燃烧后CO2捕集系统的复合无模型自适应控制

doi:10.3969/j.issn.2097-0706.2024.09.001

摘要/Abstract

摘要：

燃烧后CO₂捕集（PCC）系统作为一种有效的碳减排技术，其优化控制对提高CO₂捕集效率和降低能耗具有重要意义。针对PCC系统的控制问题，提出一种复合无模型自适应控制（MFAC）方法，旨在解决传统控制方法依赖精确模型、难以适应系统参数变化和不确定性的问题。该方法将扩张状态观测器引入MFAC中，利用扩张状态观测器估计系统总扰动，提高系统的跟踪和抗干扰能力。进行不同控制方案下的PCC系统对比仿真，其中，在跟踪CO₂捕集率设定值的仿真中，复合MFAC展现出了良好的跟踪性能，上升时间95.69 s，比传统的MFAC快4.65 s，较比例-积分-微分（PID）控制快78.02 s。在抗扰性能的对比仿真中，复合MFAC在受到扰动时所产生的偏差最小，绝对误差积分和平方误差积分的数值均小于MFAC和PID控制器，具有良好的抗干扰能力。仿真验证了所提出控制方案的有效性和适用性。

关键词: 燃烧后CO₂捕集, 扩张状态观测器, 无模型自适应控制, 控制性能

Abstract:

Post-combustion carbon capture （PCC） systems， as effective carbon reduction devices， are important for enhancing CO₂ capture efficiency and reducing energy consumption. To address control issues of PCC systems， a novel composite model-free adaptive control （MFAC）method is proposed，aiming for overcoming the reliance on precise models and the difficulties in adapting to varying parameters and uncertainties encountered by traditional methods. Composite MFAC integrates an extended state observer to estimate total system disturbances， improving systems' tracking and disturbance rejection capabilities. Comparative simulations on different control methods of PCC systems were conducted. In simulations for tracking CO₂ capture rate setpoints， composite MFAC demonstrated excellent tracking capability， whose acceleration time was only 95.69 s， which was 4.65 s faster than that of traditional MFAC and 78.02 s faster than that of PID control. In simulations for evaluating disturbance rejection performances， the composite MFAC exhibited the minimal deviation， smallest integral absolute error （IAE） and integral square error （ISE） among the three control methods， demonstrating a robust disturbance rejection capability. Simulation results validate the effectiveness and applicability of the proposed control approach.

Key words: post-combustion CO₂ capture, extended state observer, model-free adaptive control, control performance

中图分类号:

TK019：TP273

贾冰珂, 李紫豪, 吴振龙, 刘艳红. 燃烧后CO₂捕集系统的复合无模型自适应控制[J]. 综合智慧能源, 2024, 46(9): 1-8.

JIA Bingke, LI Zihao, WU Zhenlong, LIU Yanhong. Composite model-free adaptive control of a post-combustion CO₂ capture system[J]. Integrated Intelligent Energy, 2024, 46(9): 1-8.

图/表 10

图1

图2

图3

表1

不同控制器参数

控制器	参数
PID	$k p = 14.25, k i = 0.5$
MFAC	$η = 0.35, μ = 1, ρ = 0.75, 0, 0 T, λ = 25$
MFAC-ESO	$η = 0.35, μ = 1, ρ = 0.75, 0, 0 T, λ = 25, b 0 = 0.000 3, ω o = 0.8, α = 55 000$

