Dynamic control analysis of intensified extractive distillation process with vapor recompression

Dynamic control analysis of intensified extractive distillation process with vapor recompression

Separation and Purification Technology 233 (2020) 116016 Contents lists available at ScienceDirect Separation and Purification Technology journal hom...

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Separation and Purification Technology 233 (2020) 116016

Contents lists available at ScienceDirect

Separation and Purification Technology journal homepage: www.elsevier.com/locate/seppur

Dynamic control analysis of intensified extractive distillation process with vapor recompression

T



Qingjun Zhanga, Pengyuan Shia, Aiwu Zenga,b, , Youguang Maa,b, Xigang Yuana,b a b

State Key Laboratory of Chemical Engineering, School of Chemical Engineering and Technology, Tianjin University, 300350, PR China Chemical Engineering Research Center, Collaborative Innovative Center of Chemical Science and Engineering (Tianjin), PR China

A R T I C LE I N FO

A B S T R A C T

Keywords: Extractive distillation Vapor recompression Dynamic controllability

This paper explores the dynamic control of a complex multivariable interacting extractive distillation process with vapor recompression by taking the separation of acetone and methanol using water as separating agent. Results show that the effectiveness of conventional single-end temperature control structure with holding the solvent-to-feed and reflux-to-distillate ratios constant is poor owing to the large product offsets, and a series of improved control structures with composition controller(s) are developed and assessed by inserting the large throughput and feed composition perturbations. In the configuration of composition control loops, there are two crucial issues needed to be solved: one is that which of distillate impurities (methanol and solvent) should be controlled; another is the correspondingly paired manipulated variable (whether solvent-to-feed ratio or reflux ratio). Results illustrate that the effective product quality control is achieved for facing large (20%) disturbances in throughput and feed composition when the distillate methanol and water impurities are controlled by manipulating the solvent-to-feed and reflux-to-distillate ratios for extractive column, while another alternative is infeasible due to the failure of the tuning of the composition controller. And the control scheme with dualimpurity control strategy works better than that with single purity control option in terms of transient product peaks and settling time whether for handling throughput or feed composition disturbances.

1. Introduction Extractive distillation is a leading used technology for separating azeotropes or close-boiling mixtures in chemical and petrochemical industries, while the major intrinsic obstacle for extractive distillation process is the highly energy consumption rates. Therefore, it is essential to develop the energy-efficient competently alternative processes to reduce the energy consumption rates and enhance the process efficiency. Some intensified and integrated strategies had been applied to improve the efficiency of conventional extractive distillation process such as heat integration, thermal coupling, side-stream configuration and extractive dividing-wall column [1–6]. Herein, there are two tactics, for heat integration, to enhance the performance of conventional extractive distillation process that one is pairing the high-quality thermal energy of the overhead vapor stream (increase the operation pressure of either extractive column or solvent recovery column) with the heat sink (reboiler) to reduce the exclusively dependent on hot utility and another is preheating the cold stream by the hot recycle solvent stream (self-heat exchange option). Zhang et al. [7] investigated the different



configurations paired the cold stream(s) with the recirculated hot solvent stream, and the arrangement, hot solvent stream preheating the feed inlet stream of solvent recovery column, was economically efficient as it can further achieve the reductions of 4.38% in total annual cost (TAC) and 9.79% in steam cost in comparison with the conventional case. Self-heat exchange alternative strategy was also studied by Chen et al. [8], which was further lessening 8.90% in energy cost. The heat-integrated extractive distillation process was explored by Luyben et al. [9] with the separation of acetone and methanol using water as mass-separating agent as the demonstrating example, which reduced 20.53% in TAC and 27.21% in energy cost when compared to the conventional case. The operation pressure of solvent recovery column increases to achieve the reasonable heat-transferring temperature differential in the integrated condenser/reboiler exchanger. The doubleeffect heat-integrated extractive distillation process was also studied by Gu et al. [10], and it can produce 20.30% less in TAC in comparison with the conventional process. It is important to note that there are some limitations for this integrated condenser/reboiler exchanger alternative option. One is the restriction in the thermal level of hot utility, that is, the heat-transferring driving force between the reboiler and

Corresponding author at: State Key Laboratory of Chemical Engineering, School of Chemical Engineering and Technology, Tianjin University, 300350, PR China. E-mail address: [email protected] (A. Zeng).

https://doi.org/10.1016/j.seppur.2019.116016 Received 3 May 2019; Received in revised form 20 August 2019; Accepted 1 September 2019 Available online 03 September 2019 1383-5866/ © 2019 Elsevier B.V. All rights reserved.

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Nomenclature TAC PSD EDWC COP RDWC ADWC QR

RR Kc τI TC CC PC FC LC IAE

total annual cost pressure-swing distillation extractive dividing-wall column coefficient of performance reactive dividing-wall column azeotropic dividing-wall column reboiler heat duty

reflux ratio controller gains integral time [min] temperature controller composition controller pressure controller flow controller level controller integral absolute error

distillation processes in terms of steady-state designs have received some attentions. The performance of reactive dividing-wall column (RDWC) for the esterification synthesis n-propyl propionate process was improved by taking the vapor recompression and thermal integration options, and the reductions of 61.52% in CO2 emissions, 31.31% in TAC were obtained with respect to the conventional two-column design [17]. Li et al. [18] also studied the vapor recompression-assisted RDWC arrangement taking the production of methyl acetate by the esterification of methanol and acetic acid as the demonstrating example, and it can achieve 58.10% and 17.80% less in energy requirements and TAC in comparison with that of conventional RDWC. This intensified alternative option was also studied by Feng et al. [19] with the transesterification reaction of methyl acetate and isopropanol as the example, and the energy-saving and economically potential was further observed by adding a preheater in suction stream of compressor than the counterparts without preheater. The feasibility and effectiveness of the heat pump-assisted azeotropic dividing-wall column (ADWC) process for separating tert-butanol and water mixture were determined and explored by Li et al. [20], which can reduce 32.22% in TAC and 63.79% in carbon footprints when compared to the conventional two-column design. Besides, the vapor recompression-assisted ADWC arrangement with heat exchanger networks were studied by Patrascu et al. [21], and the 58% less of energy requirement was achieved. Zhang et al. [22] studied the intensified pressure-swing distillation (PSD) configuration with vapor recompression and thermal integration, and the optimal configuration can reduce 67.05% in energy consumption rates, 72.66% in carbon footprints and 34.14% in TAC as well as enhance 159.06% in thermodynamic efficiency with respect to the conventionally heat-integrated PSD arrangement. Besides, the self-heat recuperation-assisted PSD configuration with heat exchanger networks was eco-efficient when compared to the fully heat-integrated case owing to it further producing reductions of 5.18% in TAC, 53.06% in energy consumption rates and 87.15% in carbon footprint [23]. Luyben [24] revised this arrangement and developed a much simpler heat exchanger system with reoptimizing the column overhead azeotropic composition, and the 31% and 16% less in compressor power requirements and energy costs were further achieved in comparison with that of Xia et al. [23]. However, in extractive distillation process, there are high temperature differences in extractive and solvent recovery columns, which is the obstacle for the application of vapor recompression-assisted intensified option. Luo et al. [25] established a novel heat pump-assisted extractive distillation arrangement integrating three columns into one vessel with a side-reboiler for bioethanol dehydration process, and the corresponding reductions of 40% in energy requirement and 24% in TAC were obtained with respect to the conventional three-column sequence. Comprehensively taken the consideration of the temperature difference between the extractive column and solvent recovery column, Nhien et al. [26] proposed a new mechanical heat pump-assisted extractive distillation configuration to improve the performance of conventional process, wherein the heat requirement in reboiler of extractive column was partially provided by the desuperheating and condensing heats of the discharging stream of compressor in solvent regeneration column and the extra required energy was offered by the partially pressurized overhead vapor stream of extractive column. The total energy

