Energy Optimization of Pressure-Swing Azeotropic Distillation Systems

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Ind. Eng. Chem. Res. 2002, 41, 6082-6093

Energy Optimization of Pressure-Swing Azeotropic Distillation Systems Ahmad Hamad* Chemical Engineering Department, American University of Sharjah, United Arab Emirates

Russell F. Dunn† McSwain Engineering, Inc., 3320 McLemore Drive, Pensacola, Florida 32514

Global energy optimization strategies in steady-state pressure-swing distillation (PSD) systems were studied and analyzed using the minimum-boiling homogeneous azeotropic system of tetrahydrofuran (THF)-water. Using global energy optimization strategies can significantly reduce the energy consumption as opposed to local energy optimization strategies. Using the proposed approach reduced the energy requirements for the considered chemical plant including the THF-water PSD system, which reduced the energy requirements of the plant by more than 60%. The PSD system is part of the whole plant, and it should be dealt with accordingly. Introduction Azeotropic separation systems are frequently encountered in the pharmaceutical and specialty chemical processes, in particular to recover and recycle solvents. Azeotropes restrict the separation process and usually require additional operations to break the azeotropes and obtain pure products. Heterogeneous azeotropes can be assisted by phase splitting at low temperatures to have pure products. Homogeneous azeotropes can be overcome by several techniques including extractive and azeotropic distillation,1,2 reactive distillation,3,4 liquidliquid extraction,5 adsorption,6 membrane pervaporation,7 salt addition,8 and pressure-swing distillation (PSD). In this work, only PSD will be considered. PSD can be used to recover pure feed components if changing the pressure can alter the relative volatility of the feed components. This results in a change of the azeotropic composition and hence allows complete separation of the feed components. PSD has been the subject of many papers. Abu-Eishah and Luyben9 discussed the design optimization and dynamic behavior of a twocolumn azeotropic distillation system. In that work, several scenarios were studied to reduce the energy cost of the PSD system. Knapp and Doherty10 introduced the concept of adding a separating agent to separate pressure-insensitive azeotropes. Frank11 provides an overall design and thermodynamic model to separate azeotropes using PSD. It is worth mentioning here that swing and sensitive are used interchangeably in this paper. In previous work, energy required in PSD systems was optimized within the azeotropic system boundary independently of the whole plant. Such an approach would prevent the engineer from taking advantage of opportunities that may exist somewhere else in the plant to allow energy conservation design within the PSD system. In this work, we introduce and discuss * To whom correspondence should be addressed. E-mail: [email protected]. Phone: ++97165055964. Fax: ++97165055979. † E-mail: [email protected]. Phone: ++1 850-4840506. Fax: ++1 850-484-0508.

sensitivity analysis techniques to optimize the energy requirements of PSD systems using the concept of plantwide energy integration. Mathematical, graphical, and simulation techniques are used to gain insights from the process, simulate the process rigorously, and reduce the energy cost of the PSD system. Concepts of Energy Integration During the past decade, rising energy costs have required operating companies to look for ways to improve energy conservation. Energy integration is a systematic methodology that utilizes a fundamental understanding of the global energy utilization of the process to minimize the cost of energy through the design of heat-exchange networks or “HENs”. Industrial HENs are of particular importance because of their role in recovering process heat. An HEN is a network consisting of one or more heat exchangers that collectively satisfy the energy conservation task. Therefore, in most chemical process industries, it is necessary to synthesize cost-effective HENs that can transfer heat among the hot and cold streams (temperature conditions refer to the initial stream state). Moreover, temperature specifications for the hot and cold streams must be met, and at the design stage, a decision must be made regarding the use of a process stream or an external utility (e.g., steam, cooling water, etc.) to accomplish the required heat duty. Even in relatively simple situations, the problem of pairing and sequencing of exchanger streams becomes a large one and the use of systematic techniques is necessary. Figure 1 is included as a general representation of the HEN synthesis task. For a given system, the synthesis of HENs entails answering several questions including the following: Which heating/cooling utilities should be employed? What is the optimal heat load to be removed/added by each utility? How should the hot and cold streams be matched (i.e., stream pairings)? What is the optimal system configuration (e.g., how should the heat exchangers be arranged?, is there any stream splitting and mixing?, etc.)?