表1

图4

图5

表2

图6

图7

表3

参考文献 35

[1]	李敏霞, 侯焙然, 王派, 等. 二氧化碳跨临界循环热泵的应用与发展[J]. 综合智慧能源, 2023, 45(4): 12-18. doi: 10.3969/j.issn.2097-0706.2023.04.002
	LI Minxia, HOU Beiran, WANG Pai, et al. Application and development of CO₂ transcritical cycle heat pumps[J]. Integrated Intelligent Energy, 2023, 45(4): 12-18. doi: 10.3969/j.issn.2097-0706.2023.04.002
[2]	习近平在第七十五届联合国大会一般性辩论上的讲话[EB/OL].(2020-09-22)[2024-03-17]. http://www.cppcc.gov.cn/zxww/2020/09/23/ARTI1600819264410115.shtml?from=groupmessage.
[3]	Global CCS Institute. The global status of CCS: 2018[R]. Melbourne, Australia: Global CCS Institute, 2018.
[4]	UNFCCC. Historic Paris agreement on climate change[EB/OL].(2015-12-13)[2024-06-17]. https://unfccc.int/news/finale-cop21.
[5]	LIN Q Y, ZHANG X, WANG T, et al. Technical perspective of carbon capture, utilization, and storage[J]. Engineering, 2022, 14: 27-32.
[6]	CUI Q R, ZHAO R, WANG T K, et al. A 150 000 t·a^-1 post-combustion carbon capture and storage demonstration project for coal-fired power plants[J]. Engineering, 2022, 14: 22-26.
[7]	温翯, 韩伟, 车春霞, 等. 燃烧后二氧化碳捕集技术与应用进展[J]. 精细化工, 2022, 39(8): 1584-1595.
	WEN He, HAN Wei, CHE Chunxia, et al. Progress of post-combustion carbon dioxide capture technology development and applications[J]. Fine Chemicals, 2022, 39(8): 1584-1595.
[8]	胡长征, 王雅博, 刘圣春. MEA溶液在生物质电厂和燃煤电厂捕集CO₂中的应用对比[J]. 综合智慧能源, 2022, 44(6): 78-85. doi: 10.3969/j.issn.2097-0706.2022.06.009
	HU Changzheng, WANG Yabo, LIU Shengchun. Application of MEA solution in the CO₂ capture in biomass power plants and coal-fired power plants[J]. Integrated Intelligent Energy, 2022, 44(6): 78-85. doi: 10.3969/j.issn.2097-0706.2022.06.009
[9]	BUI M, GUNAWAN I, VERHEYEN V, et al. Flexible operation of CSIRO's post-combustion CO₂ capture pilot plant at the AGL Loy Yang power station[J]. International Journal of Greenhouse Gas Control, 2016, 48: 188-203.
[10]	MECHLERI E, LAWAL A, RAMOS A, et al. Process control strategies for flexible operation of post-combustion CO₂capture plants[J]. International Journal of Greenhouse Gas Control, 2017, 57: 14-25.
[11]	MANAF N A, COUSINS A, FERON P, et al. Dynamic modelling, identification and preliminary control analysis of an amine-based post-combustion CO₂ capture pilot plant[J]. Journal of Cleaner Production, 2016, 113: 635-653.
[12]	LAWAL A, WANG M, STEPHENSON P, et al. Dynamic modelling of CO₂ absorption for post combustion capture in coal-fired power plants[J]. Fuel, 2009, 88(12): 2455-2462.
[13]	SCHNEIDER R, KENIG E Y, GÓRAK A. Dynamic modelling of reactive absorption with the Maxwell-Stefan approach[J]. Chemical Engineering Research and Design, 1999, 77(7): 633-638.
[14]	NOERES C, KENIG E Y, GÓRAK A. Modelling of reactive separation processes: reactive absorption and reactive distillation[J]. Chemical Engineering and Processing:Process Intensification, 2003, 42(3):157-178.
[15]	SULTAN T, ZABIRI H, SHAHBAZ M, et al. Model analysis for the implementation of a fast model predictive control scheme on the absorption/stripping CO₂ capture plants[J]. ACS Omega, 2022, 7: 8437-8455.
[16]	ZHANG W Z, MA C B, LI H F, et al. DMC-PID cascade control for MEA-based post-combustion CO₂ capture process[J]. Chemical Engineering Research and Design, 2022, 182: 701-713.
[17]	MORES P, SCENNA N, MUSSATI S. Post-combustion CO₂ capture process: Equilibrium stage mathematical model of the chemical absorption of CO₂ into monoethanolamine (MEA) aqueous solution[J]. Chemical Engineering Research and Design, 2011, 89(9):1587-1599.
[18]	KENIG E Y, SCHNEIDER R, GORAK A. Rigorous dynamic modelling of complex reactive absorption processes[J]. Chemical Engineering Science, 1999, 54: 5195-5203.
[19]	LAWAL A, WANG M, STEPHENSON P, et al. Dynamic modelling and analysis of post-combustion CO₂ chemical absorption process for coal-fired power plants[J]. Fuel, 2010, 89: 2791-2801.
