Plantwide Control of CO2 Capture by Absorption and Stripping Using

Nov 30, 2010 - Flexible operation and simultaneous scheduling and control of a CO2 capture plant using model predictive control. Zhenrong He , M. Hoss...
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Ind. Eng. Chem. Res. 2011, 50, 1338–1345

Plantwide Control of CO2 Capture by Absorption and Stripping Using Monoethanolamine Solution Yu-Jeng Lin,† Tian-Hong Pan,‡ David Shan-Hill Wong,*,† Shi-Shang Jang,*,† Yu-Wen Chi,† and Chia-Hao Yeh† Department of Chemical Engineering, National Tsing-Hua UniVersity, Hsin-Chu 30013, Taiwan and School of Electrical and Information Engineering, Jiangsu UniVersity, Zhenjiang, Jiangsu, 212013, People’s Republic of China

In this work, plantwide control of an absorption/stripping CO2 capture process using monoethanol-amine was investigated using dynamic simulation. In this system, CO2 removal ratio is influenced by operating variables such as lean solvent rate and lean solvent loading, which is in-turn determined by reboiler duty in the stripper. Moreover, we found that the long-term stability of the system cannot be achieved unless the water balance is properly maintained. Hence the following control structure was proposed. In this scheme, the CO2 removal target is guaranteed using the lean solvent feed rate to the top of the absorber column. The overall water inventory was maintained by controlling the liquid level in the reboiler of the stripping column using makeup water. In order to operate the process with an appropriate lean solvent loading, the temperature at the bottom of stripper is controlled by the reboiler duty. This control structure was tested by disturbances involving inlet flue gas flow, CO2 concentrations, and H2O concentrations as well as changes in removal targets. Dynamic simulations showed that the system can achieve removal targets and stabilize quickly while keeping optimum lean loading constant. To ensure minimum energy consumption, optimizing control can be carried out by adjusting the set point of the reboiler temperature. 1. Introduction Over the past few decades, anthropogenic carbon emission has been recognized as an important contributing factor to global warming and climate change. Therefore, carbon dioxide capture, sequestration, and utilization has become a new focus of chemical process technology research. Flue gas from coal-fired power plants is the main source of CO2 emissions.1 In order to capture and separate CO2 effectively, several types of technologies have been developed.2-4 Among these methods, the absorption/stripping CO2 capture system is considered the most feasible method to deal with flue gas from power plants.5 Compared with other capture processes, the absorption/stripping process offers higher capture efficiency and lower energy consumption. The standard absorption/stripping process mainly consists of two columns and a heat exchanger as shown in Figure 1. Flue gas carrying CO2 from power plants is delivered into the bottom of a packed absorber to contact with the lean solvent, 30 wt % MEA is widely used as the absorbent in the absorption/stripping process. Treated gas is vented to the atmosphere from the top of the absorber. After absorption, the rich solvent is sent to a stripper with a reboiler to reproduce the MEA solvent. Hot lean solvent out from the stripper is reused after being cooled by a heat exchanger and cooler. The heat duty of the reboiler in the stripping column is the main energy consumption of this capture process. Several publications6-10 provided optimum operating conditions via steady state simulation. Alie et al.8 developed an integrated model by Aspen Plus. Several system parameters have been varied including flue gas CO2 concentration, monoethanol-amine (MEA) concentration, lean solvent loading, and rich solvent temperature to find the lowest reboiler duty settings. The optimum lean loading was found to be 0.25 mol CO2/mol MEA * To whom correspondence should be addressed. E-mail: dshwong@ che.nthu.edu.tw; [email protected]. † Department of Chemical Engineering, National Tsing-Hua University. ‡ School of Electrical and Information Engineering, Jiangsu University.

