Owing to the continued use of fossil fuels in the global energy system for the foreseeable future, the International Energy Agency (IEA) suggests that CCS is an essential part of the technology portfolio needed to achieve deep reductions in global CO2 emissions, with CCS expected to contribute around 14-20 % of total reductions in emissions by 2050 (IEA, 2010), (IPCC, 2014).
Nowadays, existing and new power plants must face the challenges of the liberalised electricity market, predictability issues regarding renewable sources and the requirement to cover intermediate and peak load constraints, to be able to respond to the variation of the electricity demand. The integration of power plants with capture plants will increase the need to develop advanced model-based control systems that are able to maintain the dynamic operability of CO2 capture plants in the presence of operational constraints and disturbances.
One of the most promising near-term options for large-scale CCS deployment is post-combustion capture of with a monoethanolamine-type solvents. The benefits of this process are high capacity of CO2 capture, fast reaction kinetics, inexpensive and abundant solvent. On the other hand the main challenge with this process is the substantial decrease in the efficiency of the power plant owing to the energy required for solvent regeneration that would otherwise be used to produce electricity. Further, as the power plant ramps up and down, the variation in liquid-to-gas ratios in the absorption columns can impose an important effect on the efficiency of the capture plant. Therefore the dynamic modelling and controllability analysis of the complete capture process is quite important (Bui et al., 2014).
In this paper we are going to discuss the flexibility in terms of different operating procedures of the coal power plant, and present the design and application of an advanced Model Predictive Control (MPC) approach to evaluate the controllability of a post-combustion plant in the presence of disturbances associated with the dynamic operation of the power plant. The outcome from this study is essential for future research to develop a control system for the CO2 capture process and to develop new operability policies that will enable the safe and optimum dynamic operation of the MEA absorption process.
In literature, many papers discuss about “flexible” scenarios in the integration of a coal fired power plant with a capture plant (Chalmers et al., 2009), for example bypassing the capture in times with high electricity demand. However, a continuous process such as the amine scrubbing and regeneration process commonly used in CCS cannot be shut down and turned on at will. There must be limits to flexibility constrained by design, operation and control of the CCS plant. It needs to be recognized that when flue gas bypasses the CO2 capture plant, hydraulics conditions of the absorber and the stripper will change substantially. A column will operate normally only when the gas flow velocity and liquid gas ratio are within range (Kister, 1992). It was also suggested that rich solvent can be stored during peak load period and can be regenerated later in off-peak period. This strategy could avoid CO2 emission penalty because CO2 is captured all the time. However, this strategy requires huge additional tanks and solvent inventory for buffering between peak and off-peak load period (Haines et al., 2009).
The implementation of the MPC approach addressed in this work can achieve the flexible operation of the power plant with the capture plant. The reason of choosing the centralised MPC is because it provides better performance, in terms of close-loop settling time, integral square error and compliance of operational and environmental constraints than the PI control schemes when applied in a post-combustion CO2 capture process. The model was developed in gCCS a system modelling tool for support of design and operating decisions across the CCS chain. gCCS is built on PSE’s gPROMS advanced process modelling platform, and inherits many of the platform’s powerful capabilities (gCCS overview, 2014). SAFT-VR was used to describe the effect of the reactions on the fluid-phase properties and phase behaviour of the MEA-H2O-CO2-N2 fluid mixture in the CO2 capture process and the thermodynamic properties of the fluids (Mac Dowell et. al, 2013). The main control objective of this plant is to maintain the CO2 removal fixed at a specified rate and maintain a constant composition in the CO2 product stream. Also the liquid levels in the absorber sump and reboiler are controlled in order to maintain the solvent inventory within the system. Further the MEA concentration in the lean solvent stream needs to be below 30wt % to minimise corrosion in the equipment. The lean amine flowrate, condenser heat duty, absorber valve, reboiler valve and reboiler heat duty were selected as manipulated variables respectively.
The MPC controller as presented above, was evaluated under several scenarios, including changes in the flue gas flowrate that comes from the power plant and in the percentage of CO2 captured in order to evaluate the amount of steam extracted from the thermodynamic cycle of the power plant during periods of high electricity demand. The results showed that the MPC control strategy can quickly adapt to any disturbance applied to the capture plant, which is essential for the profitable operation of decarbonised power plants.
Bui M., Gunawan I., Verheyen V., Feron P., Meuleman E., Adeloju S., 2014, Dynamic Modelling and optimisation of flexible operation in post-combustion CO2 capture plants - A review, Computers & Chemical Engineering, 61, 245-265.
Chalmers H, Lucquiaud M, Gibbins J, Leach M. Flexible operation of coal fired power plants with post-combustion capture of carbon dioxide. Journal of Environmental Engineering. 2009; 135:449–458.
gCCS overview: http://www.pseenterprise.com/power/ccs/gccs.html.
Haines MR, Davison JE. Designing carbon capture power plants to assist in meeting peak power demand. Energy Procedia. 2009; 1:1457–1464.
International Energy Agency, 2010, Carbon Capture and Storage, Model Regulatory Framework.
IPCC, 5th Assessment Report, Working Group III, 2014.
Kister HZ. Distillation design. New York: McGraw-Hill, 1992.
Mac Dowell N., Samsatli N., Shah N., 2013, Dynamic modelling and analysis of an amine-based post-combustion CO2 capture absorption column, International Journal of Greenhouse Gas Control, 12, 247-258.