external steam or others should be sufficiently large (20–30 K) [11,12]. Another is that solvent will be thermally decomposed when operation temperature is higher than a specific temperature. Therefore, this arrangement is limited to separate the special mixtures. The reason for the highly energy consumption rates in the conventional extractive distillation configuration mainly is the lower thermodynamic efficiency caused by the remixing effect of the intermediate component in ternary or multi-component system containing entrainer. The corresponding intensified thermally coupling or dividing-wall column configurations were developed to alleviate or eliminate this phenomenon by substituting the direct vapor-liquid interconnected streams for the reboiler or condenser at the non-product stream end. Brito et al. [13] compared the performances of the thermally coupled and heat-integrated sequences taking the separation of three azeotropic mixtures as demonstrating examples. It was observed that processes with self-heat exchanger option (preheating fresh feed stream by the hot recycle solvent stream) showed economic advantages over the thermally coupling configurations. The thermally coupled ternary extractive distillation process was studied by Zhao et al. [14] and the reductions of 8.65% in TAC and 9.11% in overall reboiler heat requirements were achieved. Besides, the energy-saving potential of the extractive dividing-wall column (EDWC) was critically assessed by Wu et al. [15] using the three industrially azeotropic mixtures as demonstrating examples in comparison with the conventional two-column systems. Although the savings of the overall reboiler heat consumptions were generated in EDWC options, while only the acetone-methanol system was economically efficient among them. The reason for the deficiency in the steady-state economics is that the savings of overall reboiler heat requirements will be transformed to the steam cost or energy cost savings when the same steam grade uses in both columns, which is determined by the operation essence of EDWC with the one reboiler generated by combining two reboilers in conventional designs. And the bottoms temperature of this combined reboiler is the maximum temperature of the previous two reboilers. To the best of our knowledge, for distillation processes, the most of heat supplied in the reboiler was wasted in the condenser, producing the huge energy consumption rates and exergy losses. To further improve the process performance (or thermodynamic efficiency) and lessen the amount of carbon footprints, the eco-efficient vapor recompression-assisted technology can be used. As is well-known, the reboiler needs high-quality energy, while only the low-grade thermal energy is offered by the condenser. Therefore, a heat pump is needed to increase its thermal quality to act as the heat requirement(s) in reboiler (s), and the surplus heat is used to preheat the cold stream(s). The feasibility and effectiveness of this intensified alternative option mainly relates to the electricity power requirement in compressor (compression ratio). The larger overall column temperature difference, the larger compression ratio, and the greater power requirement in compressor, which could increase the operation cost. Plesu et al. [16] proposed a simple evaluation criterion, coefficient of performance (COP), to rank whether a heat pump is worth using in distillation process. When the COP value exceeds 10, a heat pump is clearly recommended, whereas there are no any benefits if it is lower than 5. The investigation of vapor recompression-assisted complex 2

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the conventional design. There are few researches on dynamic controllability compared with the steady-state design for this efficient and highly-integrated option. The dynamic control analysis for this novel intensified arrangement, proposed by Luo et al. [25], was studied by Patrascu et al. [29]. The original configuration was poorly controlled and the modified process was established. The complex and weak control scheme was developed with a split-range valve arrangement and valve position control in the bypass except with the dual-composition control loops. The simpler and more robust dynamic control structure for this case was constructed by Luyben [30], and product quality control was efficiently achieved by the developed a dual-product composition control structure with the overhead vapor-splitting and without auxiliary side-reboiler for facing large (20%) disturbances in throughput and feed composition. A complex vapor recompressionassisted RDWC was modified from series configuration, heat transferring from the vapor stream discharging from compressor to the reboilers and preheaters in sequence, to parallel configuration (two vapor

consumption of this proposed novel configuration was 62% less than the conventional two-column design. You et al. [27] revised this arrangement and add two preheaters in the suction streams of compressors with reoptimizing the column variables, and this new configuration can reduce 52.78% in energy cost, 21.55% in TAC and 55.92% in CO2 emissions relatively to the conventional process. Besides, it was also attractive in economic and environmental performance evaluation indicators with respect to the bottom flashing heat pump process. And these insightful papers provide a new pathway to improve the performance of extractive distillation process. However, this insightful paper [27] was not investigated the dynamic control behavior for this economic-efficient complex configuration. As taught by the terminology of “simultaneous design” [28], the exploration of the dynamic controllability and developing a robust control scheme for this efficiently integrated configuration is an indispensable to maintain the optimal and safe operation since the interactions of parameters are highly integrated and complicated relatively to

Fig. 1. Intensified extractive distillation process flowsheet and the corresponding T-H diagram. 3

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multivariable process when facing large disturbances in throughput and feed composition.

