IGCC Power Plant Dispatch Using Infinite-Horizon Economic Model Predictive Control

2013 ◽  
Vol 52 (9) ◽  
pp. 3151-3164 ◽  
Author(s):  
Benjamin P. Omell ◽  
Donald J. Chmielewski
Keyword(s):  
Power Plant ◽  
Model Predictive Control ◽  
Predictive Control ◽  
Economic Model ◽  
Infinite Horizon ◽  
Economic Model Predictive Control ◽  
Igcc Power Plant

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.

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