I n d . Eng. Chem. Res. 1987,26, 2195-2204 0 25
10
08
g
-k0
06
-
-
h
e i
04
02
0
2
4
6
8 1 0 set
2
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20
08
&O 15
06
0 10
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0 05
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-
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16 Set
Figure 9. Circulation time distributions of pill and liquid liquid volume, 19 m3; two impellers; gas rate, 2.6 cm/s; detection with aerials in compartments 2 and 4.
+
2195
for interpreting our measurements. Such a model contains a large number of ideal mixers in series and parallel and is likely to be capable of fitting both short and long circulation times. After some modifications, the presented model can be used for the calculation of gas holdup, residence time distribution in solid-liquid dispersions, etc.
Acknowledgment The mechanical construction of the radio pill and the aerials was designed and developed by H. van Dam. The electronics were designed and built by L. P. de Meulmeester, who made a major contribution to the measurements.
partments 2 4 has been calculated. Finally the circulation time distribution of the liquid was calculated in the same way by setting the rate of fall to zero. The observed and the calculated distributions of the pill as well as the calculated distributions of the liquid are given in Figures 3-9.
Nomenclature fi+j = frequency with which the pill, being in compartment i, moves toward compartment j , s-l f, = frequency for a pill leaving a compartment with liquid flow, s-1 f, = frequency for a pill leaving a compartment by falling out,
4. Discussion The simple five-compartments model gives a good fit for the tail of the circulation time distribution of the pill. In all cases, the fit for the short circulation times is not as good. There is a time lag in the beginning of the observed pill circulation time distribution curves, which is not explained by the model. Apparently the assumption of the liquid phase in each compartment being ideally mixed is too simple. The pill, having left a detection compartment, has at least a minimum residence time in the next compartment before reentering the same aerial compartment. In all experiments, the observed pill circulation time distribution shows one or more peaks; this will also be caused by the nonideality of the mixing in the various compartments. In our model, we assume that the probability for the pill to leave a compartment by falling out or by following the liquid flow is independent of the path the pill has been following before entering the compartment. For a nonideally mixed system, this will not be completely true. The shape of the observed distribution curves is the same as the shape of the curves reported by Mann et al. (1981). After including two impellers and a rate of fall for the pill, their structured stochastic flow model may be useful
Hi= height of compartment i, m
S-1
p , = falling probability of a pill q’ = probability that the pill is present in compartment i QCJ= liquid circulation capacity of an impeller, m3/s t p time, s tcf = time between two successive passages of a liquid element through compartment i, s tc,: = time between two successive passages of the pill through
compartment i, s v , = superficial gas velocity, m/s v , = rate of fall of a pill within a compartment, m/s V = compartment volume, m3 Greek Symbols t
,= volumetric liquid fraction = mean residence time of the pill in compartment
TI,
T{
i,
s
= mean residence time of a liquid element in compartment
i, s T:
= mean time for the pill to fall out of a compartment, s
Literature Cited Barneveld, J. v.; Oosterhuis, N. M. G.; Pragt, J. J.; Smit, W. Znd. Eng. Chem. Res. 1987, preceding paper in this issue. Mann, R.; Mavros, P. P.; Middleton, J. C. Trans. Znst. Chem. Eng. 1981,59, 271-278. Received for review April 21, 1986 Revised manuscript received May 19, 1987 Accepted June 11, 1987
Screening of Process Retrofit Alternatives Wayne R. Fisher, Michael F. Doherty, and James M. Douglas* Department of Chemical Engineering, University of Massachusetts, Amherst, Massachusetts 01003
A systematic procedure for developing and screening process retrofit opportunities is presented. The procedure considers both modifications in the structure of the flow sheet and in equipment sizes for a fixed flow sheet. Also, a systematic way of identifying “bottlenecking” equipment is described. The results of case studies indicate that retrofitting to reduce raw materials costs often is much more important than retrofitting to save energy. Expert systems and “intelligent” computer codes have the potential of making a dramatic impact on the practice of chemical engineering. As a minimum, we expect that solution strategies for various types of problems will be combined with hierarchies of algorithms to make it possible 0888-5885/87/2626-2195$01.50/0
to explore more process alternatives quickly and inexpensively. A t present, “knowledge engineers” attempt to capture solution strategies by interviewing experts and watching them work. However, it is possible to develop hierarchical, “top-down”, “least-commitment” strategies 0 1987 American Chemical Society
2196 Ind. Eng. Chem. Res., Vol. 26, No. 11, 1987
that provide efficient solutions in a variety of other ways. Westerberg (1986) recently reviewed four strategies of this type that have been proposed for synthesizing process flow sheets. In this paper, we describe a solution strategy for retrofit problems. There has been rapidly growing interest in process retrofits in recent years. By retrofitting we mean making minor changes in the structure of a flow sheet and/or some equipment sizes in order to (a) significantly reduce operating costs, (b) increase the capacity of the process, (c) process new feedstocks, and/or (d) incorporate a new technology (i.e., a new catalyst, a new membrane separator, etc.). In part, this recent interest may be attributed to the impact of changing economic forces on the chemical industry, and in part it may be attributed to the great success of applying the new heat integration technology to retrofit situations. That is, Imperial Chemical Industries (Boland and Hindmarsh, 1984) and Union Carbide (Linnhoff and Vredeveld, 1984) have shown that often 30-5070 savings in energy are possible even in retrofit applications. Other studies indicate similar trends (Steinmetz and Chaney, 1985; Witherell and Linnhoff, 1985). Hence, an incentive for retrofitting has been clearly established. The very successful energy integration studies discussed above have been based on the process flows that exist in the plant. However, the design variables that fix the process flows (e.g., conversion, molar ratio of reactants, purge composition, etc.) normally involve economic tradeoffs which balance incremental raw material costs due to selectivity losses of reactants to byproducts against incremental recycle costs. Of course, the recycle costs are dependent on the heat-exchanger network so that the problems of finding the optimum process flows and heat-exchanger network are coupled. The coupling of the optimum process flow problem with the optimum energy integration implies that retrofit studies which only consider energy may not give the best retrofit design. For example, if an energy retrofit study indicates that large energy savings are possible and that these energy savings have a significant effect on the recycle costs, then it should be possible to convert some, or possibly all, of the energy savings into raw material savings by increasing the recycle flows. For a large number of processes, raw material losses to byproducts are much more important than energy costs, and therefore there is great incentive for developing a strategy of process retrofits that considers process flows, as well as energy.