streams splitting from the overhead vapor stream enhanced their own heat quality to send to the appropriate reboilers and preheaters) by Luyben [31] to improve the dynamic control rangeability for this complex arrangement, and the two-temperature control scheme with a composition control loop at an appropriate tray location was developed to robustly reject the feed disturbances. Luyben [32] also studied the control of a vapor recompression-assisted ADWC process dealing with tert-butanol dehydration process. The robust and efficient control performance was achieved by the constructed three-temperature control scheme with pressure-compensation strategy. Patrascu et al. [33] investigated the dynamics and control of a highly integrated and efficient heat pump assisted-ADWC arrangement for biobutanol purification process, and a feasible control strategy was established with temperature-composition cascaded control loops by adding an additional reboiler and condenser. Dynamic control behavior analysis for vapor recompressed ADWC process was also studied by Chen et al. [34] with separating EDA/water system and the robust dynamic response performance was obtained with the only three-temperature control strategy for facing large interferences of throughput and feed composition. Luyben [24] investigated the issue of dynamic controllability of PSD process with vapor recompression. The attenuation or elimination of snowball effect and the effective product quality control were achieved by the devised novel robust control structure for rejecting large (20%) feed disturbances, and the core control loops of this robust control scheme was the recycle distillate flowrate as the throughput manipulator and the reflux drum levels controlled by regulating the corresponding feed inlet stream flow. From the above results, these complex processes were much attractive in economic, energy-saving and environmental performance evaluation indicators, while these complex processes present great challenges in establishing the robust control structures. Therefore, the dynamic controllability for this efficiently intensified extractive distillation process with highly multivariable interacting loops is needed to be thoroughly investigated. This paper is the extended work of You et al. [27] for the novel complex extractive distillation configuration with vapor recompression and the contribution of this paper is to develop an effective and robust plant-wide control scheme for this highly integrating and interacting

2. Process description Fig. 1 gives the flowsheet of the extractive distillation process with vapor recompression studied in this paper. The Aspen built-in UNIQUAC physical properties package is used. The fresh feed is fed on Stage 55 of a 65-stage column C1 (operated at 0.6 atm) and the corresponding feed flowrate and temperature are 540 kmol·h−1 and 320 K with the equimolar composition of acetone and methanol. The solvent is fed on Stage 34 at 560 kmol·h−1 and 320 K with 99.998 mol% purity water. Product acetone (99.50 mol%) is taken out in distillate stream D1. Bottoms stream is fed into the column C2 (operated at 1 atm) at Stage 25 of a 35-stage column. Product methanol (99.50 mol%) is obtained in distillate stream D2. And the corresponding solvent makeup stream is added to compensate the entrainer losses in both distillate streams, along with the bottoms stream of column C2 recycling back to column C1 after cooling down to 320 K. The pressure drop of per tray is 0.0068 atm for both columns. The structural parameters (column stages, feed location, and compression ratio, etc) are directly taken from You et al. [27] paper. The overhead vapor stream from each column is compressed to a pressure that is high enough to provide a suitable heat transfer temperature differential driving force in the reboiler, consisting of two virtual heat exchangers named REB1 and REB2, of extractive column C1. The energy requirement to achieve the specifying separation in column C1 is 8.56 MW, while the heat released in desuperheating and condensing the discharging stream from the compressor Comp 2 is only 5.42 MW, indicating that about 63.32% portion of the heat requirement in reboiler is provided by this virtual heat exchanger REB2, and the extra required vapor boilup (3.14 MW), shown in virtual heat exchanger REB1, is provided by the partially pressurized overhead vapor stream coming from compressor Comp 1 for column C1. The overhead vapor stream is splitting into two streams that one stream with flowrate at 375.60 kmol·h−1 enters the compressor Comp 1 to improve its heat quality to serve as the heat source of reboiler, then the stream leaving

Fig. 2. The open-loop analysis results for columns C1 and C2. 4

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exchanger Cooler 1. And these two streams blend in reflux drum 1. To reduce the heat differential between the two sides of compressor, the preheaters, Heater 1 and Heater 2, are installed to improve the suction vapor temperature and avoid the liquefaction during the compression process. Both temperatures of overhead vapor streams entering the compressors are set as 3 K superheating by the preheaters to exactly meet the heat requirement in reboiler of column C1 in the previous work, while in our simulation process, the corresponding heat released in these two virtual heat exchangers are less than the overall heat requirement in reboiler of column C1. Therefore, both the suction temperatures of compressors are adjusting by the preheater (Heater 1 and Heater 2) heat loads to achieve this neat operation. The heat released in these two virtual heat exchangers is exactly equal to the heat requirement in reboiler of column C1 when the superheating temperature is 15 K and 18 K for streams entering compressors Comp 1 and Comp 2, respectively, holding compression ratios of these two compressors constant. The detailed information and the corresponding temperatureenthalpy (T-H) diagrams for this arrangement are shown in Fig. 1. The overlap region (shaded zone) between the hot composite curve (HCC) and the cold composite curve (CCC) is for the heat recovery possible within the process. The “overshoots” of the HCC and CCC curves represent the extra requirements of the cold utility (cooling water) and the hot utility (LP or MP Steam). And the detailed implication of these composite curves is illustrated in the works of Zhang et al. [22] and Xia et al. [23]. The QCW and Qh, respectively, represent the requirements of the cold and hot utilities for this process.

Table 1 Effects of Feed Composition Change on Variables for Intensified Extractive Distillation Process. Items

Case 1

Design

Case 2

Feed Acetone molar content Feed flowrate F kmol/h kg/h Reflux flowrate R1 kmol/h kg/h R1/F molar ratio % change from design R1/F mass ratio % change from design Reflux ratio RR1 % change from design Bottom flowrate B1 kmol/h kg/h Reflux flowrate R2 kmol/h kg/h R2/F molar ratio % change from design R2/F mass ratio % change from design R2/B1 molar ratio % change from design R2/B1 mass ratio % change from design Reflux ratio RR2 % change from design

0.49 540 24192.39 684.38 39613.72 1.267 −2.094 1.637 −1.525 2.578 −0.092 834.55 18914.23 272.16 8718.09 0.504 1.478 0.360 2.065 0.326 0.818 0.461 0.544 0.984 −0.514

0.50 540 24332.99 699.01 40461.02 1.294 0 1.663 0 2.580 0 829.12 18740.50 268.20 8591.32 0.497 0 0.353 0 0.323 0 0.458 0 0.989 0

0.51 540 24473.60 713.76 41315.00 1.322 2.110 1.688 1.524 2.583 0.104 823.69 18566.76 264.26 8465.47 0.489 −1.467 0.346 −2.031 0.321 −0.818 0.456 −0.543 0.994 0.546

Note: The subscripts 1 and 2 are for the process variables of columns C1 and C2, respectively.