[20]	WU X, WANG M L, LIAO P Z, et al. Solvent-based post-combustion CO₂ capture for power plants: A critical review and perspective on dynamic modelling, system identification, process control and flexible operation[J]. Applied Energy, 2020, 257(1): 113941.
[21]	ROBINSON P J, LUYBEN W L. Integrated gasification combined cycle dynamic model: H₂S absorption/stripping, water-gas shift reactors, and CO₂ absorption/stripping[J]. Industrial & Engineering Chemistry Research, 2010, 49: 4766-4781.
[22]	NITTAYA T, DOUGLAS P L, CROISET E, et al. Dynamic modelling and evaluation of an industrial-scale CO₂ capture plant using monoethanolamine absorption processes[J]. Industrial & Engineering Chemistry Research, 2014, 53: 11411-11426.
[23]	MEJDELL T, KVAMSDAL H M, HAUGER S O, et al. Demonstration of non-linear model predictive control for optimal flexible operation of a CO₂ capture plant[J]. International Journal of Greenhouse Gas Control, 2022, 117: 103645.
[24]	LIAO P Z, LI Y G, WU X, et al. Flexible operation of large-scale coal-fired power plant integrated with solvent-based post-combustion CO₂ capture based on neural network inverse control[J]. International Journal of Greenhouse Gas Control, 2020, 95: 102985.
[25]	WU X, SHEN J, WANG M L, et al. Intelligent predictive control of large-scale solvent-based CO₂ capture plant using artificial neural network and particle swarm optimization[J]. Energy, 2020, 196: 117070.
[26]	ZHANG W Z, MA C B, LI H F, et al. DMC-PID cascade control for MEA-based post-combustion CO₂ capture process[J]. Chemical Engineering Research and Design, 2022, 182: 701-713.
[27]	唐炜洁, 沈炯, 吴啸, 等. 化学吸附燃烧后CO₂捕集系统前馈优化控制[J]. 工程热物理学报, 2019, 40(9): 1969-1975.
	TANG Weijie, SHEN Jiong, WU Xiao, et al. Feedforward optimization control of post-combustion CO₂ capture system[J]. Journal of Engineering Thermophysics, 2019, 40(9): 1969-1975.
[28]	侯忠生, 金尚泰. 无模型自适应控制——理论与应用[M]. 北京: 科学出版社, 2013.
[29]	IPCC. Intergovernmental panel on climate change (IPCC) special report on carbon dioxide capture and storage[R]. Cambridge, UK: Cambridge University Press, 2005.
[30]	李伟斌, 陈健. 乙醇胺溶液吸收 CO₂动力学实验研究[J]. 中国科技论文在线, 2009., 4(12):849-854.
	LI Weibin, CHEN Jian. Kinetics of absorption of CO₂ into aqueous MEA solutions[J]. Sciencepaper Online, 2009, 4(12):849-854.
[31]	李朋真, 贾冰珂, 刘艳红, 等. 燃烧后二氧化碳捕集系统的改进自抗扰控制[J]. 综合智慧能源, 2023, 45(8):18-25. doi: 10.3969/j.issn.2097-0706.2023.08.003
	LI Pengzhen, JIA Bingke, LIU Yanhong, et al. Modified active disturbance rejection control on the post-combustion CO₂ capture system[J]. Integrated Intelligent Energy, 2023, 45(8): 18-25. doi: 10.3969/j.issn.2097-0706.2023.08.003
[32]	HAN J Q. From PID to active disturbance rejection control[J]. IEEE Transactions on Industrial Electronics, 2009, 56(3):900-906.
[33]	GAO Z Q. Scaling and bandwidth-parameterization based controller tuning[C]// Proceedings of the 2003 American Control Conference, Denver, 2003: 4989-4996.
[34]	HOU Z S, JIN S T. A novel data-driven control approach for a class of discrete-time nonlinear systems[J]. IEEE Transactions on Control Systems Technology, 2011, 19(6): 1549-1558.
[35]	李朋真, 刘艳红, 吴振龙. 高比例可再生能源的多区域电力系统负荷频率自抗扰控制[J]. 综合智慧能源, 2022, 44(10): 33-41. doi: 10.3969/j.issn.2097-0706.2022.10.005
	LI Pengzhen, LIU Yanhong, WU Zhenlong. Active disturbance rejection control on load frequency of multi-area power systems with high-proportion renewable energy[J]. Integrated Intelligent Energy, 2022, 44(10): 33-41. doi: 10.3969/j.issn.2097-0706.2022.10.005

控制器	上升时间/s	IAE	ISE
PID	173.71	75 872.5	104 098.5
MFAC	100.34	66 446.3	108 219.1
MFAC-ESO	95.69	65 787.7	98 349.7

燃烧后CO₂捕集系统的复合无模型自适应控制

Composite model-free adaptive control of a post-combustion CO₂ capture system

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控制器	IAE	ISE
PID	49 998.9	46 305.0
MFAC	37 945.4	24 829.7
MFAC-ESO	34 348.8	20 389.4