Design and Optimization of CO2 Recovery Process of Fire-Flooding Exhaust Based on Membrane Separation Method

1. Design of CO₂ Recovery Process of Fire-Flooding Exhaust

The components of fire-flooding exhaust are shown in Table 1.

As shown in Figure 1, the recycling process consists of three parts:

(1)

Secondary membrane separation

Membrane separation method has the advantages of no phase change, high separation efficiency, compact equipment and high reliability, which greatly simplifies the decarbonization process[24]. The method has been widely used at home and abroad, and the membrane separation of acetate fiber membrane is the most widely used and economical. As shown in Figure 2, the feed gas was pressurized to 2-3 MPa to enter the primary membrane separation unit, and CO₂ was enriched on the permeable side through the polymer membrane. The retained gas is mainly N₂, which re-enters the secondary membrane separation unit, and a small amount of CO₂ is enriched on the permeable side. The permeable side CO₂ rich flow is introduced into the cold box for pre-cooling liquefaction.

(2)

Mixed refrigerant refrigeration cycle

After the mixed refrigerant is compressed at three stages and cooled by water cooler, it is throttled by throttle valve and the CO₂ rich flow is liquefied in the cold box. The low pressure refrigerant after gasification returns to the entrance of the primary compressor and continues to cycle refrigeration.

(3)

CO₂ distillation and purification

The liquefied CO₂ rich flow is introduced into the rectification column, and the content of oxygen and hydrogen sulfide at the bottom of the column is controlled to obtain high purity food-grade liquid CO₂, which is entered into the CO₂ finished product storage tank. The temperature of the top of the tower is controlled to avoid the ice blockage of CO₂, and a small amount of tail gas mixture generated at the top of the tower is discharged.

According to the above process, the CO₂ recovery process shown in Figure 1 was established based on HYSYS software. However, Aspen HYSYS does not have a built-in gas penetration unit module. For this purpose, a "Membrane" membrane separation expansion module is used. This module has been used by foreign scholars to separate CO₂ from CH₄/CO₂ mixture and flue gas[25,26,27].

2. Analysis of Parameters of Liquefaction Process

2.1. Initial Parameter Setting and Product Requirements

Table 1 components are applied, and other parameters are set in Table 2.

2.2. Process Parameters and Performance Specifications

The main indicators to measure the performance of the process are specific power consumption and recovery rate. This article defines the specific power consumption of the process:

$$w={\displaystyle \frac{W_{MR,C}+W_{EG,C}+W_{Tower}}{M_{C{O}_2}}}\left(\mathrm{kW}\cdot \mathrm{h}/\mathrm{kg}\right)$$

(1)

CO₂ recovery rate:

$$x_{rec,C{O}_2}=\left(1-{\displaystyle \frac{M_{C{O}_{2}ofventing}}{M_{C{O}_{2}ofEG}}}\right)\times 100\%$$

(4)

where, W_MR,C, W_EG,C are the refrigerant compression work, and the compression work before fire-flooding exhaust film separation, kW respectively; W_Tower is the heat consumption of rectification tower, kW; M_EG is the mass flow rate of fire exhaust gas, kg/h; M_{CO2 of EG} is the mass flow of CO2 in the exhaust gas of fire flooding, kg/h; M_{CO2 of Venting} is the mass flow of CO2 in the vented air, kg/h; M_CO2 is the mass flow rate of liquid CO2, kg/h; w is the specific power consumption, kW∙h/kg.

According to Chapter 1 and 2, Table 3 gives the simulation results of key parameters of the process under basic cases.

At this time, the minimum heat transfer temperature difference of LNG-100 in the process is 3.446 ℃, the specific power consumption of the process is 2.818 kW∙h/kg, and the CO₂ recovery rate is 69.02%.

3. Process Optimization

3.1. Objective Functions and Constraints

The specific power consumption of the process is taken as the objective function, the minimum heat exchange temperature difference of the heat exchanger is not less than 3 ° C, the gas phase fraction of the low-pressure refrigerant returned to the primary compressor is equal to 1[34], the pressure ratio is not greater than 3, and the purity of liquid CO₂ meets Table 1 as the constraint conditions, and the optimization variables include the refrigerant flow rate, the outlet pressure of the refrigerant compressor and the temperature after throttling. In order to improve optimization efficiency and reduce the number of optimization variables, only the three-stage compression outlet pressure of mixed refrigerant χ is considered as the optimization variable of the compressor outlet pressure (refrigerant high pressure), while the outlet pressure of other stages is not regarded as an independent optimization variable, which is calculated by χ according to the optimal theory of proportional compression [35]. The final objective function and constraints are shown in Equation (7) and (8).