3. Dynamic control

the virtual heat exchanger REB1 is through the throttle valve and Cooler 2 to achieve the top temperature of column C1, while another stream is directly cooled down to the reflux drum temperature by the

The steady-state simulation file is exported to the Aspen Dynamics after specifying the plumbing system and major equipment(s) sizes with pressure-driven dynamic simulation. The sizes of reflux drums and

Fig. 3. Basic control structure CS1 for intensified extractive distillation process. 5

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Fig. 4. The Aspen plus PFD for intensified extractive distillation process.

obtained with the small variation ( ± 0.1% of design value) of manipulated variables (such as rebolier heat duty QR and reflux ratio RR). The open-loop steady-state gains between the temperature on that tray and each manipulated variable are obtained by dividing the change in the tray temperature with the variation of the relevant manipulated variable. And the tray with largest temperature change should be controlled since the composition change from tray to tray is also large. As obtained from Fig. 2, the temperatures of Stages 59 and 30 are sensitive to the change of reflux ratio and reboiler heat input for columns C1 and C2. And the conventional distillation control wisdom predicts that the tighter control can be achieved by manipulating the vapor flowrate than the liquid reflux flowrate [37,38]. If the manipulated variable of liquid reflux flow is used, the response lag time is quite large due to the inherent liquid hydraulic lags for typically 3–6 s per tray. Therefore, controlling the temperatures of Stages 59 and 30 with liquid reflux flow have the 177–354 s and 90–180 s lags in the temperature control loops, respectively, indicating the inefficient operation. It is dynamically feasible and efficient for pairing the reboiler heat input with sensitive tray temperature. The reboiler heat duty is not a free variable for column C1 due to the restriction of heat integration by these two virtual heat exchangers, herein, Stage 59 temperature in column C1 is controlled by manipulating the power in compressor Comp 1. To achieve the robust control performance, another tight selection of control scheme is also significant, including single- and dual-end control strategies. For single-end scheme, another potential issue is how to screen the other fixed variables (such as the reflux-to-distillate or reflux-to-feed ratios, etc.), which can be efficiently determined by the method of feed composition sensitive analysis [35,39]. The percentage changes of manipulated variables are obtained over a range of feed composition holding product purities and feed flowrate constant. Table 1 gives the analysis results of the reflux-to-distillate and reflux-tofeed ratios for changing feed acetone composition in columns C1 and C2. These results demonstrate that a molar reflux-to-distillate (RR) (kmol/ kmol) ratio structure should be clearly better than others since its percent changes are lowest.

Fig. 5. Flowsheet equations for heat integration between the reboiler of column C1 and two virtual heat exchangers.

column bases are determined by providing 10 min of liquid holdup when the vessel is half full. The conventional proportional-only controller with the gain (Kc) of 2 and integral time (τI) of 9999 min is employed to all level control loops. The proportional-integral temperature and composition controllers are used in the regulatory control loops, and their ultimate periods and frequencies are determined and obtained by the relay-feedback testing procedure and Tyreus-Luyben tuning rules [9]. The dead-time blocks of 1-min and 3-min are inserted to the temperature and composition control loops, respectively [35]. The proportional-integral controller is also used to feed flowrate controller with Kc = 0.5 and τI = 0.3 min. And the default setting parameters of pressure controller are Kc = 20 and τI = 12 min [9,35].

3.1. Feed composition sensitive analysis and sensitive tray location determination The significant issue of finding a robust control scheme is to select tray location(s) whose temperature should be controlled. In this work, the sensitivity criterion is used to determine the sensitive tray temperature location(s) [35,36]. The temperature changes of all stages are 6

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Fig. 6. Dynamic response results of basic control structure CS1: (a) ± 10% throughput disturbances; (b) ± 10% feed composition disturbances.

7

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Fig. 7. (a) Effect of reflux ratio and solvent flowrate on product acetone purity; (b) Effect of reflux ratio and solvent flowrate on product acetone impurities.

Fig. 8. Improved control structure CS3 for intensified extractive distillation process.

8

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Fig. 9. Dynamic response results of control structure CS3: (a) ± 20% throughput disturbances; (b) ± 20% feed composition disturbances.

the heat removals in Cooler 2 and Cooler 3 (reverse action). 10. The temperatures of overhead vapor streams entering compressors are controlled by manipulating the heat input in preheaters of Heater 1 and Heater 2 for columns C1 and C2, respectively (reverse action). 11. The temperature of recycle entrainer stream is controlled to 320 K by manipulating the heat removal in Cooler 4 (reverse action). 12. The reflux flowrates are ratioed to the distillate flowrates. 13. The solvent flowrate is ratioed to the fresh feed flowrate and the recycle solvent is flow controlled by bottoms flowrate of column C2 (reverse action).

3.2. Plant-wide dynamic control schemes 3.2.1. Conventional Single-end temperature control structure The initial control structure CS1 is shown in Fig. 3, the detailed control loops with their paired controlled and manipulated variables are enumerated below. 1. The fresh feed is flow controlled, and the throughput disturbances are introduced by adjusting its set-point (reverse action). 2. The reflux drum levels are controlled by manipulating the distillate flowrates (direct action). 3. The base level of extractive column C1 is controlled by manipulating the bottoms B1 flowrate (direct action). 4. The base level of solvent recovery column C2 is controlled by manipulating the small solvent makeup flowrate (reverse action). 5. The operation pressure of extractive column C1 is controlled by manipulating the heat removal in Cooler 1 (reverse action). 6. The operation pressure of solvent recovery column C2 is controlled by manipulating the power in compressor Comp 2 (direct action). 7. The temperature on Stage 59 in extractive column C1 is controlled by manipulating the power in compressor Comp 1 (reverse action). 8. The temperature on Stage 30 in solvent recovery column C2 is controlled by manipulating the heat input in reboiler (reverse action). 9. The temperatures of streams entering reflux drums 1 and 2 are controlled to 315.10 K and 337.70 K, respectively, by manipulating

The procedure used in this work for this complex configuration with three tear streams in steady-state simulation is shown in Fig. 4. Herein, the discharging streams leaving compressors (Comp 1 and Comp 2) are fed into the fictitious heat exchanger blocks that are Aspen Heater models labeled “REB1” and “REB2”, and the heat released in heat exchangers “REB1” and “REB2” are served as the heat source in reboiler of column C1. The detailed heat transfer relationships between the reboiler of column C1 and these two virtual heat exchangers “REB1” and “REB2” are handled in Aspen Dynamics by using Flowsheet Equations, as given in Fig. 5. A log-mean temperature differential is calculated by using the temperature of the discharging stream in compressor as the hot-end of heat exchanger and base temperature of column C1 as the cold end. The duty of virtual heat exchanger is calculated by a fixed area, a constant overall heat transfer coefficient and current log-mean 9

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Fig. 9. (continued)

in feed acetone composition and it is ultimately stable to about 96.20 mol%, while it is 98.10 mol% for product methanol purity. Results indicate that the effectiveness of this conventional single-end temperature control strategy with holding solvent-to-feed and reflux-todistillate ratios constant is poor owing to the large steady-state deviations of product compositions to their correspondingly initial design specifications. Therefore, the efficient and robust control scheme needs to be established to effectively reject these interferences. The detailed tuning parameters for the regulatory controllers in this control structure CS1 are enumerated in Table S1 of Supporting Information.

