power station for flexible operation. Computers & Chemical Engineering, 2015, 74: 169–183 https://doi.org/10.1016/j.compchemeng.2015.01.006
27	N M Dowell, N Shah. Dynamic modelling and analysis of a coal-fired power plant integrated with a novel split-flow configuration post-combustion CO2 capture process. International Journal of Greenhouse Gas Control, 2014, 27: 103–119 https://doi.org/10.1016/j.ijggc.2014.05.007
28	J Gaspar, J B Jorgensen, P L Fosbol. Control of a post-combustion CO2 capture plant during process start-up and load variations. IFAC-PapersOnLine, 2015, 48(8): 580–585 https://doi.org/10.1016/j.ifacol.2015.09.030
29	T Marx-Schubach, G Schmitz. Modeling and simulation of the start-up process of coal fired power plants with post-combustion CO2 capture. International Journal of Greenhouse Gas Control, 2019, 87: 44–57 https://doi.org/10.1016/j.ijggc.2019.05.003
30	J Åkesson, C D Laird, G Lavedan, K Prölß, H Tummescheit, S Velut, Y Zhu. Nonlinear model predictive control of a CO2 post combustion absorption unit. Chemical Engineering & Technology, 2012, 35(3): 445–454 https://doi.org/10.1002/ceat.201100480
31	H Jin, P Liu, Z Li. Energy-efficient process intensification for post-combustion CO2 capture: a modeling approach. Energy, 2018, 158: 471–483 https://doi.org/10.1016/j.energy.2018.06.045
32	N Harun, T Nittaya, P L Douglas, E Croiset, L A Ricardez-Sandoval. Dynamic simulation of MEA absorption process for CO2 capture from power plants. International Journal of Greenhouse Gas Control, 2012, 10: 295–309 https://doi.org/10.1016/j.ijggc.2012.06.017
33	B H Lyu. Mass transfer-reaction mechanism of CO2 absorption in MEA/ionic liquid mixed aqueous solution. Dissertation for the Doctoral Degree. Zhejiang: Zhejiang University, 2014, 59–60
34	K Onda, H Takeuchi, Y Okumoto. Mass transfer coefficients between gas and liquid phases in packed columns. Journal of Chemical Engineering of Japan, 1968, 1(1): 56–62 https://doi.org/10.1252/jcej.1.56
35	P V Danckwerts, A Lannus. Gas-liquid reactions. Journal of the Electrochemical Society, 1970, 117(10): 369C https://doi.org/10.1149/1.2407312
36	N Ramachandran, A Aboudheir, R Idem, P Tontiwachwuthikul. Kinetics of the absorption of CO2 into mixed aqueous loaded solutions of monoethanolamine and methyldiethanolamine. Industrial & Engineering Chemistry Research, 2006, 45(8): 2608–2616 https://doi.org/10.1021/ie0505716
37	A K Saha, S S Bandyopadhyay, A K Biswas. Solubility and diffusivity of nitrous oxide and carbon dioxide in aqueous solutions of 2-amino-2-methyl-1-propanol. Journal of Chemical & Engineering Data, 1993, 38(1): 78–82 https://doi.org/10.1021/je00009a019
38	G F Versteeg, W P M Van Swaaij. Solubility and diffusivity of acid gases (carbon dioxide, nitrous oxide) in aqueous alkanolamine solutions. Journal of Chemical & Engineering Data, 1988, 33(1): 29–34 https://doi.org/10.1021/je00051a011
39	J J Ko, T C Tsai, C Y Lin, H M Wang, M H Li. Diffusivity of nitrous oxide in aqueous alkanolamine solutions. Journal of Chemical & Engineering Data, 2001, 46(1): 160–165 https://doi.org/10.1021/je000138x
40	T J Edwards, G Maurer, J Newman, J M Prausnitz. Vapor-liquid equilibria in multicomponent aqueous solutions of volatile weak electrolytes. AIChE Journal, 1978, 24(6): 966–976 https://doi.org/10.1002/aic.690240605
41	V E Bower, R A Robinson, R G Bates. Acidic dissociation constant and related thermodynamic quantities for diethanolammonium ion in water from 0 to 50 °C. Journal of Research of the National Bureau of Standards, 1962, 66(1): 71–75 https://doi.org/10.6028/jres.066A.008
42	H Li, J Chen. Thermodynamic model and process simulation of CO2 absorption by monoethanolamine. CIESC, 2014, 65(1): 47–54
43	J Gaspar, J B Jørgensen, P L Fosbøl. A dynamic mathematical model for packed columns in carbon capture plants. In: 2015 European Control Conference (ECC). Linz: IEEE, 2015, 2738–2743
44	G G Bemer , G A J Kalis . New calculation method of liquid holding capacity and pressure drop in packed tower. Guangxi Chemical Technology, 1979, 1979(2): 55–63
45	J Stichlmair, J L Bravo, J R Fair. General model for prediction of pressure drop and capacity of countercurrent gas/liquid packed columns. Gas Separation & Purification, 1989, 3(1): 19–28 https://doi.org/10.1016/0950-4214(89)80016-7
46	S A Jayarathna, B Lie, M C Melaaen. Development of a dynamic model of a post combustion CO2 capture process. Energy Procedia, 2013, 37: 1760–1769 https://doi.org/10.1016/j.egypro.2013.06.052