for all CO2 concentrations (3%, 14%, and 25%). Abu-Zahra et al.9 investigated the energy requirement by varying the removal percentage, MEA concentration, lean solvent loading, stripper operating pressure, and lean solvent temperature. Finally, lean solvent loading was regarded as the major energy saving factor. Optimum lean loadings were found to be 0.32 and 0.30 mol CO2/mol MEA in 30 wt % and 40 wt % MEA cases, respectively. Ziaii et al.10 created a rate-based model by Aspen Custom Modeler. Lean loading and height of packing were varied to minimize energy consumptions. The optimum operating condition was found to be at a lean loading of 0.42 mol CO2/mol MEA with a packing height of 1.8 m. Several papers offered dynamic analysis of this capture system.10-13 Panahi et al.12 used a UniSim process simulator to find an adequate controlled variable which gives close-tooptimal operation when held at constant. They found the temperature close to the top (tray no. 4) of the stripper can be a suitable self-optimizing controlled variable that keeps the capture system close to optimal operation. Kvamsdal et al.13 developed a dynamic model of absorber by gPROMs. Dynamic simulation results were presented for two transient conditions: start-up period and load-varying flue gas. The results showed that the L/G ratio significantly affects absorption performance and control operability in the partial load circumstance. Ziaii et al.10 constructed a dynamic model of stripper by Aspen Customer Modeler. Control strategies were applied during the period of electricity peak load. Open loop responses of the stripper were presented via two control methods. The majority of the above process dynamic studies focused on only analysis of individual units. There was very little study on the plantwide control of the integrated absorption/stripping system and control aspects. In this process, the MEA solution is used to absorb CO2 from the flue gas and then regenerated in stripper column. Luyben and Luyben,14 Yu and co-workers,15,16 and Wang and co-workers,17,18 have demonstrated the importance of recycle on the control design on the process. The primary objective of

10.1021/ie100771x  2011 American Chemical Society Published on Web 11/30/2010

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Figure 1. Process flowsheet of the absorption/stripping CO2 capture process.

this work is to investigate plantwide dynamics and control strategy of the absorption stripping process which is necessary for optimal and stable operation. The scope of the manuscript is organized as follows. In the next section, an initial steady state simulation of an existing pilot plant is presented. The dynamic simulation and control strategy are presented in Section 3. Results presented in Section 4 include the effect of water loss and accumulation on long stability of the system and the performance of the control structure against various disturbances and setpiont changes. Conclusions from this study will be given in the last section. In this work, dynamic behaviors were implemented by Aspen Dynamics. It is a widely used commercial dynamic simulator for studying dynamic process in academia and industry.19 It has been demonstrated that the rate-based model based on mass and heat transfer are more suitable for simulating absorption processes, only equilibrium-stage model can be used in Aspen Dynamics. Peng et al.20 compared dynamic simulation results of equilibrium and rate-based model. Although there were some differences in steady-state value, dynamic responses were similar. Robinson and Luyben21 used Aspen Dynamics to construct an IGCC dynamic model including CO2 absorption/ stripping unit and plantwide control structures were tested by involving different disturbances. It is not our purpose to match plant performance with simulations but to investigate the impact of recycle solvent on control structure design. Dynamic simulation based on equilibrium stage model can be adequately applied. 2. Process Description and Simulated Case A typical absorber/stripper process shown in Figure 1 was simulated. 30% MEA solution was used as the solvent. The dimensions of absorber and stripper are shown in Table 1. The stripper pressure is 1.8 atm which is designed slightly above atmospheric pressure to reduce energy requirement and avoid amine degradation. These dimensions correspond to a pilot plant to be completed in China Steel Corporation, Kaohsiung, Taiwan from which experimental verification can be obtained in the future. Steady-state simulations were obtained of the process using Aspen Plus version 7.1. Five equilibrium stages were assumed in both absorbers and strippers. To describe the absorption equilibrium, the electrolyte nonrandom-two liquid (ELECNRTL) property method and CO2MEA-H2O system chemistry that includes the following five equilibrium reactions were used.