10.1021/ie020219h CCC: $22.00 © 2002 American Chemical Society Published on Web 10/30/2002

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diagram that does not constitute an overlap between the hot and cold composite streams represents the minimum amount of heating and cooling utilities that must be purchased to satisfy the energy needs of the process. As noted previously, the thermal pinch method has been summarized in greater detail in the literature by Shenoy,12 Linnhoff,13 Gundersen and Naess,14 and Douglas.15 Material Balance of a Pressure-Swing Distillation System PSD gets an advantage of pressure change to alter the volatility of the feed components to produce pure components. The PSD system for a minimum-boiling homogeneous azeotrope for a two-component system is illustrated in Figure 3. The distillate flow rates of both columns can be determined from the following equations (based on overall material balance) for targeted species i:

Figure 1. HEN synthesis.

Several graphical and mathematical approaches have been developed to minimize the energy cost of processes through the design of HENs. Of particular importance in this work is thermal pinch analysis. These methods have been reviewed by Shenoy,12 Linnhoff,13 Gundersen and Naess,14 and Douglas.15 A thermal pinch diagram can be used to minimize heating and cooling utilities of the process and gain insights on how to improve the process design. This approach will be used in this work to minimize the annualized cost of the azeotropic system for a particular feed. The thermal pinch diagram is a graphical representation of all individual process hot and cold streams. These streams are grouped together mathematically to form the “hot composite stream” and “cold composite stream”, respectively. The composite streams are a graphical representation of the collective process hot and cold streams. Figure 2 is included as a representative example of a thermal pinch diagram. The vertical scale represents the temperature changes that the process streams undergo when heated and cooled. The horizontal scale represents the heat duty associated with the heating and cooling processes. These streams can be moved in a horizontal direction, with the understanding that the hot composite curve must lie entirely to the left of the cold composite curve (these streams cannot cross). The closest point between the hot composite stream and the cold composite stream is referred to as the pinch point, which is termed this because it represents a thermodynamic (i.e., temperature) bottleneck for heat transfer. The horizontal overlap between streams represents the maximum amount of heat integration that may be achieved by transferring heat from hot process streams to cold process streams via HENs. The amount of the horizontal region on the thermal pinch

1 - xD2,i D1 ) mF,i xD1,i - xD2,i

(1)

1 - xD1,i D2 ) mF,i xD1,i - xD2,i

(2)

mF,i ) FzF,i

(3)

In the above equations, AZ + 1,i xD1,i ) x1,i

(4)

AZ + 2,i xD2,i ) x2,i

(5)

AZ AZ where x1,i and x2,i are the azeotropic compositions of the targeted species, i, at P1 and P2, respectively; 1,i and 2,i are the composition differences between azeotropic and distillate compositions in columns 1 and 2, respectively; and mF,i is the mass load of the targeted species, i, in the feed. Abu-Eishah and Luyben9 used 1,i and 2,i to reduce the energy costs of the tetrahydrofuran (THF)-water system. It is worth mentioning here that either i,j or 2,i should be negative, and the other should be positive. To illustrate this point, look at Figure 4 for the THF-water system. In this case, 1,THF should be negative and 2,THF should be positive. Negative 1,THF allows the distillate composition in the first column to move away from the azeotrope and hence enhance separation. Similarly, having 2,THF positive allows the distillate composition in the second column to move away from the azeotrope composition. To remove the confusion of signs of 1,THF and 2,THF, both will be assigned (throughout this paper) positive values by replacing the “plus” sign in eq 4 with a “minus” sign. Hence, eq 4 is rewritten as

AZ - 1,i xD1,i ) x1,i

(6)

Because xD1,i is originally greater than xD2,i (see Figure 4), xD2,i and xD1,i approach each other as 2,THF and/or 1,THF increases (eqs 5 and 6). The azeotropic composition is a function of the pressure of the column. Figure 5 shows the azeotropic composition of THF in the THF-water system.

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Figure 3. Generic representation of a two-column minimumboiling homogeneous azeotrope system. Figure 2. Thermal pinch diagram.