Goals of This Research Since a retrofit analysis requires looking at the complete plant, it is a large and complicated problem. Thus, in order to minimize the engineering effort required to identify the most important retrofit opportunities, it would be desirable to have approximate methods available that could be used for screening purposes. Moreover, it would be highly desirable to develop a general, systematic procedure based on these shortcut techniques, which could provide the basis for an interactive computer code that could be used to screen retrofit opportunities. Our goal in this research was to establish a systematic procedure of this type. Fortunately, many of the tools that we have developed for the preliminary design of new processes are also useful for retrofit studies. A Systematic Procedure for Retrofitting The retrofit procedure that we describe below has been developed in terms of a hierarchical set of problems. This hierarchy corresponds to establishing a series of bounds
Table I. Retrofit Screening Strategy 1. Use an operating cost diagram to identify the incentive for raw materials and energy savings. 2. Determine the incentive for completely replacing the existing plant. a. Estimate the optimum values of the design variables with current costs. b. Identify important process alternatives. 3. Screen the process alternatives, and find the best flow sheet if we completely replace the plant. 4. Modify the existing equipment sizes for the existing flow sheet or a structural alternative. a. Eliminate the existing heat exchangers, but retain the heating and cooling ultilities costs. b. Identify the dominant operating variables. c. Identify the equipment that constrains the dominant operating variables. d. Remove the equipment constraints by adding incremental equipment capacity until the incremental investment costs balance the incremental savings in operating costs. e. Develop a new heat-exchanger network for the process. f. Modify the new heat-exchanger network in order to use as much existing heat-exchange equipment as possible. g. Reoptimize the process flows and heat-exchanger network. 5 . Refine the retrofit calculations.
and/or targets, which make it possible to terminate the retrofit study early if there is not a sufficient economic incentive to justify additional effort. Thus, the hierarchy corresponds to a “top-down”,“least commitment” strategy, and consists of the five levels given in Table I. Each step in the hierarchy is discussed in more detail below. 1. Identify the Incentive for Raw Material and Energy Retrofitting. The first step in our procedure is to prepare an operating cost diagram. That is, all the significant operating costs are attached to stream arrows on the current process flow sheet. In particular, we show the following. a. We show the cost of steam or fuel for all reboilers, furnaces, preheaters, etc. b. We show the cost of electric power (or steam) for all compressors and blowers. Normally, we neglect the operating costs of pumps if they are less than 10% of the most expensive operating cost; Le., we only want to consider the most important operating costs in order to simplify the screening calculations. c. We show any other significant energy-related operating costs. d. We show the cost of raw materials in excess of the stoichiometric requirements to achieve the existing production rate (we use the maximum value if the production rate is changing). For complex reactions, the raw material requirement will depend on the selectivity losses to byproducts and the purge losses that exist in the current plant. e. We show the credit associated with any byproduct streams that are sold or are used as fuel and the pollution treatment cost of all waste streams. This operating cost diagram is based on the cost diagrams that Douglas and Woodcock (1985) describe for process synthesis and the quick screening of process alternatives. From an inspection of this operating cost diagram, we can quickly evaluate the maximum incentive for making process modifications in order to reduce the raw material losses to byproducts, the energy costs, or both. For complex reactions, the raw material losses are usually dominant. The relative value of the coproducts dictates the desired operation of the process. In some instances this corresponds to a single valuable product balanced against byproducts which have either waste or fuel value. In other cases, there will be several products (e.g., glycols), each of differing value. However, if there
Ind. Eng. Chem. Res., Vol. 26, No. 11, 1987 2197 is only small potential for raw material savings, but a large potential for energy savings, then we bypass the remainder of this procedure and just focus on energy retrofitting by using the new energy integration procedures that have been published recently, i.e., Linnhoff et al. (1982), Boland and Hindmarsh (1984), Linnhoff and Vredeveld (1984), Tjoe and Linnhoff (1986). 2. Determine the Economics of Replacing the Whole Plant for the Existing Flow Sheet. One option we have is to replace the complete plant. We want to evaluate this option (assuming we can do it quickly) both to provide a benchmark for our retrofit analysis and also to evaluate the costs and profitability position of our competitors if they built a process like ours. In the next step, we will also consider the cost of building a new plant that corresponds to the best process alternative. We can use the hierarchical decision procedure described by Douglas (1985) to estimate the optimum design of a new plant. This procedure usas approximate material and energy balances, as well as shortcut equipment and cost models, so that an estimate of the optimum design can be obtained, within 2 days to 1week. An interactive computer program developed by Kirkwood et al. (1987) that is based on this procedure makes it possible to complete a conceptual design in about 1 h. Since the hierarchical design procedure is systematic, it makes it a simple matter to generate a list of process alternatives. These are the same alternatives that we want to consider for structural modifications of the process flow sheet in our retrofit analysis. Thus, using the hierarchical design procedure to redesign the existing plant has four positive contributions: (a) it helps the user to quickly understand the process, (b) it provides a current picture of the design economics, (c) it generates a list of process alternatives, and (d) it estimates the optimum values of the most significant design variables with current costs. Of course, if the new values of the optimum design variables and costs are close to the existing values, then there is little incentive for continuing to consider the retrofit of the process. 3. Screen the Process Alternatives for a New Design. A procedure for the quick screening of process alternatives for a new design has been presented by Douglas and Woodcock (1985). Starting with a base-case (optimum) design, the procedure allocates the costs of heat exchangersto the process streams based on the reciprocals of the heat-transfer coefficients of each stream (Townsend and Linnhoff, 1984). Then, costs are allocated to the fresh feed streams, gas recycle streams, and liquid recycle streams based on the process flows and heat loads. Next, the effect that changing the structure of the flow sheet has on each of the process flows is estimated, and the effects of these flow rate changes on the fresh feed, gas recycle, and liquid recycle costs are calculated. For some alternatives, e.g., an equipment replacement, the process flows are not changed, but a comparison between alternatives is straightforward. The goal of this rough screening analysis is to estimate the order of magnitude of savings obtained by using various process alternatives without having to redesign the process. In other words, we attempt to find the incentive to go through the hierarchical design procedure again for the various alternatives. We repeat the hierarchical design procedure for the most promising alternatives in order to estimate the optimum design conditions for each alternative. By comparing the optimum design for a new plant by using our existing flow sheet with the optimum design of the best alternatives, we generate a list of promising
x (conversion)
Figure 1. Typical cost tradeoffs for each design variable in a flow sheet.
