Economic Model Predictive Control for Post-Combustion CO2 Capture System Based on MEA
Economic Model Predictive Control for Post-Combustion CO2 Capture System Based on MEA
复制标题
基于MEA的燃烧后CO2捕集系统经济模型预测控制
DOI：
10.3390/en14238160
复制
发表时间：
2021-12
期刊：
影响因子：
3.2
通讯作者：
Chenbin Ma;Wenzhao Zhang;Yu Zheng;Aimin An
中科院分区：
文献类型：
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作者：
Chenbin Ma;Wenzhao Zhang;Yu Zheng;Aimin An
对于燃烧后CO2捕集（PCC）系统，经济性能的时变性是这种实际工业过程的生产过程的关键。然而，传统的模型预测控制（MPC）所采用的性能指标并不能反映生产过程的经济性，因此采用经济成本函数代替传统的性能指标来衡量生产过程的经济性。本文在白杨Plus Dynamics软件中建立了完整的PCC系统动态模型。通过动态测试验证了模型的有效性;利用实验数据进行子空间辨识，建立了烟气流量和贫溶剂流量之间的状态空间方程，得到了CO2捕集率;在Matlab/Simulink中建立了被控对象的动态模型和控制算法模型。在环保政策背景下，提出了一种经济模型预测控制（EMPC）策略，通过寻求经济性能的最优函数对PCC系统进行控制，保证系统在MPC控制策略的经济最优和优良品质下运行。仿真结果验证了该方法的有效性。
For the post-combustion CO2 capture (PCC) system, the time variability of the economic performance is key to the production process of such an actual industrial process. However, the performance index used by the conventional model predictive control (MPC) does not reflect the economy of the production process, so the economic cost function is used instead of the traditional performance index to measure the economy of the production process. In this paper, a complete dynamic model of the PCC system is constructed in Aspen Plus Dynamics. The effectiveness of the model is verified by dynamic testing; subspace identification is carried out using experimental data, a state-space equation between flue gas flow and lean solvent flow; the CO2 capture rate is obtained; and dynamic models and control algorithm models of accused objects are established in Matlab/Simulink. Under the background of the environmental protection policy, an economic model predictive control (EMPC) strategy is proposed to manipulate the PCC system through seeking the optimal function of the economic performance, and the system is guaranteed to operate under the economic optimal and excellent quality of the MPC control strategy. The simulation results verify the effectiveness of the proposed method.