Figure 5 was developed using Hysys software and the Wilson model to predict vapor-liquid equilibrium data. The results are in good agreement with the theoretical and experimental data discussed by Abu-Eishah and Luyben.9 Optimization Parameters for the PSD Systems For specified product purities, there are several parameters that can be used to optimize the PSD system to reduce energy requirements and the total cost of the system. These parameters are highlighted in the following sections. Pressure. As the pressure of the column changes, so does the azeotropic composition. In turn, the flow rates of the feed to the second column (D1) and the recycle stream (D2) change. Changing the flow rates of D1 and D2 affects the heat duties of each column and hence the heat that can be used for integration. In addition, changing the pressure changes the overhead and the bottom temperatures of each column. This, in turn, also affects the heat available for integration. Distillate Composition. As can be detected from the above equations, the flow rates of D1 and D2 change as the distillate compositions change. The distillate compositions change as the pressure changes and as 1,i and 2,i change. At fixed 1,i, the flow rate of D1 (and hence D2) increases as 2,i increases. In the same manner, the D1 flow rate increases as 2,i increases at a fixed 2,i. These relationships are illustrated in Figure 6. Figure 6 shows how D1 increases as 1,i and 2,i increase until it approaches infinity (eq 1) as xD2,i

Figure 4. THF-water azeotrope at p ) 100 psig. Data generated by Hysys.

approaches xD1,i (see eqs 5 and 6). Figure 6 also indicates that D1 is minimum when the first column operates at lowest feasible pressure (azeotropic composition is high) and the second column operates at highest feasible pressure (azeotropic composition is low; see Figure 5). Low flow rates of D1 (and hence D2) generally may result in reduced costs. However, the optimum cost does not correspond to the minimum flow rates of D1 and D2, as will be illustrated later. Number of Trays. Increasing the number of trays would enhance the separation and reduce the energy consumption. Therefore, column cost optimization would


could in return save energy utilities at high temperatures. Heat Integration. Heat integration can be used to reduce the operating cost of the PSD system. There has been significant work in the area of heat integration of distillation systems. Overheads of some distillation columns were used to provide reboiler duties for other columns. Vapor recompression and feed preheating can be used to improve heat integration in distillation systems. Optimization Strategies for the PSD Systems

Figure 5. THF azeotropic composition vs P. Data generated by Hysys.

Figure 6. Three-dimensional representation of D1 as a function of 1 and 2.

require tradeoff between the number of stages (capital cost) and the energy cost (operating cost). Feed Tray. The location of the feed tray can have a direct impact on the energy requirements. This issue was discussed in more detail in other references.16,17 The feed composition affects the selection of the feed tray location. Feed Temperature. In many cases, increasing the feed temperature would reduce the reboiler duty. Preheating the feed to the column can be performed in many cases using low-temperature energy sources but

Local Optimization Strategies. Local optimization strategies focus on the PSD system independently of the rest of the plant. For example, energy integration of the two columns and preheating of the feeds to the two columns can be considered by using bottom or overhead products as the heating utility. The above-mentioned parameters are used to optimize the energy requirements of the system. Abu-Eishah and Luyben9 and Knapp and Doherty10 followed this approach to optimize the PSD systems. Later, this approach will be discussed through a case study and several findings will be illustrated. Insights from this approach will be used to extract global energy optimization opportunities. Global Optimization Strategies. In this work, the PSD system and energy requirements will be minimized through global strategies. This approach utilizes opportunities available in the whole plant to enhance optimization of the PSD system. The PSD system is part of the whole process and should not be designed independently. The boundaries within the chemical plant should be eliminated and the global energy flow/ requirements should be understood. Why? Consider Figure 7, where it is necessary to determine the temperature of the condenser that maximizes the profit of the recovery system. There are two outlet streams from this unit, gas and liquid. Each stream has its own destination and will have a cost for later processing. If the design is limited to the condenser, that is considering the rest of the plant as a black box. For this case, the profit vs temperature diagram provides a certain local optimum temperature where the profit is a maximum. In this case, only the cost of the condenser is considered. The effects of the condenser outlets on the rest of the plant are not taken into consideration. In addition, how the design of the condenser is influenced by other parts of the chemical plant is not addressed. However, if the design boundaries are extended to consider the entire chemical plant and the condenser is optimized based on overall plant objectives, then a better optimum temperature which provides better profit can often be identified (Figure 8). In this case, global plant insights and a fundamental understanding of the plant flow are used to optimize the temperature of the condenser. Dunn et al.18 explored the global energy integration potential of entire plant while also considering the mass separation effects of pressurization and/or depressurization on various, often simple, unit operations (ideal systems). Indeed, this should also be considered for the PSD system; however, PSD is a nonideal system that involves multiple, complex, process parameters that were summarized earlier in this paper. The design methods previously reported in the literature are insufficient for addressing the simultaneous optimization of PSD and global energy

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Figure 7. Condenser temperature vs profit. Generic problem.

