On closed-loop economic performance under Lyapunov-based economic model predictive control

2016 ◽  
Author(s):  
Matthew Ellis ◽  
Panagiotis D. Christofides
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Economic Performance ◽  
Economic Model ◽  
Closed Loop ◽  
Economic Model Predictive Control

scholarly journals Improving Flexibility and Energy Efficiency of Post-Combustion CO2 Capture Plants Using Economic Model Predictive Control

Processes ◽  
2018 ◽  
Vol 6 (9) ◽  
pp. 135 ◽  
Author(s):  
Benjamin Decardi-Nelson ◽  
Su Liu ◽  
Jinfeng Liu
Keyword(s):  
Energy Efficiency ◽  
Power Plant ◽  
Model Predictive Control ◽  
Predictive Control ◽  
Economic Performance ◽  
Economic Model ◽  
Power Plants ◽  
Gas Flow ◽  
Renewable Energy Sources ◽  
Economic Model Predictive Control

To reduce CO 2 emissions from power plants, electricity companies have diversified their generation sources. Fossil fuels, however, still remain an integral energy generation source as they are more reliable compared to the renewable energy sources. This diversification as well as changing electricity demand could hinder effective economical operation of an amine-based post-combustion CO 2 capture (PCC) plant attached to the power plant to reduce CO 2 emissions. This is as a result of large fluctuations in the flue gas flow rate and unavailability of steam from the power plant. To tackle this problem, efficient control algorithms are necessary. In this work, tracking and economic model predictive controllers are applied to a PCC plant and their economic performance is compared under different scenarios. The results show that economic model predictive control has a potential to improve the economic performance and energy efficiency of the amine-based PCC process up to 6% and 7%, respectively, over conventional model predictive control.

scholarly journals Economic Model Predictive Control for Post-Combustion CO2 Capture System Based on MEA

Energies ◽  
2021 ◽  
Vol 14 (23) ◽  
pp. 8160
Author(s):  
Chenbin Ma ◽  
Wenzhao Zhang ◽  
Yu Zheng ◽  
Aimin An
Keyword(s):  
Model Predictive Control ◽  
Production Process ◽  
Predictive Control ◽  
Co2 Capture ◽  
Economic Performance ◽  
Economic Model ◽  
Performance Index ◽  
Dynamic Models ◽  
Capture Rate ◽  
Economic Model Predictive Control

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.

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