differential temperature driving force. Note that heat is transfer out from these “REB1” and “REB2” blocks, respectively, therefore it is a negative number using Aspen notation. Therefore, the energy requirement to achieve the specified separation in column C1 is set equal to the summation of negative of the duties in fictitious “REB1” and “REB2” blocks. Fig. 6 gives the dynamic response results of this basic control structure CS1 for handling throughput and feed composition disturbances. The solid lines demonstrate the responses for positive increment of disturbances, while the dashed lines show the response for negative changes. Dynamic response results for handling plus and minus 10% step changes in throughput are shown in Fig. 6(a). Both product purities are quickly going back to their steady-state design specifications when handling plus 10% step change in throughput. All controlled temperatures are also restored to their initial steady-state design values. Product acetone composition is largely deviated from its steady-state design for facing minus 10% step change in throughput and it is ultimately stable to 97.80 mol%, while it is 99.20 mol% for product methanol purity. Fig. 6(b) shows the dynamic response results for handling feed composition disturbances. The solid lines are for plus 10% step change of feed acetone composition with the corresponding reduction of methanol composition in fresh feed stream, and the dashed lines are for minus 10% step change of feed acetone composition with the corresponding increase of methanol composition in throughput manipulator stream. The poor control performance is also observed due to the large product offsets. Product acetone composition is largely deviated from its steady-state design for facing minus 10% step change

3.2.2. Control schemes with distillate composition control In solvent recovery column, it is relatively simple since the solvent water is identified as the main impurity in the distillate methanol stream, and it can be paired with the manipulated variable of reflux ratio. In extractive column, the distillate stream has two impurities including solvent (water) and heavy component methanol, respectively. And the corresponding manipulated variables are three, which are the solvent flowrate, reflux flowrate and reboiler heat duty (herein, the power in compressor Comp1 is used), respectively. In the configuration of composition control loops, there are two crucial issues needed to be addressed: the one is that which of impurities should be controlled, and another is that which of manipulated variables should be paired with this relevant controlled variable. The effect of reflux ratio and solvent flowrate on product purity and impurities is essentially investigated to determine how to reasonably pair the controlled variable(s) with manipulated variable(s). These 10

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Fig. 10. Improved control structure CS5 for intensified extractive distillation process.

with either of two impurities for extractive column C1, and the corresponding results will be verified below. Considering the opposite effect of these two impurities with manipulating variables of solvent flowrate and reflux ratio and the main impurity in product acetone stream, the solvent water impurity is selected to control. There are two choices for pairing either reflux ratio or solvent content to regulate this impurity. One is that the water impurity is controlled by manipulating solvent flowrate, and the failure of the tuning of this controller is occurred when the controller action is selected to reverse. The system is crashed at 0.36 h without adding any interference, although this controller is successfully tuned with direct action. Another is the reflux ratio. The tuning of this controller (direct action) is normal when the running time is less than 3.5 h, while the same failure also occurs after more than 3.5 h owing to the occurrence of the divergence in the tuned responding curves. The system is server oscillatory and without stable when facing plus 20% step changes in throughput when the parameters (KC = 0.88 and τI = 59.40 min) of this composition controller are selected from the previously successful tuning results before 3.5 h. It is also severely inefficient for selecting control methanol impurity by manipulating solvent flowrate (KC = 0.065 and τI = 315.48 min, direct action) or reflux ratio (KC = 0.069 and τI = 345.84 min, direct action) owing to the particularly longer stable time (about 20 h) and larger transient product peaks. Therefore, in the single composition control loops, product acetone composition is directly controlled by manipulating the solvent-to-feed flowrate ratio, according to the results of Fig. 7(a), and this control structure CS2 is presented in Fig. S1 of Supporting Information. A 3-min deadtime is contained in this regulatory control loops. Besides, the remaining control loops are the same as the initial control structure CS1. Fig. S2 of Supporting Information gives the dynamic response results of

results are obtained, shown in Fig. 7, at specified over range of solvent flowrate and reflux ratio with holding bottoms composition constant (0. 01 mol% acetone) by adjusting the reboiler heat duty. The effect of solvent flowrate and reflux ratio on distillate acetone composition is shown in Fig. 7(a), what the conclusion is that the higher solvent flowrate, the higher acetone purity and the relationship of reflux ratio with acetone purity is nonmonotonic for a specified solvent flowrate, which indicates that there is an optimal reflux ratio giving the maximum product purity for a certain solvent flowrate. Fig. 7(b) gives the results of distillate impurities by varying solvent flowrate and reflux ratio. The nonmonotonic relationship for impurities (methanol and water) and reflux ratio is also obtained at a specified solvent flowrate, but the shapes are the opposite for these two impurities. The methanol impurity is decreased with the increase of solvent flowrate, and it reaches a minimum while solvent water impurity reaches a maximum. And of particular importance is that the trend of solvent impurity changing with the reflux ratio is different from that of conventional extractive distillation process using heavy entrainer as separating agent. In conventional extractive distillation column, the solvent impurity always decreases by augmenting the reflux ratio for a specified solvent flowrate [9,40]. In this system, the effect of solvent flowrate on these two impurities is the opposite, which means that more solvent flowrate will reduce methanol impurity in distillate acetone stream while it will inversely increase the solvent water impurity. Besides, the effect of reflux ratio on these two impurities is also the opposite. When reflux ratio is larger than the optimal reflux ratio, the increase of reflux ratio will result in the decrease of solvent content in the extractive section (dilution effect) while it will lead to the augment of methanol impurity in distillate stream. These opposite effects will produce some controlled difficulties in this process by pairing solvent flowrate or reflux ratio 11

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Fig. 11. Dynamic response performance results of control structure CS5: (a) ± 20% throughput disturbances; (b) ± 20% feed composition disturbances.