integration problems. How the global energy optimization of the process can enhance the design and energy cost of the PSD system will be illustrated in the following case study. Illustrative Case Study: THF-Water System The THF-water example (reference example) that was discussed in work by Abu-Eishah and Luyben9 with slight changes (base case) is used to compare the results and illustrate the advantages of the global energy optimization. Figure 9 contains all data needed for our base case. The process was simulated using Hysys simulation software and the Wilson model. The energy requirements shown in Figure 9 are different from those reported in the reference example, for the following reasons. First, the feed flow rate in this example is higher by 1000 times to obtain more practical numbers and to have a better comparison in terms of heat duties. Second, the fresh feed to the first column was not preheated. The effects of feed preheating will be studied in this work. Also, the accuracies of the prediction models used in the reference example and this work are different. In our base case, the duties of reboilers and condensers and the pressure drop in the column were

Figure 8. Optimum condenser temperature from a global point view.

manipulated to obtain flow rates, compositions, and temperatures similar to those reported in the reference example. Hence, the results comparison in this work versus the reference example will be based on findings and trends and not on absolute values. It is assumed that the first and second product streams can be cooled to a minimum of 45 and 50 °C, respectively. The cold and hot streams are plotted on the temperature vs heat duties diagram as in Figure 10a, and the pinch diagram with a minimum approach temperature of 5 °C is represented in Figure 10b. 1. The overhead of the second column can be used to provide heat to the reboiler of the first column. 2. A heat pump can be used to recompress the overhead of the second column to provide heat to the reboiler of the same column.15 3. The second product stream can be used to provide heat to the reboiler of the first column. 4. Free heat is available from product streams 1 and 2 and the overhead of the first column that can be used to provide heat to other sinks in the process or to preheat the feed streams to the columns. 5. Heat sources from other parts of the chemical plant can be used to provide heat to the reboiler of the second column.


Figure 9. Base case study. Basis: 1 h.

Local Optimization Strategies In this section, the local optimization strategies to optimize the SPD system are discussed. Through this discussion, several points will be noted where global optimization can affect the solution. A. Heat Integration. As can be depicted from Figure 10b, the total heating utilities without considering feed preheating can be reduced by 7.9 MMBtu/h (8.3 × 106 kJ/h). The total heat and cooling utilities needed are 10.9 MMBtu/h (11.5 × 106 kJ/h) and 3.7 MMBtu/h (3.9 × 106 kJ/h), respectively. Figure 11 includes feed preheating. The fresh feed can be preheated by the first product stream, and the feed to the second column can be preheated by the second product stream. In this case, the total heat requirements can be reduced to 8.9 MMBtu/h (9.4 × 106 kJ/h) because all of the heating requirements for the first column can be provided by the overhead of the second column. B. Pressure of Columns. To study the affect of pressure change in each column, the pressure is fixed in one column and continually altered in the other. To study only one variable at a time, the following fixed values are used:

1,THF ) 0.011 2,THF ) 0.011 The azeotropic composition is a function of the pressure of the column. A comparison of the different pressures is made in two different ways:

Figure 10. (a) Hot and cold streams of the base case. (b) Pinch diagram of the base case.

1. Feed preheating is not used, and heat integration between the second column’s overhead and the first column’s reboiler is considered. 2. Feed preheating using the product streams is considered in addition to the heat integration considered in part 1. A comparison is made based on the total heat required for the reboilers. At this moment, the cooling utility cost is assumed to be minimal compared to the heating utility cost (e.g., the unit cost of cooling water is often a fraction of the unit cost of steam). Hence, the total heat required is calculated as follows:

QR,total ) QR,1 + QR,2 - min(QR,1, QC,2) QR,1 and QR,2 are the heat duties for the first and second reboilers. QC,2 is the heat duty of the second condenser. The “min” function is used to denote the maximum potential heat for integration. a. Affect of the Pressure on Heat Requirements without Feed Preheating. The pressure of the second column was fixed at 100 psig (791 kPa), and the pressure in the first column was varied. The total heat

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Figure 13. Total heat requirements vs pressure of the second column without feed preheating.

Figure 11. Base case study with feed preheating. Basis: 1 h.