MEA + H3O+ T MEAH+ + H2O CO2 + 2H2O T H3O+ + HCO3 2+ HCO3 + H2O T H3O + CO3 MEA + HCO3 T MEACOO + H2O

2H2O T H3O+ + OHCirculation of regenerated MEA solvent between stripper and absorber constitutes the recycle of the system. A key degree of freedom in designing the steady state operation is the lean loading, i.e., the amount of CO2 remaining in the lean solution coming out of the bottom of stripper. However, water balance is also a key factor that affects the convergence and stability of system. If water vapor in stripped gas is condensed and completely returned into the stripper (as shown by dash line in Figure 1) so that water balance depends on flue gas and vented gas only; then it is very difficult to obtain a steady state at any chosen recycle lean loading. However, if either water makeup or purge is allowed; different steady states can be reached using different recycle lean loadings. As shown in Table 2, different steady states can achieved at different lean solvent loadings ranging from 0.32 to 0.40 mol CO2/ mol MEA. Moreover, at low lean loadings, water makeup is required, while at high loadings water purge is necessary. To facilitate easy operation, water condensed from the stripped product gas is no longer directly recycled; instead steady flow of makeup water is used. Given that water inventory in the process can be manipulated by makeup, an operable case is needed for further Table 1. Column Internals description

absorber

top pressure (atm) column pressure drop (atm) packing height (m) inside diameter (m) packing type liquid holdup time (min)

1.0

stripper

1.8 0.1 2.0 0.1 16-mm Pall ring 5 5

Table 2. Water Balance in Different Lean Loadings lean loading water input water output water makeup water purge (mol CO2/mol MEA) (kg/h) (kg/h) (kg/h) (kg/h) 0.32 0.34 0.38 0.40

0.77 0.77 0.77 0.77

1.06 0.95 0.75 0.69

0.29 0.18 0.02 0.08

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Figure 2. The steady state optimization procedure: relationship between reboiler duty, lean loading and reboiler temperature.

Figure 3. Process flowsheet of the absorption/Stripping CO2 capture process with stream information of the optimized steady state.

control studies. Using steady state analysis, the energy consumptions at varying lean loadings were calculated as shown in Figure 2. The optimum case with lean loading 0.38 is selected. The temperature, pressure, and component flow rates are listed in Figure 3. This steady state employ a recycle lean solvent rate of 100.2 kg/h with lean solvent loading 0.38 mol CO2/mol MEA. A CO2 removal ratio of 90% was achieved using a reboiler duty of 2.15 kW and water makeup of 0.84 kg/h. Temperature at the bottom of the reboiler is 112.2 °C. 3. Dynamic Simulation and Control Strategy The steady state optimum case was exported to Aspen Dynamics and pressure-driven type was used to drive system dynamically. In Aspen Dynamics, several controllers were installed automatically including pressure and level controllers

of two columns. In addition, temperature controller of cooler was installed to maintain the temperature of the recirculating lean solvent at 40 °C. In dynamic simulation and control study, the stripper top pressure is controlled by a valve which adjust the stripped gas flow rate so that stripper top pressure can be maintained constant. The stripper pressure drop is calculated by the column hydraulics. The stripper top pressure can be controlled stably and quickly when any disturbance occurs. However, the bottom pressure of the stripper changes slightly as the flow rate through the stripper column changes. The primary objective of this process is to remove a fixed percentage (90%) of CO2 entering the absorber. The removal ratio can be calculated by measuring the concentrations of the CO2 in the flue gas inlet and vented gas. To maintain the removal target, the flow rate of the recirculating lean solvent flow rate is manipulated. However, since recirculating lean solvent flow

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Figure 4. The proposed plantwide control scheme.