modifications for the existing flow sheet that should be considered in a retrofit analysis. Of course, if a retrofit alternative does not use an existing piece of equipment in the plant, we must still include the continuing payment for that equipment in our retrofit economics. Furthermore, if our most promising alternative requires changing the process flow rates, we might encounter equipment constraints in our existing plant. In order to better understand the nature of these equipment constraints, it seems desirable to deviate from our retrofitting procedure to review the difference between designing to achieve the minimum total annual cost (i.e., the sum of annualized capital and operating cost) vs. attempting to retrofit a design to achieve the minimum operating cost. Optimum Design vs. Minimizing Operating Costs. Most design problems have some processing constraints. For example, if the reactor temperature exceeds a certain value, undesirable side reactions may take place. Similarly, if the molar ratio of reactants is less than a certain value, undesirable side reactions, such as coking, may occur. If we were willing to undertake more detailed kinetic modeling, we could treat these situations as optimum design problems, but normally it is much simpler to treat them as constraints. We can satisfy these constraints by removing one of the optimum design variables (degrees of freedom) from the design problem (by using variable elimination, for example). For each of the remaining design variables, we normally find that there is a minimum (annualized) capital cost, a minimum operating cost, and a minimum total annualized cost (annualized capital plus operating cost); see Figure 1. We do not design to obtain the minimum operating cost because the capital investment is too high, nor do we design to obtain the minimum capital cost because the operating costs are too high. Thus, we trade off annualized capital vs. operating cost, and we design for the minimum total annual cost. Of course, in many cases this optimum design is not operable when disturbances enter the plant, and in these situations we must include some overdesign. This problem of optimal overdesign to accommodate disturbances is discussed elsewhere (Fisher et al., 1987). As soon as the plant is built, we have spent our total capital investment. From that time on, we would like to obtain our desired production rate and product purity, as well as satisfy the process constraints, with the minimum operating costs. Thus, it is always desirable to change the operating variables away from their optimum steady-state design settings in the direction that minimizes operating costs; see Figure 1. When we change the values of these operating variables, we normally encounter equipment constrainsts because the equipment sizes were fixed by the best capital vs. operating cost tradeoffs. If we attempt to
2198 Ind. Eng. Chem. Res., Vol. 26, No. 11, 1987
overdesign the equipment beyond that needed to make the process operable in the face of disturbances (see Fisher et al. (1987)), the incremental capital cost will exceed the savings in operating costs. However, both raw materials costs and utilities costs change with time. As these costs change, the location of the minimum operating cost and minimum total annual costs will change. Thus, even if the original plant corresponded to an optimum design (which is seldom the case), situations can arise where the expenditure of incremental capital can be much less than the corresponding savings in operating costs as a particular operating variable is changed. For these cases, we expect that the current value of an operating variable in the existing plant will be at an equipment constraint, since this policy corresponds to the most profitable operation. We call the equipment that constrains changing an operating variable to a lower operating cost condition bottlenecking equipment. It should be noted that not all operating variables are constrained, and there might be some optimization problems that involve tradeoffs only between operating costs. Hence, we distinguish between process constraints (which must always be satisfied), constrained operating variables (where the constraint can be removed by changing the existing sizes of bottlenecked equipment), and unconstrained operating variables (where we want to adjust the operating variable in order to minimize the operating costs). 4. Modify Equipment Sizes for the Existing Flow Sheet or a Process Alternative. In order to modify process equipment sizes for a given flow sheet alternative, we proceed through the following levels. (4a) Eliminate the process heat exchangers, but retain the heating and cooling utilities costs. (4b) Identify the most significant operating variables. (4c) Identify the piece(s) of equipment that constrains the significant operating variables. (4d)Remove the equipment constraints by adding excess capacity until the incremental savings balance the incremental investment. (4e) Energy integrate the process without regard to the existing heat exchangers. (40 Modify the new heat-exchanger network (if desirable) to accommodate the use of existing heat exchangers. (4g) Reoptimize the flows and heat-exchanger network (since they are coupled) if the retrofit study is to be continued. Each of these levels will be discussed below. Level 4a. Normally the heat-exchanger network depends more strongly on the process flows than vice versa. Moreover, if we change the process flows with a fixed heat-exchanger network, we will almost always encounter equipment constraints. Therefore, to simplify the problem, we begin by eliminating the existing heat-exchanger network, except for the hot and cold utility operating costs. Level 4b. In order to determine the most important operating variables, we use the rank-order parameter, rj, presented by Fisher et al. (1985). This is defined as
where rj is the rank-order parameter for variable j , x j is the operating variable, a f i / a x j are the components of the total operating cost gradient, and Axj is a scaling factor. The scale factor ( k j ) is chosen on physical grounds as the maximum range of the operating variable within which we expect to observe the optimum. Some typical values are given in Table 11.