Figure 12. Total heat requirements vs pressure of first column.

required versus the pressure of the first column is presented in Figure 12. Figure 12 indicates that as the pressure of the first column increases so does the total heat duty needed in the system. The approach of Abu-Eishah and Luyben9 is followed when choosing the pressure of the first column to be -7.928 psig (350 mmHg, 46.7 kPa). This will guarantee an overhead temperature in the first column that will allow the use of cooling tower water (∼32 °C) to perform the condensation task. Next, the pressure of the second column is changed while keeping

the pressure in the first column at 350 mmHg (46.7 kPa). There is a trend, as can be seen from Figure 13, which indicates that there is an optimum value for the pressure of the second column between 100 and 150 psig (791 and 1136 kPa). However, before a conclusion is made on the effect of pressure on the system, the following study is needed to consider feed preheating affects on pressure selection. b. Affect of the Pressure on Heat Requirements with Feed Preheating. In this exercise, feed preheating is considered. The first product stream preheats the fresh feed to the first column with a minimum temperature difference of 10 °C, to avoid vapor formation in the feed stream to the column. Likewise, the second product stream preheats the feed to the second column with a minimum temperature difference of 5 °C, to maximize heat recovery from the product stream. The following figure shows the total heat required versus the pressure of the second column. From Figure 14, it is noted that the total heat duty decreases as the pressure increases. This behavior can be attributed to the fact that as the pressure in the second column increases so does the heat exchanged between the second product stream and the feed to the second column, as illustrated in Figure 15. However, before any conclusions are drawn and the results are discussed, it is very important to plot the overhead and bottom temperatures of the second column as a function of the pressure in the column, as presented in Figure 16. Figure 16 provides an indication of the type of utility needed to provide the reboiler of the second column. For example, at 50 psig (446 kPa), a saturated steam at a pressure as low as 25 psig (274 kPa) could be used; however, at 300 psig (2170 kPa), a saturated steam at a pressure of around 300 psig (2170 kPa) is needed. Also, Figure 16 shows that the opportunity to use vapor recompression in the second column improves as the pressure decreases. Highlights of the Results from This Study. 1. Before determination of the optimum pressure, the following factors should be considered: (a) heat integra-


Figure 16. Overhead and bottom temperatures of the second column vs pressure. Figure 14. Total heat requirements vs pressure of the second column with feed preheating.

Figure 17. Total heat requirements vs 2,THF at fixed 1,THF values.

Figure 15. Pressure of the second column vs heat exchanged between the second product and the feed to the second column.

tion within the system; (b) feed preheating opportunities; (c) the material of construction (beyond the scope of this work); (d) the cost of equipment including the heat exchangers and heat pumps (beyond the scope of this work). 2. The following points will illustrate the importance of global energy optimization: (a) The quality and quantity of the system heat that can be used from or supplied to other parts of the plant would change as the pressure changes. (b) The quality and quantity of heating and cooling utilities would change as the pressure changes. This has a direct impact on the cost of the external utilities in the plant. (c) The design of the PSD should be performed based on plant requirements. C. Distillate Compositions. The pressure of the first column is fixed at -7.928 psig (46.7 kPa) and the

second column at 150 psig (1136 kPa) to study the effect of the distillate composition change. A pressure of 150 psig is used for the second column because this pressure lies within the optimum pressure range whether feed preheating is considered or not; 100 psig also can be used. Because fixed pressures are employed (and hence fixed azeotropic compositions), the values of 1,THF and 2,THF are changed to change the distillate compositions. One variable will be analyzed at a time. a. Fixed E1,THF. At -7.928 psig (46.7 kPa) and 150 psig (1136 kPa), the THF azeotropic molar compositions are 0.875 and 0.615, respectively. Changing 1,THF will change the compositions and the flow rates of the recycle stream to the first column and the feed stream to the second column, as can be illustrated from the previously mentioned equations. In this study, only the case using feed preheating will be considered. Figure 17 shows the total heat required versus 2,THF at constant 1,THF (0.011, 0.02, 0.05). Figure 17 shows that the heat duty has an optimum range between 2,THF of 0.02-0.07. The heat duty does not change significantly in this range. Fixed E2,THF. Another study was done at fixed 2,THF of 0.03 to find out how the total heat duty changes as 1,THF changes.

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Figure 18. Total heat requirements vs 1,THF at (a) 2,THF ) 0.03 and (b) 2,THF ) 0.08.