Figure 5. Dynamic responses when level control of the stripper was relinquished and water makeup was (a) increased or (b) decreased.

rate must be changed, the usual level control of the reboiler using bottom draw rate of the stripper must be relinquished. Lean solvent loading is the most important parameter in the operation of this process. In the stripper, CO2 product was stripped from hot rich solvent. However, it is usually difficult to remove all of the CO2. Less reboiler duty is required if the remaining CO2 loading in the lean solvent is high. However, high lean solvent loading leads to poor absorption performance in the absorber. Generally, reboiler temperature is regarded as a good indicator of the lean solvent loading. Hence, the reboiler

temperature is controlled by the reboiler duty system and can be operated at a desired lean solvent loading. As mentioned in Section 2, the water make up is a critical factor in determining the actual steady state achieved. If the water condensed from the stripped product gas is not recycled, then water will be constantly lost and the overall holdup inventory of the absorber/stripper system cannot be maintained. In this process, the holdup in the absorber is maintained by the rich solvent draw rate, loss of inventory will be indicated by the loss of holdup in the reboiler. Hence, the water makeup

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Figure 6. Dynamic responses to (10% disturbance to inlet flue gas flow.

Figure 7. Dynamic responses of disturbances in CO2 composition in flue gas (a) 12.5 mol % to 14.5 mol % (b) 12.5 mol % to 10.5 mol %.

should be manipulated to stabilize liquid level in the reboiler, replacing the usual level control due to the need of manipulating the recirculating lean solvent rate. The completed control scheme suggested is shown in Figure 4. All controller’s parameters are tuned via tuning tools applying Tyreus-Luyben rules in Aspen Dynamics.

4. Results and Discussions 4.1. Water Makeup. To demonstrate the importance of proper water makeup in maintaining the system overall inventory and performance, the following simulation was carried out. Starting with the steady state of the optimum case, the water

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Figure 8. Dynamic responses of disturbances in water composition in flue gas (a) 9.5 mol % to 11.5 mol % (b) 9.5 mol % to 7.5 mol %.

makeup was increased and decreased by 20%, and the level control is relinquished at 0.5 h. It was found that the liquid level in the reboiler will deplete or accumulate (Figure 5). If a higher water makeup was used, then water will accumulate, resulting in a steady decrease in concentration of MEA, and an increase in reboiler duty. However, if there is not enough water makeup, then the concentration of MEA will keep increasing, and the liquid level in the reboiler will deplete. Therefore, it is important to maintain the correct water makeup by tracking the reboiler level. 4.2. Disturbance in Inlet Flue Gas. Now the CO2 capture process can be operated stably with minimum reboiler duty consumption. The ability of the control to regulate input disturbances is tested. Responses to (10% step change in inlet flue gas rate were presented in Figure 6. Due to more flue gas input, lean solvent flow rate increased to keep 90% removal. In the meanwhile, the stripper performance was controlled by reboiler temperature controller. It can be seen that the 90% removal target can be successfully maintained with corresponding increase in recycle solvent rate. The reboiler temperature remained unchanged. Responses to positive and negative step change in CO2 composition in flue gas inlet at 0.5 h are shown in Figure 7. CO2 composition step change in positive and negative case was made from 12.5 mol % to 14.5 mol % and 12.5 mol % to 10.5 mol %, respectively. The dynamic responses are similar to flue gas flow case. Figure 8 shows the responses of positive and negative step change in H2O composition in flue gas inlet at 0.5 h. H2O composition step change in positive and negative case was made from 9.5 mol % to 11.5 mol % and 9.5 mol % to 7.5 mol %, respectively. Disturbance of water composition in flue gas significantly affected the water balance of system.