$$\left\{\begin{array}{c}\mathit{min}f\left(X\right)={\displaystyle \frac{W_{MR,C}+W_{EG,C}+W_{Tower}}{M_{C{O}_2}}}\left(\mathrm{kW}\cdot h\cdot \mathrm{k}{\mathrm{g}}^{-1}\right)\\ X=\left[q_{C1}{q}_{C2}{q}_{C3}{q}_{N2}\chi \mu \right]\end{array}\right.$$

(7)

$$\left\{\begin{array}{c}min.approach\left(LNG-100\right)-3\ge 0\\ \left({\displaystyle \frac{p_{MR1}}{p_{MR-Com}}},{\displaystyle \frac{p_{MR3}}{p_{MR2}}},{\displaystyle \frac{p_{MR5}}{p_{MR4}}}\right)\in \left[\mathrm{1,3}\right]\end{array}\right.$$

(8)

where, X is the independent variable matrix. Combined with the liquefaction process, it includes refrigerant CH₄ flow rate q_C1, refrigerant C₂H₆ flow rate q_C2, refrigerant C₃H₈ flow rate q_C3, refrigerant N₂ flow rate q_N2, three-stage compression outlet pressure of mixed refrigerant χ, and temperature μ after throttling of mixed refrigerant.

3.2. Optimization Process

The steady-state optimizer of HYSYS can optimize the process, but for the process with more variables, the optimization results often do not meet the constraints, so the optimization process is transferred to MATLAB[36]. By creating ActiveXcom server, the effective information exchange between HYSYS and Matlab programs can be realized. There are two advantages to using MATLAB for process optimization: on the one hand, it can easily satisfy constraints and allow custom optimization routines; On the other hand, detailed output can be displayed during the optimization process. In this study, sequential quadratic programming algorithm (SQP) is used to solve min f(X) and determine the optimal solution of variables. The detailed optimization process is shown in Figure 3, and the iterative process of SQP algorithm is shown in Figure 4.

3.3. Results and Analysis

On the basis of MATLAB & HYSYS hybrid simulation platform, SQP optimization algorithm is used to optimize the specific power consumption of the liquefaction process, and the optimal solutions of its objective function and variables are shown in Table 4. The specific power consumption is reduced to 2.287 kW∙h/kg, which is 18.8% lower than before optimization.

4. Process Adaptability Analysis

According to the current market situation, the price of food-grade liquid CO₂ is about 12 yuan/kg, then the total sales of the whole process product S is:

$$S=12\cdot M_{C{O}_2}\left(yuan\cdot h^{-1}\right)$$

(9)

According to the calculation, corresponding to 1000 kg/h of feed gas, the total sales of products under optimized conditions is S=2086.8 yuan/h. Based on the initial component and ignoring other trace components, the N₂ / CO₂ component ratio in the fire-flooding exhaust is changed under the condition that the minimum heat exchange temperature difference of the heat exchanger is 2-4 ℃ (to ensure a high heat exchange efficiency) to analyze the adaptability of optimization conditions. The results show that under the condition of constant raw gas flow, with the increase of CO₂ content in fire-flooding exhaust, the total sales of the product increases, the specific power consumption of the process decreases, and the CO₂ recovery rate increases, which means that the ability of the process to recover CO₂ is getting higher and higher.

5. Conclusions

In this paper, a process flow of CO₂ recovery from fire-flooding exhaust is designed, and HYSYS software is used to simulate the process. Meanwhile, HYSYS & MATLAB hybrid simulation platform is established, and SQP algorithm is used to optimize the process. Finally, the adaptability of optimization conditions is analyzed, and the following conclusions are drawn:

(1)

The designed CO₂ recovery process of fire-flooding exhaust can achieve the preparation of food-grade liquid CO₂. HYSYS process simulation shows that the CO₂ recovery rate is 69.02% under the basic case condition. After the optimization, the specific power consumption of the liquefaction process is reduced to 2.287 kW∙h/kg, which is 18.8% lower than before the optimization.

(2)

For a flow rate of 1000 kg/h, the total sales of products under optimized conditions under the components in Table 1 is S=2086.8 yuan/h. Under the conditions of N₂ / CO₂ components in Table 6, with the increase of CO₂ content in the exhaust gas, the total sales volume of the product increases, the specific power consumption of the process decreases, and the CO₂ recovery rate increases, that is, the ability of the process to recover CO₂ becomes higher and higher.

(3)

The process adopts membrane separation and enrichment of CO₂, avoids complex chemical decarbonization process, reduces the initial investment of equipment and long-term operating costs, makes full use of carbon resources in fire-flooding exhaust, and achieves the dual carbon goal of energy saving and emission reduction.