Figure 18 shows that the total heat duty has an optimum range for 1,THF of around 0.01 and then it starts to increase in a linear fashion as 2,THF increases. Highlights of Results of This Study. 1. The change of the distillate composition has a minor impact on the total heat duty requirements when 1,THF and 2,THF are small. 2. There is an optimum region of the distillate composition where the total energy requirement is essentially less than 1 MMBtu (1 × 106 kJ). Hence, using any composition within this region should be close enough to the global energy points. 3. The following points will illustrate the importance of global energy optimization: (a) The quantity of the system heat that can be used from or supplied to other parts of the plant would change as the distillate compositions change. (b) The design of the PSD should be performed based on plant requirements. D. Number of Trays. The values of 1,THF and 2,THF will be fixed at 0.01 and 0.03, respectively, to study the effect of the number of trays. a. First Column at 15 Trays. The number of trays of the first column is fixed at 15. The number of trays of the second column varied to study the impact on the total heat required. Figure 19 shows how the total heat changes as a function of the second column trays. The figure shows that the total heat duty reduces as the number of trays increases until it reaches what seems to be a fixed value at around 30 stages. The reduction in the total heat duty for the system above 20 stages is negligible. b. Second Column at 20 Trays. The number of trays of the second column is set at 20, and the results of how the total heat duty changes as a function of the trays in the first column are presented in Figure 20. Figure 20 shows that the change in the total heat duty requirement is negligible when the number of trays of the first column is 15 or above. Before the highlights of the results of this study are discussed, it is important to study how the heat duty of each reboiler changes as a function of the number of trays in each column. Figures 21 and 22 show that the heat duties of reboilers and condensers become constant as the number of trays in each column increases. E. Feed Tray. Changing the feed tray to the second column within the range of 10-13 does not have a

Figure 19. Total heat requirements vs number of trays of the second column.

Figure 20. Total heat requirements vs number of trays of the first column.

considerable effect on the heat requirements in the column. Outside this range, the heat duty of the reboiler and the condenser would jump by considerable amounts. For the first column, feeding the fresh feed in trays 3-7 does not have a considerable effect on the heat requirements of the column. The recycle stream should be fed to trays 3 or 4 to have a feasible separation. For more information about the rigorous feed tray location, the reader is referred to refs 12 and 13. From the above discussions, it seems that our PSD system should be designed as follows: 1. Column 1 should have 15 trays. 2. Column 2 should have 20-25 trays. 3. The feed tray in the second column should be in the range of 10-13.


Figure 21. Individual heat requirements vs number of trays of the second column. Figure 23. Temperature and heat duty ranges for each heat exchanger. Table 1. Streams in the Illustrative Example stream

supply temp, °C

target temp, °C

absolute heat duty, MMBtu (1 × 106 kJ)

C1 H1 H2

180 200 140

182 190 139

7 (7.4) 3 (3.2) 8 (8.4)

Global Optimization Strategies

Figure 22. Individual heat requirements vs number of trays of the first column.

4. The feed tray of fresh feed in the first column should be in the range of 3-7. 5. The feed tray of the recycle stream should be 3 or 4. 6. 1,THF is around 0.01. 7. 2,THF is around 0.03. 8. The pressure in the first column should be as low as technically feasible, especially if feed preheating is considered. 9. The pressure in the second column should be as high as technically feasible when feed preheating is considered. It is very important here to clarify that the goal from this sensitivity analysis is not to determine the global optimum configuration but rather to identify suboptimal configurations where the design will be within the global optimum range. In the remaining part of this paper, a discussion is presented concerning how the optimal design parameters would change as we optimize the PSD system globally within the whole plant.

Until now, we have limited the scope to the two distillation columns and their product streams to optimize the PSD system. How would the PSD system design change if the boundaries within the plant were removed and the plant as a whole was considered in the design phase? According to the previous studies, Figure 23 shows the potential range of operation for each column in terms of the temperature and heat duty. The operating temperatures of the first and second columns could be as low as 79.6 and 120 °C, respectively, and as high as 130.4 and 234 °C, respectively. These temperatures are applicable under tested pressures. This means that the location of these streams on the overall plant pinch diagram can be changed to a better fit with the other streams of the plant. The design parameters used earlier to study local optimization strategies can be adjusted to maximize the heat exchanged with the overall plant streams. Insightful brain storming can be employed to develop ideas on how to select these parameters. The following example is designed to better illustrate how the PSD system design parameters are selected when global energy optimization strategies are considered. Illustrative Example Suppose that a chemical plant exists that includes the streams indicated in Table 1. Each stream is listed with its supply and target temperatures and total cooling/ heat duty. The pinch diagram for this plant is shown in Figure 24. From the pinch diagram with a minimum approach temperature (∆T) of 5 °C, the minimum hot utility and cooling utility requirements are 4 MMBtu (4.2 × 106 kJ) and 8 MMBtu (8.4 × 106 kJ), respectively.