loops. Product methanol purity is controlled by manipulating the reflux ratio of column C2 and the rest control loops are the same as control structure CS2. Dynamic response results for facing throughput disturbances are shown in Fig. S3(a) of Supporting Information. The implications of these solid and dashed lines are the same as that of the above cases. These disturbances are well handled with the stable regulatory control achieved. Both product purities are rigorously restored to their steady-state design specifications. All temperatures are well controlled and are also quickly going back to their initial steady-state design values. Dynamic response results for facing feed composition disturbances are shown in Fig. S3(b) in Supporting Information. And the implications of these solid and dashed lines are also the same as that of the aforementioned control structures. These perturbations are also well handled with stable regulatory control achieved. Both product purities are also rigorously restored to their steady-state design values, which are addressed the issues (large product offsets) of control structures CS1 and CS2 at facing throughput and feed composition disturbances, respectively. The aforementioned results are indicated that this control scheme is robust and efficient for facing large throughput and feed composition disturbances. And the relay-feedback testing and Tyreus-Luyben tuning results of temperature and composition loops for control structures CS2 and CS3 are enumerated in Tables S2 and S3 of Supporting Information. To further determine the anti-rejecting disturbance ability of this control structure CS3, the larger (20%) disturbances are also introduced. Fig. 9(a) gives the dynamic response results for facing 20%

control structure CS2 for facing throughput and feed composition perturbations. These disturbances are well handled with stable regulatory control achieved. Fig. S2(a) of Supporting Information illustrates the dynamic response results for handling throughput perturbations. The solid and dashed lines are, respectively, for handling plus and minus 10% step change in throughput. Product acetone composition is rigorously restored to its initial steady-state design specification. The transient deviation of product acetone purity is quite small, which indicates that this control strategy is robust and efficient. Product methanol composition is closely going back to its steady-state design specification for handling 10% step increase in throughput, while there is a large product offset for handling minus 10% step change in throughput and its ultimate response value is 99.10 mol%. Dynamic response results for feed composition disturbances are shown in Fig. S2(b) of Supporting Information. The solid lines are for feed acetone composition increase from 50 to 55 mol% with a corresponding reduction of methanol composition in throughput manipulator’s stream. The dashed lines are for 10% decreases with the corresponding augment of methanol composition in fresh feed stream. Product acetone composition is well controlled and is quickly returned to the specification, while for methanol purity, there is also a large product offset for 10% increases. These problems can be addressed by the developed control strategy with direct dual-product composition control loops. Fig. 8 shows the modified control structure CS3 with dual-product composition control loops to eliminate or attenuate product methanol offset. A same 3-min deadtime is used in these composition control 12

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Fig. 11. (continued) Table 2 Dynamic response performance comparisons for different alternative control structures. 20% Throughput Disturbances Items IAExD1, IAExD2, IAESum

Acetone Methanol

20% Feed Composition Disturbances

CS3

CS4

CS5

CS3

CS4

CS5

0.006616 9.566E−05 0.006712

4.867E−05 0.000128 0.000177

2.277E−05 0.000123 0.000146

0.004572 0.000371 0.004943

2.391E−05 0.000348 0.000372

2.270E−05 0.000295 0.000317

time is relatively longer (about 12 h) to reach new steady state in comparison with that of handling 10% feed disturbances. As obtained from Fig. 7, the opposite effect of solvent flowrate and reflux ratio on distillate acetone impurities show some issues of efficient control in this process. In this section, we explore the performance and effectiveness of dual-impurity control scheme (inspired by Luyben et al. [41]) in distillate acetone stream. According to the nonmonotonic relationship of two impurities in distillate acetone stream with two manipulated variables of solvent flowrate and reflux ratio, these two impurities are controlled. There is also an important issue needed to be addressed, which is the paired of controlled variables (solvent and methanol impurities) with manipulated variables (either solvent flowrate or reflux ratio). The curves shown in Fig. 7(b) illustrate that methanol impurity is reduced by increasing solvent flowrate and increasing reflux ratio will result in the decrease of water content in the higher reflux ratio region (large than the optimal reflux ratio) while the results are the opposite in the lower reflux ratio region (less than the

throughput perturbations. The solid lines are for changes from 540 to 648 kmol·h−1. The dashed lines are for 20% decreases. These disturbances are also well addressed with both product purities rigorously restored to their steady-state design specifications. All temperatures are also well controlled and are quickly going back to their initial steadystate design values. It is also discovered that the fluctuations for system facing large disturbances are severer than that with relatively small disturbances (10%) due to the large transient deviation of product acetone purity and the limitation of the heat integration between the two virtual heat exchangers. Dynamic response results for feed composition perturbations are presented in Fig. 9(b). The solid lines are for feed acetone composition changes from 50 to 60 mol% with the corresponding reduction of methanol composition in fresh feed stream. The dashed lines are for feed acetone composition decreases from 50 to 40 mol% with the relevant increase methanol composition in fresh feed stream. These disturbances are also well handled with stable regulatory control achieved. As observed from Fig. 9, we can find that the settling 13

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Fig. 12. Dynamic control behavior comparisons of alternative control schemes for facing throughput disturbances: (a) +20%; (b) −20%.

Fig. 13. Dynamic control behavior comparisons of alternative control schemes for facing feed composition disturbances: (a) +20%; (b) −20%.

distillate ratios, respectively. And the corresponding tuning procedures are successful for these two composition controllers. These control loops contain 3-min dead-times. The detailed control structure CS4 is presented in Fig. S4 of Supporting Information. Dynamic response results for throughput disturbances are shown in Fig. S5(a) of Supporting Information. The solid and dashed lines are for handling plus and minus 20% step changes in throughput, respectively. These disturbances are well handled with stable regulatory control achieved. Both product purities are rigorously going back to their initial

optimal reflux ratio). There are two pairs for controlling these two impurities. One is that methanol impurity is controlled by manipulating reflux ratio, and the water content is controlled by manipulating solvent flowrate (in this work, the solvent-to-feed ratio is selected as the manipulated variable). The failure of the tuning of the controller is occurred neither the composition controller action is selected to reverse or direct for methanol impurity control. Another is that the impurities of methanol and water are controlled by manipulating solvent-to-feed and reflux-to14

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differences in terms of product transient deviations and settling time between these two control schemes. For extractive column C1, the performance and effectiveness of dual-impurity control strategy is superior to that with single purity control since the former has the smaller product transient peaks and shorter settling time when system encounters plus and minus 20% step changes in throughput. There is no significant difference for product methanol composition in handling plus 20% step change in throughput, while the robustness of control structure with dual-impurity control is prevailed over that with single purity control in terms of product transient peak, settling time and fluctuating time when handling minus 20% change in throughput. Meanwhile, we can also find that the effectiveness of intensified control structure CS5 is superior to control scheme CS3 in extractive column C1 for handling 20% increases and decreases of feed composition in terms of product transient deviation, and settling time, while the performance is also similar for column C2. Therefore, the control scheme with dualimpurity control strategy works better than that with single purity control option.