Table 11. Scale Factors for ODtimization Analysis tvDe of oDtimization reflux ratio in distillation solvent flow in gas absorbers fractional recoveries in columns approach temp in heat exchangers reactor conversion reactor temp reactor pressure molar ratio of reactants
ranee of the oDtimum 1.0 R / R m < 1.3 1.2 < L/mG < 1.6
scale factor 0.3 0.4
0.99 < f < 1.0
0.01
3O
F
< AT < 25 O F
0 < x < 1 or xeq obtain the range from the chemist obtain the range from the chemist obtain the range from the chemist
22 O
F
1 or xeq
As shown by Fisher et al. (1983, the rank-order function separates the optimization variables into various orderof-magnitude categories. Thus, it is a simple matter to judge the relative importance of the optimization required; i.e., usually we can ignore the optimization variables that are 1 or 2 orders of magnitude less important than the operating variables with the largest rank-order values. We determine the dominant economic tradeoffs for each operating variable by comparing the positive and negative contributions of the components of the gradient separately. Then, any positive terms that are less than 10% of the largest positive term are neglected in subsequent calculations and the same for the negative terms. With this approach, we can often eliminate more than 50% of the calculations (of course, we need to check the results once we have determined the new optimum conditions). The remaining positive and negative terms correspond to the dominant tradeoffs. In order to estimate the incentive for optimizing the most important operating variables (i.e., those with the largest rank-order parameters), we calculate the proximity parameter, Pj, defined by Fisher et al. (1985), where
Thus, the proximity parameter is confined to lie between -1 and 1. If the proximity parameter for an operating variable is equal to zero, that variable is at its optimum value; i.e., the gradient is equal to zero. However, if the absolute value of the proximity parameter is greater than about 0.3, the variable is outside the region where the optimum is relatively flat. Since the minimum operating cost is shifted from the optimum total annual cost, as explained above, the proximity parameters for the operating variables will normally be large. Level 4c. For large values of the proximity parameter (Le., lPjl > 0.3), we change the operating variable in the direction opposite to the sign of the proximity parameter for that variable; i.e., if the gradient is positive, we decrease the value of the operating variable. We continue moving in this direction until we hit an equipment constraint (which may be immediately). This identifies the piece (or pieces) of equipment which constrains the operating variables as we attempt to decrease the operating costs. Level 4d. Then, we calculate the incremental annualized capital cost required to remove the equipment constraint and the savings in operating costs. We continue until the incremental costs are equal or until we hit another constraint. If a second equipment constraint is encoun-
Ind. Eng. Chem. Res., Vol. 26, NO. 11, 1987 2199 tered, we merely calculate the incremental, annualized capital costs required to remove both constrainsts and continue until the incremental costs balance the incremental savings in operating costs. Then, if time permits, we might consider wing the same approach for the less important operating variables. Our primary goals are to get some “feeling” for the magnitude of possible savings from retrofitting and to see if a more rigorous retrofit study can be justified. This screening of retrofit opportunities should provide an estimate of where we reach the point of “diminishingreturns”, Le., where the effort required to optimize an operating variable is not justified by the potential savings. Level 4e. With the new process flows, we now develop the best heat-exchanger network. Level 4f. It is possible that the best new heat-exchanger network will be able to use some of the existing heat-exchange equipment. Hence, we modify the design to use as much existing equipment as is economical. Level 4g. In cases where potential raw material savings are important, our initial retrofit analysis is focused on changing the process flows. Of course, the desired amount of energy integration changes with the flows although the optimum flows also depend on the heat-exchanger network. To resolve this conflict, we initially remove the heat exchangers used for energy integration, and then we retrofit considering only the flows (this procedure will change the energy integration). Then, we consider the energy integration retrofit problem. Next, we could evaluate the effect that the heat-exchanger network has on the new estimates of the optimum flows. However, the goal of our screening calculations is to see if further work can be justified; both in terms of the simultaneous optimization of the flows and the heat-exchanger network and more rigorous computer-aided design calculations. 5. Refine the Retrofit Calculations. Our screening calculations provide an indication of the incentive for doing additional work. These subsequent studies should be carried out by using computer-aided design programs.
Retrofitting and Process Controllability We must ensure that any changes to the structure of the flow sheet or the equipment will not make the retrofitted plant uncontrollable. The steady-state controllability criterion used by Fisher and Douglas (1985) and Fisher et al. (1987) is that for every process constraint or significant operating (optimization) variable, there exists at least one significant manipulative variable. The major potential problem with process controllability in a retrofit analysis is the elimination of manipulative variables. This is particularly true for highly energy-integrated processes. For example, heat loads in integrated distillation columns cannot be varied independently. However, the addition of bypass valves or auxilliary heaters can be used to restore operability. The retrofit design should also be checked to ensure that it can handle the full range of process distrubances, Le., that it is operable. In many cases, equipment overdesign to accommodate disturbances can be used to significantly decrease the incremental operating costs required to maintain operability when disturbances enter the plant. These issues are discussed by Fisher et al. (1987). Example. The Hydrodealkylation of Toluene To Produce Benzene As an example of the retrofit procedure, we consider the hydrodealkylation of toluene to produce benzene (HDA). This process was selected because the design of the process has been discussed in detail in the literature. Here we
Table 111. Optimum Design Conditions for t h e Existing HDA Process design variable reactor conversion H2 purge composition water cooler inlet temp, K water cooler outlet temp, K benzene recovery in product column reflux ratio in product column toluene recovery in recycle column diphenyl recovery in recycle column reflux ratio in recycle column GAS
value 0.75 0.46 428
311 0.99 1.2 0.986 0.807 1.0
RECYCLE
COMPREBDR
TOLUENE FEED
DIPHENYL
4
4
Figure 2. HDA process flow sheet.
Figure 3. Operating cost diagram for the HDA process. Values are in $1 X 106/year. Negative values are credits.
focus on the difference between the design and retrofit problems. The original problem and an optimized design can be found in McKetta (1977). The reactions are toluene H2 benzene CH4
+
-
2(benzene) 2 diphenyl
+
+ H2
The values of the optimized design variables are listed in Table 111, and a simple flow sheet is given in Figure 2. Since, the prices of the raw materials and energy have changed considerably since 1967, we can examine the retrofit of the original design. 1. Identifying the Incentive for Raw Material and Energy Retrofitting. An operating cost diagram for the HDA process is shown in Figure 3. It is obvious from this diagram that incremental raw materials costs (incurred by selectivity losses to byproducts, purge losses, etc.) are much greater than energy costs. Thus, there is a significant incentive to look for ways of decreasing the amount of toluene that is lost to diphenyl (and to the purge) and to reduce the amount of hydrogen that is lost in the purge stream. However, any changes in these flows will also
2200 Ind. Eng. Chem. Res., Vol. 26, No. 11, 1987
.