[1]	Nikolaus I. Vollmer, Resul Al, Krist V. Gernaey, Gürkan Sin. Synergistic optimization framework for the process synthesis and design of biorefineries[J]. Front. Chem. Sci. Eng., 2022, 16(2): 251-273.
[2]	Patrick Otto Ludl, Raoul Heese, Johannes Höller, Norbert Asprion, Michael Bortz. Using machine learning models to explore the solution space of large nonlinear systems underlying flowsheet simulations with constraints[J]. Front. Chem. Sci. Eng., 2022, 16(2): 183-197.
[3]	Linlin You, Yandong Guo, Yanjing He, Feng Huo, Shaojuan Zeng, Chunshan Li, Xiangping Zhang, Xiaochun Zhang. Molecular level understanding of CO₂ capture in ionic liquid/polyimide composite membrane[J]. Front. Chem. Sci. Eng., 2022, 16(2): 141-151.
[4]	Daohui Zhao, Huang Chen, Yuqing Wang, Bei Li, Chongxiong Duan, Zhixian Li, Libo Li. Molecular dynamics simulation on DNA translocating through MoS₂ nanopores with various structures[J]. Front. Chem. Sci. Eng., 2021, 15(4): 922-934.
[5]	Quan Liu, Mingqiang Chen, Yangyang Mao, Gongping Liu. Theoretical study on Janus graphene oxide membrane for water transport[J]. Front. Chem. Sci. Eng., 2021, 15(4): 913-921.
[6]	Sanaa Hafeez, Tayeba Safdar, Elena Pallari, George Manos, Elsa Aristodemou, Zhien Zhang, S. M. Al-Salem, Achilleas Constantinou. CO₂ capture using membrane contactors: a systematic literature review[J]. Front. Chem. Sci. Eng., 2021, 15(4): 720-754.
[7]	Zhihong Xu, Tao Jiang, Hao Zhang, Yujun Zhao, Xinbin Ma, Shengping Wang. Efficient MgO-doped CaO sorbent pellets for high temperature CO₂ capture[J]. Front. Chem. Sci. Eng., 2021, 15(3): 698-708.
[8]	Hong Li, Fang Yi, Xingang Li, Xin Gao. Numerical modeling of mass transfer processes coupling with reaction for the design of the ozone oxidation treatment of wastewater[J]. Front. Chem. Sci. Eng., 2021, 15(3): 602-614.
[9]	Gongkui Xiao, Penny Xiao, Andrew Hoadley, Paul Webley. Integrated adsorption and absorption process for post-combustion CO₂ capture[J]. Front. Chem. Sci. Eng., 2021, 15(3): 483-492.
[10]	Fernando F. Rivera, Berenice Miranda-Alcántara, Germán Orozco, Carlos Ponce de León, Luis F. Arenas. Pressure drop analysis on the positive half-cell of a cerium redox flow battery using computational fluid dynamics: mathematical and modelling aspects of porous media[J]. Front. Chem. Sci. Eng., 2021, 15(2): 399-409.
[11]	Chenkai Gu, Yang Liu, Weizhou Wang, Jing Liu, Jianbo Hu. Effects of functional groups for CO₂ capture using metal organic frameworks[J]. Front. Chem. Sci. Eng., 2021, 15(2): 437-449.
[12]	Lin Yang, Wenpeng Li, Junheng Guo, Wei Li, Baoguo Wang, Minqing Zhang, Jinli Zhang. Effects of rotor and stator geometry on dissolution process and power consumption in jet-flow high shear mixers[J]. Front. Chem. Sci. Eng., 2021, 15(2): 384-398.
[13]	Yujie Ban, Meng Zhao, Weishen Yang. Metal-organic framework-based CO₂ capture: from precise material design to high-efficiency membranes[J]. Front. Chem. Sci. Eng., 2020, 14(2): 188-215.
[14]	Ervin Saracevic, David Woess, Franz Theuretzbacher, Anton Friedl, Angela Miltner. Techno-economic assessment of providing control energy reserves with a biogas plant[J]. Front. Chem. Sci. Eng., 2018, 12(4): 763-771.
[15]	Ismael Matino, Valentina Colla, Teresa A. Branca. Extension of pilot tests of cyanide elimination by ozone from blast furnace gas washing water through Aspen Plus^® based model[J]. Front. Chem. Sci. Eng., 2018, 12(4): 718-730.

Viewed

Full text

Abstract

Cited

Shared

Discussed