Therefore, water makeup flow was manipulated to stabilize stripper sump’s level. 4.3. Flexible Removal Target. Ziazii et al.10 had simulated dynamic behaviors of a stripper in a flexible reboiler duty operation via ratio control strategy. Their objective was making systems flexible. For example, in a cogeneration power plant, the cost of steam production rises during peak hours of electricity demand. One would like to adjust set point of removal ratio to accommodate fluctuations in availability or cost of steam. Figure 9 shows dynamic responses of removal set point was adjusted from 90% to 85% and 90% to 95% at 0.5 h. As we decrease the removal target, less CO2 needs to be recovered, the lean solvent flow rate was decreased to attain 85% removal. The reboiler duty is reduced 6% in the new steady state. These results proved that the reboiler duty successfully decreased by adjusting the removal controller set point. So the system can be flexibly operated to deal with different CO2 recovery level. 4.4. Optimizing Control. Given the new steady state, which is acquired after regulations mentioned above, the primary question would be whether the given steady state is an energyefficient one. According to the control strategy suggested, the only operating degree of freedom is the temperature of the stripper. Hence a gradient-based step-by-step optimization can be implemented. Steps of 0.5 °C were used to determine the gradient. The maximum step was limited to 2 °C. Steady states can be obtained in each of the subsequent optimization moves after the reboiler temperature set point is changed. Results of optimization are shown in Table 3. The results show that the optimal target of the reboiler temperature is robust to all disturbances studied. Changes in H2O composition disturbance and removal rate adjustment between 85% and 95%

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Figure 9. Dynamic responses to set point changes in removal rate (a) 90% to 95% (b) 90% to 85%. Table 3. Re-optimized Results: Reboiler Duty and Stripper Bottom Temperature in Different System Disturbances steady state

reoptimized

system disturbance

reboiler T (°C)

reboiler duty (kW)

reboiler T (°C)

reboiler duty (kW)

optimum case flue gas flow rate +10% flue gas flow rate -10% CO2 composition 12.5% to 14.5% CO2 composition 12.5% to 10.5% H2O composition 9.5% to 11.5% H2O composition 9.5% to 7.5% removal 90% to 95% removal 90% to 85%

112.2 112.2 112.2 112.2 112.2 112.2 112.2 112.2 112.2

2.150 2.474 1.863 2.532 1.788 2.147 2.156 2.298 2.012

113.2 111.7 113.2 111.7 112.2 112.2 112.2 112.2

2.471 1.860 2.530 1.785 2.147 2.156 2.298 2.012

do not affect this value at all. 10% changes in total flue gas rate system induced a 0.5 °C change in this target. The robustness of this target value is most desirable to optimal control. 5. Conclusions In the above study, three important factorssnamely, lean solvent flow, lean solvent loading, and water makeup, which affect CO2 removal performance, energy efficiency, and longterm stability of the absorption/stripping CO2 capture process using monoethanolamine solutionswere identified. A control structure is proposed in which CO2 removal, which can be measured by CO2 concentrations in the inlet flue gas and vented gas at the top of the absorber, is guaranteed by manipulating the lean solvent feed rate to the top of the absorber column. The liquid level in the reboiler of the stripping column is controlled by the makeup water flow rate in order to maintain water inventory balance. The temperature at the bottom of stripper is controlled by the reboiler duty so that a fixed lean solvent loading can be achieved.

System disturbances, including flue gas total flow, CO2 concentration, and H2O concentration, were considered to test operability of the closed loop system. Dynamic results showed that the entire system can be controlled successfully at a 90% removal ratio and optimal lean loading of 0.38 mol CO2/mol MEA. Moreover, the removal ratio set point can be changed successfully, adjusted to accommodate variations in steam cost and availability. The desired lean loading that leads to minimum energy consumption can be found by simply adjusting the set point of the reboiler temperature using an optimizing control procedure. Acknowledgment The authors from National Tsinghua University, Hsinchu, Taiwan, are thankful for the financial support provided by the National Science Council, Taiwan, under the Grant Nos. 98ET-E-007-002-ET and NSC-98-3114-E-007-013; and by the China Steel Corporation, Taiwan, under Grant No. RE98611. T.H.P. acknowledges the support of the National Nature Science Foundation of China under Grant No. 60904053 and the

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ReceiVed for reView March 31, 2010 ReVised manuscript receiVed August 24, 2010 Accepted October 27, 2010 IE100771X