Table IV Design Decisions Level 1: Batch vs. Continuous-we consider only continuous processes. Level 2: Input-Output Structure of Flow Sheet 1. “Should we purify the raw material streams before they are fed to the reactor?” If the impurities are inert, there are no quantitative heuristics. 2. ‘How many product streams will there be?” Reasonable heuristics seem to be available, except for the case of a reversible byproduct. 3. “Should a reversible byproduct be recovered or recycled to extinction?” No quantitative heuristic is available. 4. ”Do we need a gas recycle and a purge stream?“ A quantitative heuristic seemed to be available before the invention of membrane separation processes to separate gaseous mixtures. Level 3: Recycle Structure 1, “How many reactor systems are required?” The heuristics seem to be reasonable. “Is there any separation between the reactors?” Usually a decision can be made based on the chemist’s data. 2. “How many recycle streams are there?” Heuristics are available. 3. “Should we use an excess of one reactant?” Normally chemist’s data will indicate the answer. 4. “Is a gas recycle compressor required?” A heuristic is available. 5 . “Should the reactor be operated adiabatically, with direct heating (or cooling), or is a diluent (heat carrier) needed?” Some calculations are needed to use the heuristic. 6. Do we want to shift the equilibrium conversion? Calculations and judgement are required. Level 4: Separation System 1. “What is the structure of the vapor and liquid recovery system?” Heuristics are available. Level 4a: Vapor Recovery System 1. “What is the best location of the vapor recovery system?“ No heuristics are available. 2. “What sequence of distillation columns should be used?” The published heuristics are limited to sharp splits of ideal mixtures for a single feed, but in many cases they do not lead to the best sequence. 3. “How should the light ends be removed?” Calculations and judgement are required. 4. “Should the light ends be vented, sent to fuel, or recycled to the vapor recovery system?” Calculations and judgement are required. 5 . “How should we accomplish the other separations?” No heuristics are available. Level 5: Heat-Exchanger Network-A design procedure is available (Linnhoff et al., 1982) for developing alternative designs for heat-exchanger networks. Also, a procedure described by Andrecovich and Westerberg (1985) can be used for energy-integrating distillation columns.
change the utility requirements. 2. Designing a New Plant Using the Existing Flow Sheet. The application of the hierarchical decision procedure to the design of the HDA process has been described in detail by Douglas (1985). The decisions that must be made to develop a flow sheet are given in Table IV, and the decisions that correspond to the flow sheet shown in Figure 2 are listed in Table V. By use of current prices, the optimum design conditions for conversion and purge composition are significantly different than the original optimum values given in Table 111. That is, the new optimum conversion is lower than the original value so that the selectivity losses are lower. The optimum purge composition is also lower so that less hydrogen is lost in the purge. These differences reflect the large change in raw materials prices over the years, (e.g., the cost of toluene in the 1967 case study was given as $0.16/gal vs. $1.30/gal now).
Table V. Process Alternatives for the HDA Process Level 2 Decisions: Input-Output Structure 1. Do not purify the hydrogen feed stream. 2. Recover, rather than recycle, diphenyl so that there are three product streams (purge, benzene product, diphenyl byproduct). 3. Use a gas recycle and purge stream. Level 3 Decisions: Recycle Structure 1. Use a single reactor. 2. Use a gas (H2 and CH,) and a liquified (toluene) recycle stream. 3. Use a 5 / 1 H2/aromatics ratio to prevent coking-assuming this to be a design constraint (although it could be formulated as an optimization problem). 4. A gas recycle compressor is needed. 5 . Operate the reactor adiabatically. 6. Don’t consider equilibrium effects. Level 4b Decisions: Liquid Separation Systems 1. All separations should be by distillation. 2. Use the direct sequence of simple columns-probably complex columns should be used. 3. Remove light ends in stabilizer. 4. The light ends are sent to fuel-no vapor recovery systems. Level 5 Decisions: Energy Integration-there are numerous alternatives.
3. Quick Screening of Process Alternatives. The hierarchical decision procedure of Douglas (1985) makes it a simple matter to generate a list of process alternatives, Le., we merely change the decisions given in Table IV. A procedure for quickly screening these alternatives for the design of a new HDA process has been presented by Douglas and Woodcock (1985). The results indicate that there is a large incentive for decreasing the selectivitylosses by recycling the diphenyl to extinction and that there is a large incentive for recovery of hydrogen from the purge stream. Of course, the design problem is different from the retrofit problem, because in the design problem we always calculate the equipment sizes as a function of the design variables, whereas in the retrofit problem we fix the values of the equipment sizes. If diphenyl is recycled to extinction (i.e., to its equilibrium value), then there are no selectivity losses, the optimum conversion of toluene changes from x = 0.675 to x = 0.997, and the total annual cost of the process is reduced from $4.73 X 106/year to $3.57 X 106/year (Terrill and Douglas, 1987). In a retrofit analysis, we must determine whether the existing equipment can tolerate a large change in flows corresponding to this new value of conversion, and if not we must consider the addition of new equipment. 4. Modifying Equipment Sizes for the Existing Flow Sheet or a Process Alternative. Obviously, it is necessary to evaluate each of the process alternatives from a retrofit viewpoint. However, for the purposes of illustrating our procedure, we only consider changes to the existing flow sheet. Normally, we would evaluate this type of change first, because we expect that the fewest number of changes would be required (Le., the lowest incremental investment). The first step in examining equipment modifications is to remove the feed-effluent heat exchanger in Figure 1 from the process (i.e., we will perform an energy integration analysis after we have modified the flows). We retain the furnace and partial condenser, however, so that we can consider their operating costs (although we do not consider equipment constraints in these units a t this stage of the analysis). We retain these operating costs because some energy from hot and cold utilities will always be required. Next we determine the significant operating variables and the economic tradeoffs for these optimizations by calculating the rank-order functions and the proximity