steady-state design specifications. All temperatures are well controlled and are also quickly restored to their initial steady-state design values. Dynamic response results for feed composition disturbances are shown in Fig. S5(b) of Supporting Information. The solid lines are for feed acetone composition change from 50 to 60 mol% with the corresponding reduction of methanol composition in fresh feed stream, and the dashed lines are for 20% decreases with the corresponding augment of methanol composition in throughput manipulator’s stream. These perturbations are also well handled with stable regulatory control achieved. Both product purities are also rigorously restored to their initial steady-state design values. All temperatures are also well controlled and are quickly going back to their initial steady-state design values. The aforementioned results are indicated that this control scheme is robust and efficient for facing large throughput and feed composition disturbances. To further attenuate the oscillatory degree and reduce settling time of the process, the intensified feedforward action is applied, as shown in Fig. 10. The sensitive tray temperatures are controlled by manipulating the reboiler heat duty to bottoms flowrate (QR2/B1) and the compressor power to bottoms flowrate of extractive column C1 (W1/B1) ratios, respectively, for columns C2 and C1. The detailed control loops with their controlled and manipulated variables are illustrated in Fig. 10. Dynamic response results for handling plus and minus 20% step changes in throughput and feed composition are demonstrated in Fig. 11(a) and (b), respectively. The effective product quality control is achieved. The transient deviations of product compositions are reduced with respect to the control structure CS4. Besides, the oscillatory stabilization time for controlling Stage 30 temperature in solvent recovery column C2 is also dropped from 20 h to 15 h at facing feed composition disturbances. And the relay-feedback testing and Tyreus-Luyben tuning results of temperature and composition loops for control structures CS4 and CS5 are enumerated in Tables S4 and S5 of Supporting Information.

4. Conclusions Dynamic control behavior analysis was performed for this highly complex and interacting extractive distillation process with vapor recompression taking the separation of acetone and methanol using water as separating agent. The performance of conventional single-end temperature control structure in both columns was poor owing to the large product offsets. The effective product quality control was achieved by the two new developed control schemes, two-temperature control configuration with product composition measurements, when facing large (20%) disturbances in throughput and feed composition. And the dynamic control performance for control structure with dual-impurity control strategy in column C1 was superior to that with single purity control option in terms of transient product peaks and settling time whether handling throughput or feed composition disturbances.

3.2.3. Results and discussions The corresponding summaries and comparisons about dynamic control analysis of this complex configuration are shown in this section. The control strategies are classified to two categories including conventional single-end temperature control structure with holding refluxto-distillate and solvent-to-feed ratios constant and intensified control schemes with distillate composition(s) control. The performance of conventional single-end temperature control structure is inefficient and poor owing to the large product offsets. Given these results, the relevant control scheme with distillate composition control is investigated. The opposite effect is obtained according to the analysis of the effect of reflux ratio and solvent flowrate on distillate acetone impurities. The single purity control and dual-impurity control strategies are developed in the dynamic simulation. The dynamic control behavior comparisons for different control schemes with alternative options (single purity or dual-impurity control strategy) are illustrated in Table 2, which the evaluation indicator of integral absolute error (IAE) is utilized, representing the difference of the numerical integration (area) between the product purity of fluctuation and specification after an interference joined to system [36,38,42]. The result demonstrates that the performance of control structures with dual-impurity control option are better than that of counterparts with single purity alternative. As also observed in Table 2, the performance of dual-impurity control option is further improved by taking the feedforward action. The dynamic control behavior comparisons for these two differently intensified control options are visually illustrated in Figs. 12 and 13 for handling plus and minus 20% step changes in throughput and feed composition, respectively. Herein, the annotations (single purity control and dual-impurity control) of each graph are for dynamic responses of control structures CS3 and CS5 for this highly interacted process. These disturbances can be efficiently handled in these two strategies and all product purities are rigorously restored to their initial steady-state values, while there are some

Acknowledgement We are grateful to the comments and suggestions from the editor (Prof. de Haan) and the anonymous reviewers. These will have a great positive effect on my future research works by studying your comments carefully. Special thanks again to you for your good comments. Appendix A. Supplementary material Supplementary data to this article can be found online at https:// doi.org/10.1016/j.seppur.2019.116016. References [1] Y. Ma, P. Cui, Y. Wang, Z. Zhu, Y. Wang, J. Gao, A review of extractive distillation from an azeotropic phenomenon for dynamic control, Chin. J. Chem. Eng. (2018), https://doi.org/10.1016/j.cjche.2018.08.015. [2] S. Tututi-Axila, N. Medina-Herrera, J. Hahn, A. Gutierrez, Design of an energyefficient side-stream extractive distillation system, Comput. Chem. Eng. 102 (2017) 17–25. [3] K. Ma, M. Yu, Y. Dai, Y. Ma, J. Gao, P. Cui, Y. Wang, Control of an energy-saving side-stream extractive distillation process with different disturbance conditions, Sep. Purif. Technol. 210 (2019) 192–208. [4] L. Li, L. Guo, Y. Tu, N. Yu, L. Sun, Y. Tian, Q. Li, Comparison of different extractive distillation processes for 2-methoxyethanol/toluene separation: design and control, Comput. Chem. Eng. 99 (2017) 117–134. [5] W.L. Luyben, Control comparison of conventional and thermally coupled ternary extractive distillation processes, Chem. Eng. Res. Des. 106 (2016) 253–262. [6] L. Sun, Q. Wang, L. Li, J. Zhai, Y. Liu, Design and control of extractive dividing wall coumn for separating benzene/cyclohexane mixtures, Ind. Eng. Chem. Res. 53 (2014) 8120–8131. [7] Q. Zhang, M. Liu, C. Li, A. Zeng, Design and control of extractive distillation process for separation of the minimum-boiling azeotrope ethyl-acetate and ethanol, Chem. Eng. Res. Des. 136 (2018) 57–70. [8] Y. Chen, B. Yu, C. Hsu, I. Chien, Comparison of heteroazeotropic and extractive distillation for the dehydration of propylene glycol methyl ether, Chem. Eng. Res.