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Figure 26. Pinch representation for the whole plant including the PSD system.

Figure 24. Pinch representation of the illustrative example without the PSD system.

Figure 25. Pinch diagram superimposed onto the range diagram.

Now, let us superimpose Figure 24 onto Figure 23 to study how the PSD system fits with the overall picture of energy in the chemical plant. Because heat can only be transferred from hot streams to cold streams (downward in Figure 25), the following design insights can be brainstormed from Figure 25: 1. There is a potential to transfer heat from condenser 2 to other parts of the plant. 2. There is a potential to transfer heat to reboiler 2 from other parts of the plant. 3. There is a potential to transfer heat to reboiler 1 from other parts of the plant. 4. Condenser 1 could be eliminated from the analysis. Because the temperature of condenser 2 is always lower than the temperature of reboiler 2, points 1 and 2 cannot both be achieved. Point 1 indicates that reboiler 2 should be operated at high pressure, which in turn

means that high-pressure steam is needed as a hot utility. Because high-pressure steam is expensive, it appears to be more beneficial to ignore point 1 and the heat released from condenser 2 can be utilized to provide heat to reboiler 1. This indicates that point 3 can be ignored. Hence, point 2 will be the focus. This suggests that the PSD design should be based on the following points: (a) The heat duty of condenser 2 should provide all or most of the heat duty of reboiler 1. (b) The second column should run at a pressure low enough so that we can use some of the wasted heat in the plant. Using the information from “local optimization” studies, the following design parameters are used to achieve these points: 1. The pressure in the first column is 350 mmHg (46.7 kPa). 2. The pressure in the second column is 50 psig (446 kPa). 3. 1,THF and 2,THF are 0.01 and 0.03, respectively. 4. The design includes feed preheating by product streams. 5. Column 1 has 15 trays. 6. Column 2 has 20 trays. Using these parameters, the following pinch diagram (Figure 26) is developed. The following scenarios are discussed to illustrate the effectiveness of the proposed integration approach in reducing the cost of energy in the plant. 1. If the PSD system is designed independently using the above parameters, then the PSD system would require 5.84 and 5 MMBtu/h of heating and cooling utilities, respectively. Hence, the total plant requirements would be 9.84 and 13 MMBtu/h of heating and cooling utilities, respectively. 2. If the PSD system is designed based on the solution developed by Abu-Eishah and Luyben,9 with following design parameters are used when generating this solution: (a) The pressure in the first column is 350 mmHg (46.7 kPa). (b) The pressure in the second column is 150 psig (1136 kPa). (c) 1,THF and 2,THF are 0.018 and 0.015, respectively. (d) The design includes feed preheating by product streams.


(e) Column 1 has 15 trays. (f) Column 2 has 15 trays. The heating and cooling utilities would be 10.25 and 13.4 MMBtu/h, respectively. The above scenarios show how the proposed approach could reduce energy utilities by more than 60% in this case study. It is worth reiterating here that this is not the global solution, but it is within its range. There are other solutions that could be used to give close or similar utility requirements. Usually process design engineers in the industry would prefer these types of sensitivity studies as opposed to searching for global optimum solutions through rigorous mathematical formulation. This work applies practical optimization in a dynamic and creative methodology that involves brain storming, exploring alternatives, and applying systematic process integration tools. This approach shows how to design and optimize PSD systems from a global point view instead of limiting the scope of design to the PSD system. Conclusion Using global energy optimization strategies reduced the energy consumption of the THF-water PSD and the whole chemical plant by more than 60%. Sensitivity analysis and optimization studies were used to show the benefits of eliminating the boundaries within the plant to further reduce the energy consumption of the PSD system. Local optimization studies were used to develop potential operation conditions of the PSD system. Then, the PSD system is incorporated within the rest of the plant. The design parameters of the PSD system are then selected to optimize energy requirement for the whole plant including the PSD system. The PSD system was modeled using Hysys software, and graphical thermal pinch techniques were used to illustrate graphically the potential benefits of this work.

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Received for review March 26, 2002 Accepted September 24, 2002 IE020219H

Energy Optimization of Pressure-Swing Azeotropic Distillation Systems

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