Ind. Eng. Chem. Res., Vol. 26, No. 11, 1987 2201
-1
Table VI. Gradients of Cost Functions at Base-Case Conditions
f, furnace fuel compressor power product column utilities benzene losses in prod. col. purge losses selectivity losses recycle column utilities coling water (flash drum) Xj
Axj
afiiax
amypH
afiiaFm afiiaRpp
-1134 -125
-1156 -201
0 0
0
0
0
0
0 0
-311 5577 -382
7135 0 0 0
0
0.75 0.1 750 0.48
0.46 0.1 850 0.77
-0.5 0 0 0 150 50 50 0
0 0 154 -154 0 0 0 0
1.27 0.1
30 0
parameters. These values are shown in Table VI. The conversion per pass of toluene and the hydrogen purge composition are clearly the most important optimization variables. Their rank-order parameters are at least an order of magnitude larger than the remaining variables. Also, their large proximity parameter values suggest that smaller values for both conversion and purge composition should lead to significant reductions in operating costs, but these changes might not be attainable with existing equipment capacities. Curiously, it can be shown that the same piece of equipment constrains the optimum value of both of these variables. Operation at lower hydrogen purge compositions would require higher gas recycle flows to satisfy the 5:l hydrogen-to-toluene ratio requirement at the reactor inlet. Thus, the gas recycle compressor capacity constrains the optimum purge composition. Operation at lower reactor conversions would naturally require higher toluene recycle flows. An unusually high design value for the reflux ratio in the recycle column for the original design ensures that sufficient vapor capacity is available to handle the increased toluene recycle load. However, in this case a larger gas recycle flow would also be required to maintain H2/T = 5. Thus, the optimum reactor conversion is also constrained by the gas recycle compressor capacity. Because the compressor capacity constrains the two most important optimization variables, it provides our most likely candidate for retrofitting. Both variables primarily trade off raw material costs vs. heating costs for increased recycle flows. Thus, energy integration aimed a t reducing these costs may also be appropriate. The cooling water flow rate and the reflux ratio in the product column are less important optimization variables. Moreover, these variables are able to attain their optimum values with the existing equipment (Pj = 0 for each). The cooling water flow rate primarily trades off utilities costs vs. purge losses of benzene and toluene. The only retrofit policy possible to reduce these costs would be to increase the area of the partial condenser preceding the flash drum. The reflux ratio in the product column primarily trades off product losses to the bottoms stream vs. heating and cooling costs for an increased reflux ratio. Possible retrofit policies would be energy integration to reduce the utilities requirements or increased number of trays in the stripping section to improve the product recovery. Implementing this last policy is unlikely for an existing column. Now that the most attractive retrofit policies have been identified, the cost of equipment modifications must be incorporated into the optimization analysis. In particular, we must specify whether the capacity of a piece of
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Figure 4. Estimation of the optimum retrofit policy for the gas recycle compressor.
equipment can be increased incrementally (via auxiliary exchangers, etc.) or whether a new unit must be introduced to replace an existing one. Only by comparing the potential decrease in opeating costs with the incremental capital costs incurred can we decide if a retrofit policy is beneficial. Gas Recycle Compressor. In order to increase the gas recycle flow rate, we assume that we can introduce another compressor in parallel with the existing unit. As the capacity of this new compressor increases, the constrained (optimum) values for both purge composition and reactor conversion decrease. This tradeoff between the added annualized compressor capital cost and the total annual operating cost for the process is shown in Figure 4. Based on a capital charge factor of 113 per year (of course, different companies use different capital charge factors), the approximately optimum retrofit policy is to install an additional gas recycle compressor with 56% of the capacity of the existing unit. The incremental capital cost for the compressor just balances the reduction in operating costs (where the slopes in Figure 4 are equal and opposite in sign). This policy incurs a capital cost of $55 000/year but reduces the total operating costs by about $480000/year. Of course, the greatly increased gas and liquid recycle flows would also saturate the furnance heating capacity. Again, this conflict will be addressed after a revised energy integration analysis has been completed. Flash Drum Cooler. In order to drive the flash drum temperature closer to the cooling water temperature, we could introduce another exchanger in series with the existing partial condenser. The optimum exchanger area would primarily trade off the associated capital cost vs. the purge losses of benzene and toluene. That is, the flash drum temperature has only a small effect on the remaining operating costs. As shown in Figure 5, the approximately optimum retrofit policy is to install an additional exchanger with 1.5 times the area of the existing unit. This policy incurs a capital cost of $75 000fyear but reduces the total operating costs by about $410 000fyear. Energy Integration Analysis. The energy integration for the original flow sheet, Figure 2, consists solely of a feed-effluent heat exchanger (FEHE) around the high-
2202 Ind. Eng. Chem. Res., Vol. 26, No. 11, 1987
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Figure 6. Temperature-enthalpy diagram for the HDA process at base-case operating conditions. Table VII. Comparison of t h e Base-Case a n d Retrofit Operating Conditions original retrofitted 0.75 0.69 reactor conversion purge composition 0.46 0.35 150 120 cooling water flow ( % of design) recycle col. reflux ratio 1.27 1.36 11.9 11.9 furnace duty ($ X lo6 Btu/h)
temperature reactor. Figure 6 shows the temperatureenthalpy diagram for the original operating conditions and equipment sizes. The incentive for additional energy integration is shown quantitatively by the separation of the heating-and cooling curves. The new optimum operating conditions based on the above retrofit analysis are given in Table VII. The resulting temperature-enthalpy diagram is given in Figure 7. On the basis of this information, we can make two important observations: (1) the incentive for energy integration is much greater for the new process flows and (2)
Figure 8. Estimation of the optimum retrofit policy for the feedeffluent heat exchanger.