15

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Q. Zhang, et al.

bioethanol purification, Ind. Eng. Chem. Res. 24 (2015) 2208–2213. [26] L.C. Nhien, G. Kim, R. Andika, Y.A. Husnil, M.Y. Lee, Application of mechanical vapor recompression to acetone-methanol separation, Int. J. Chem. Eng. Appl. 3 (5) (2014) 215–218. [27] X. You, I. Rodriguea-Donis, V. Gerbaud, Reducing process cost and CO2 emissions for extractive distillation by double-effect heat integration and mechanical heat pump, Appl. Energy 166 (2016) 128–140. [28] W.L. Luyben, Principles and Case Studies of Simultaneous Design, John Wiley & Sons Inc, 2011. [29] I. Patrascu, C.S. Bildea, A.A. Kiss, Dynamics and control of a heat pump assisted extractive dividing-wall column for bioethanol dehydration, Chem. Eng. Res. Des. 119 (2017) 66–74. [30] W.L. Luyben, Improved plantwide control structure for extractive divided-wall columns with vapor recompression, Chem. Eng. Res. Des. 123 (2017) 152–164. [31] W.L. Luyben, Series versus parallel reboilers in distillation columns, Chem. Eng. Res. Des. 133 (2018) 294–302. [32] W.L. Luyben, Control of an azeotropic DWC with vapor recompression, Chem. Eng. Process. 109 (2016) 114–124. [33] I. Patrascu, C.S. Bildea, A.A. Kiss, Dynamics and control of a heat pump assisted azeotropic dividing-wall column for biobutanol purification, Chem. Eng. Res. Des. 146 (2019) 416–426. [34] M. Chen, N. Yu, L. Cong, J. Wang, M. Zhu, L. Sun, Design and control of a heat pump-assisted azeotropic dividing wall column for EDA/water separation, Ind. Eng. Chem. Res. 56 (2017) 9770–9777. [35] W.L. Luyben, Distillation Design and Control using Aspen™ Simulation, second ed., John Wiley & Sons Inc, 2013. [36] Q.J. Zhang, A.W. Zeng, X.G. Yuan, Y.G. Ma, Control comparison of conventional and thermally coupled ternary extractive distillation processes with recycle splitting using a mixed entrainer as separating agent, Sep. Purif. Technol. 224 (2019) 70–84. [37] W.L. Luyben, Vapor split manipulation in extractive divided-wall distillation columns, Chem. Eng. Process. Process Intensif. 126 (2018) 132–140. [38] Q.J. Zhang, C.X.D. Li, A.W. Zeng, Y.G. Ma, X.G. Yuan, Dynamic control analysis of partially heat-integrated pressure-swing distillation for separating a maximumboiling azeotrope, Sep. Purif. Technol. 230 (2020,) 115853. [39] Q.J. Zhang, M.L. Liu, C. Li, A.W. Zeng, Heat-integrated pressure-swing distillation process for separating the minimum-boiling azeotrope ethyl-acetate and ethanol, Sep. Purif. Technol. 189 (2017) 310–334. [40] W.L. Luyben, Control of an extractive distillation system for the separation of CO2 and ethane in enhanced oil recovery processes, Ind. Eng. Chem. Res. 52 (2013) 10780–10787. [41] W.L. Luyben, B.D. Tyreus, M.L. Luyben, Plantwide Process Control, McGraw-Hill, New York, 1999. [42] Q. Pan, X.Y. Shang, J. Li, S.T. Ma, L.M. Li, L.Y. Sun, Energy-efficient separation process and control scheme for extractive distillation of ethanol-water using deep eutectic solvent, Sep. Purif. Technol. 219 (2019) 113–126.

Des. 111 (2016) 184–195. [9] W.L. Luyben, I.L. Chien, Design and Control of Distillation Systems for Separating Azeotropes, John Wiley & Sons Inc, 2010. [10] J. Gu, X. You, C. Tao, J. Li, W. Shen, J. Li, Improved design and optimization for separating tetrahydrofuran-water azeotrope through extractive distillation with and without heat integration by varying pressure, Chem. Eng. Res. Des. 133 (2018) 303–313. [11] W.L. Luyben, Comparison of extractive distillation and pressure-swing distillation for acetone/chloroform separation, Comput. Chem. Eng. 50 (2013) 1–7. [12] Y. Wang, Z. Zhang, Y. Zhao, S. Liang, G. Bu, Control of extractive distillation and partially heat-integrated pressure-swing distillation for separating azeotropic mixture of ethanol and tetrahydrofuran, Ind. Eng. Chem. Res. 54 (2015) 8533–8545. [13] K.D. Brito, G.M. Cordeiro, M.F. Figueiredo, L.G.S. Vasconcelos, R.P. Brito, Economic evaluation of energy saving alternatives in extractive distillation process, Comput. Chem. Eng. 93 (2016) 185–196. [14] Y. Zhao, K. Ma, W. Bai, D. Du, Z. Zhu, Y. Wang, J. Gao, Energy-saving thermally coupled ternary extractive distillation process by combining with mixed entrainer for separating ternary mixture containing bioethanol, Energy 148 (2018) 296–308. [15] Y. Wu, P. Hsu, I. Chien, Critical assessment of the energy-saving potential of an extractive dividing-wall column, Ind. Eng. Chem. Res. 52 (2013) 5384–5399. [16] V. Plesu, A.E. Bonet Ruiz, J. Bonet, J. Llorens, Simple equation for suitability of heat pump use in distillation, Comput. -Aided Chem. Eng. 33 (2014) 1327–1332. [17] S. Feng, X. Lyu, Q. Ye, H. Xia, R. Li, X. Suo, Performance enhancement of reactive dividing-wall column via vapor recompression heat pump, Ind. Eng. Chem. Res. 55 (2016) 11305–11314. [18] J. Li, F.J. Zhang, Q. Pan, Y.L. Yang, L.Y. Sun, Performance enhancement of reactive dividing wall column based on self-heat recuperation technology, Ind. Eng. Chem. Res. 58 (2019) 12179–12191. [19] S. Feng, Q. Ye, H. Xia, R. Li, X. Suo, Integrating a vapor recompression heat pump into a lower partitioned reactive dividing-wall column for better energy-saving performance, Chem. Eng. Res. Des. 125 (2017) 204–213. [20] R. Li, Q. Ye, X. Suo, X. Dai, H. Yu, S. Feng, H. Xia, Improving the performance of heat pump-assisted azeotropic dividing wall distillation, Ind. Eng. Chem. Res. 55 (2016) 6454–6464. [21] I. Patrascu, C.S. Bildea, A.A. Kiss, Eco-efficient downstream, processing of biobutanol by enhanced process intensification and integration, ACS Sustain. Chem. Eng. 6 (2018) 5452–5461. [22] Q.J. Zhang, M.L. Liu, A.W. Zeng, Performance enhancement of pressure-swing distillation process by the combined use of vapor recompression and thermal integration, Comput. Chem. Eng. 120 (2019) 30–45. [23] H. Xia, Q. Ye, S.Y. Feng, R. Li, X.M. Suo, A novel energy-saving pressure swing distillation process based on self-heat recuperation technology, Energy 141 (2017) 770–781. [24] W.L. Luyben, Design and control of a pressure-swing distillation process with vapor recompression, Chem. Eng. Process. Process Intensif. 123 (2018) 174–184. [25] H. Luo, C.S. Bildea, A.A. Kiss, Novel heat-pump-assisted extractive distillation for

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