the required furnace load is 60% greater than the design value. Thus, one goal of any additional energy integration should be to reduce the required furnace load and to restore operability. This can most easily be achieved by increasing the area of the existing FEHE. Other integration strategies (such as thermal coupling of the distillation columns) should also be investigated. In a detailed study of heat-exchanger networks for the design of an HDA process, Terrill and Douglas (1987) found that a feed-effluent exchanger alone provides close to the optimum design. Thus, we might begin our retrofit of energy integration by estimating the optimum amount of overdesign for the FEHE. The tradeoffs involved are shown in Figure 8. The approximately optimum retrofit policy is to install an additional exchanger with 68% of the area of the existing one. This policy incurs a capital cost of about $160 000/year, while reducing the total operating costs by about $250 000/year. This “optimum” retrofit policy for the FEHE reduces the required furnace load to within 10% of its design value. If this is still not tolerable, additional overdesign of the
Ind. Eng. Chem. Res., Vol. 26, No. 11, 1987 2203 FEHE could be used to reduce the furnance load further. As illustrated in Figure 8, this would result in only a small increase in the total annualized costs for the process. We can use calculations of this type in order to make a preliminary assessment of the incentive for undertaking a more detailed energy integration retrofit study. Of course, if our screening calculations indicate that additional effort can be justified, we want to repeat our analysis by using rigorous calculation procedures and a more detailed energy integration retrofit procedure; see Tjoe and Linnhoff (1986). A much more detailed energy integration analysis for the design of this process has been conducted by Terrill and Douglas (1987). They found that a feed-effluent heat exchange alone provides a nearly optimum heat-exchanger network for a new process design. That is, more complex networks provide only minimal (6%) reductions in the total annualized costs for this process. For the retrofit analysis, the flow sheet is much less flexible with more complex networks, so we assume that a feed-effluent exchanger is close to optimum. Summary of the Initial Retrofit Analysis. The proposed retrofit policies for the HDA process incurred a total of $290 000/year in capital costs, while reducing the total operating costs by $1 140000/year. The policies provide a 130% return on a capital investment of $870000 (or a 9-month payback period). If this is sufficient justification to proceed further with the retrofit study, then we must iterate between the flow optimizations and the heat-exchanger network optimization. This provides a good starting point for computer-aided design calculations. We should note that energy integration alone reduced the total annualized costs for the process by about $90000/year, accounting for only 10% of the savings for the complete retrofit analysis. While this result is specific to this example, it nonetheless points out the importance of considering both flow optimizations and heat-exchanger network alteratives during the retrofit analysis. Clearly, the "best" heat-exchanger network for the original conditions, Figure 6, would differ significantly from any network based on Figure 7. As will often be the case, the proposed retrofit policies for the HDA plant increase the total utility heating and cooling, as well as increase the amount of process/process heat exchange.
Other Alternatives Of course the retrofit policy described above may not be the best one to choose. Thus, we also need to consider the other process alternatives that we identified earlier. However, the general approach of identifying the significant operating variables and modifying equipment sizes is the same. Developing an Interactive Computer Code for Screening Retrofit Opportunities The retrofit procedure that we present in Table I is computationally intensive; i.e., a large number of calculations are required, and the number of production rules as compared to the number of algorithms is much less than in the synthesis procedure described by Douglas (1985). Hence, the proceudre is not well suited for current AI (Artificial Intelligence) expert system shells which handle only qualitative knowledge (e.g., MYCIN, KEE, etc.). Similarly, the calculations are tedious if conventional simulators such as PROCESS, ASPEN, DESIGN 2000, Chem CAD, etc., are used, because it is necessary to switch from a performance to a design model (and to recompile the program) every time that an equipment constraint is encountered as the operating variables are changed.
An interactive program, PIP (Process Invention Procedure), that contains both heuristics and algorithms that will accomplish the first three steps in the procedure, as well as step 4b, has been described by Kirkwood et al. (1987). This program has a different achitecture than a conventionalAI expert system because the knowledge base has been arranged as a hierarchical plan (Sacerdoti, 19741, the knowledge has been precedence ordered at each level in the hierarchy, both a qualitative (heuristics) and a quantitative (algorithms) knowledge base have been included at each level in the hierarchy, and the heuristics that are used to fix the structure of the flow sheet and to identify the process alternatives are also used to select the appropriate subroutines for the design calculations. A code for screening retrofit opportunities (for the same, limited class of processes considered by PIP) can be developed by adding a set of shortcut performance models to PIP and by adding the logic required to recognize equipment constraints and to switch from performance models to design models when constraints are encountered, to plot the incremental and annualized capital costs and operating cost savings as the operating variables are changed, and to retrofit heat exchanger networks after the flows have been changed. An attempt to devlop a code for this purpose is currently under way.
Conclusions It is possible to identify three types of retrofitting problems: (1)process "debottlenecking" to increase production capacity, (2) expansion of equipment capacity to ease constrained operation, and (3) modification of unconstrained equipment to reduce operating costs. Heatexchanger network retrofit procedures concern themselves primarily with this last item but do not normally address the remaining issues. The systematic retrofit procedure developed in this paper considers each of these problems in the order given. Bottlenecking equipment can be identified by using a published flow sheet decompositionscheme. Quantitative parameters used to characterize the design optimization problem for new processes can be used to evaluate the incentive for additional retrofitting. The procedure can be used as the basis for an interactive code for screening retrofit opportunities for petrochemical plants. The procedure has been applied to several published case studies, where the goal of retrofitting was to reduce operating costs at current production rates and operating conditions (a common case). In each of the case studies there were large selectivity losses of raw materials to byproducts. The results indicate that there is a significant incentive to modify the process operating conditions if raw material costs have changed significantly from the original design conditions. The new stream flow rates and heating/cooling loads also increase the incentive for energy integration. Nonetheless, the final decrease in annualized costs is an order of magnitude larger than is possible with energy integration alone. Acknowledgment We are grateful to the National Science Foundation for partial support of this work under Grant CPE-8105500.
Nomenclature f = fractional recovery (Table I) f i = cost function F,, = flow rate of cooling water to flash drum cooler FEHE = feed-effluent heat exchanger HDA = hydrodealkylation of toluene to benzene process P, = proximity parameter for optimization variable x j
Ind. Eng. Chem. Res. 1987,26, 2204-2211
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r . = rank-order parameter for optimization variable x,
R = reflux ratio
R, = minimum reflux ratio RPc = reflux ratio for the product column x = reactor conversion x = equilibrium reactor conversion (Table I) x;”= optimization variable YpH = hydrogen purge composition
Literature Cited Andrecovich, M. J.; Westerberg, A. W. “A Simple Synthesis Method Based on Utility Bounding for Heat-Integrated Distillation Sequences”, AIChE J. 1985, 31, 363. Boland, D.; Hindmarsh, E. “Heat Exchanger Network Improvement”, CEP 1984, 80(7),47. Douglas, J. M. “A Hierarchical Decision Procedure for Process Synthesis”, AIChE J. 1985, 31, 353. Douglas, J. M.; Woodcock, D. C. “Cost Diagrams and the Quick Screening of Alternatives”, Ind. Eng. Chem. Process Des. Deu. 1985, 24, 970. Fisher, W. R.; Doherty, M. F.; Douglas, J. M. “Evaluating Significant Economic Tradeoffs for Process Design and Steady-State Control Optimization Problems”, AIChE J . 1985, 31, 1538. Fisher, W. R.; Douglas, J. M. “Evaluating Process Operability at the Preliminary Design Stage”, Comp. Chem. Eng. 1985, 9, 499. Fisher, W. R.; Doherty, M. F.; Douglas, J. M. “The Interface Between Design and Control”, Ind. Eng. Chem. Res. 1987, in press. Kirkwood, R. L.; Locke, M. H.; Douglas, J. M. “An Expert System for Synthesizing Flowsheets and Optimum Designs”, Comp. Chem. Eng. 1987, in press.
Linnhoff, B.; Vredeveld, D. R. “Pinch Technology Has come of Age”, CEP 1984, 80(7), 33. Linnhoff, B.; Townsend, D. W.; Boland, D.; Hewitt, G. F.; Thomas, B. E. A.; Guy, A. R.; Marsland, R. H.; “A User Guide on Process Integration for the Efficient Use of Energy”, Inst. Chem. Eng. 1982, 1.
McKetta, J. J., Ed. “Encyclopedia of Chemical Processing and Design”, Marcel Dekker: New York, 1977; Vol. 4, p 182. Sacerdoti, E. D., “Planning in a Hierarchy of Abstraction Spaces”, Artif. Intelligence 1974, 5, 115. Steinmetz, F. J.; Chaney, M. D. “Total Plant Energy Integration”, Presented at the Spring National AIChE Meeting, Houston, March 24-28, 1985; Paper 88d. Terrill, D. T.; Douglas, J. M. “Heat Exchanger Network Analysis. 1. Optimization”, Ind. Eng. Chem. Res. 1987, 26, 685. Tjoe, T. N.; Linnhoff, B. “Using Pinch Technology for Process Retrofit”, Chem. Eng. 1986, April 28, 47. Townsend, D. W.; Linnhoff, B. “Surface Area Targets for Heat Exchanger Networks”, Annual Meeting of the Institute of Chemical Engineers, Bath, U.K., April 1984. Westerberg, A. W. ”The Role of Expert System Technology in Design”, Paper presented at the International Symposium on Chemical Reaction Engineering, Philadelphia, May 18-21, 1986; ISCRE 9. Witherell, W. D.; Linnhoff, B. “Pinch Technology Retrofit: A Complex Industrial Application”, Presented at the Spring National AIChE Meeting, Houston, March 24-28, 1985; Paper 88b. Received for review August 15, 1986 Revised manuscript received J u n e 3, 1987 Accepted June 27, 1987
Cocracking and Separate Cracking of Ethane and Naphtha Patrick M. Plehiers and Gilbert F. Ftoment* Laboratorium voor Petrochemische Techniek, Rijksuniversiteit te Gent, B-9000 Gent, Belgium
This paper presents experimental data on the thermal cracking of a naphtha-ethane mixture in a pilot plant, under conditions representative of industrial operation. The effects of the interaction between ethane and naphtha on the ethane conversion and kinetics and on the product distribution are investigated. When naphtha, ethane, and the mixture are cracked under an equal molar dilution, the cocracking yields and selectivities can be quantitatively predicted from the separate cracking data, except for hydrogen, methane, and high molecular weight products. The combined effects of cocracking and partial pressure, occurring when naphtha, ethane, and the mixture are cracked under an equal weight dilution, are such that, if maximum olefins selectivities are desired, separate cracking is to be preferred. Some aspects of coke formation are addressed as well. Introduction Literature data on naphtha-ethane pyrolysis are scarce and very incomplete. Most authors base their conclusions upon one single data point. de Blieck and Goossens (1971a,b)observed that cocracking with naphtha increased, for identical reaction conditions, the ethane conversion. From a comparison of “typical” product distributions for cocracking and separate cracking, Mol (1981) concluded that the interaction between ethane and naphtha in the cracking of a mixture containing about 24% by weight ethane leads to an enhanced ethylene selectivity, enabling a 2 YO savings in naphtha consumption. Propylene and butadiene selectivities, however, were markedly reduced. Nowowiejski et al. (1982) cracked naphtha with ethane in an industrial millisecond furnace. In addition to the millisecond effects, they found the methane and ethylene yields to be favored by cocracking; the C,+ and butenes yields were found to be reduced. No accelerating effect of the naphtha on the ethane cracking was noticed in this case. A considerable influence of the naphtha composition on the deviations of the cocracking yields from additivity 0888-5885/87/2626-2204$01.50/0
was observed, but no further details are given on this issue, however. Clearly, until now, no thorough study of naphtha-ethane cocracking has been published. The work reported in the present paper aimed at a better understanding of the interaction between naphtha and ethane during pyrolysis. I t was investigated how the interaction alters the overall ethane cracking kinetics and the product distributions. Experiments were performed under conditions close to those encountered in industrial practice. Statement of the Problem The aim of a study on cocracking of hydrocarbons is to compare the cocracking yields with those resulting from the mixing of the effluents of separate cracking. Quite often in the literature, “identical reaction conditions” are chosen as a basis for this comparison. Since different hydrocarbons demand completely different operating conditions, comparing yields at equal conditions does not seem very appropriate. Moreover, identical reaction conditions do not guarantee the naphtha and ethane con0 1987 American Chemical Society
