DISTILLATION ECONOMIC OPTIMIZATION

In Chapter 3, we studied how to design a distillation column, given the feed conditions, the desired product specifications, and the total number of stages. The calculated design parameters included the operating pressure of the column, the reboiler and condenser heat duties, and the length and diameter of the column vessel. 

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Bauer, M. H. and J. Stichlmair. Design and Economic Optimization of Azeotropic Distillation Process Using Mixed-Integer Nonlinear Programming. Comput Chem Eng 22 1271-1286 (1998). 

Computer modeling of the crude process is worthwhile for many reasons including 1) initial design 2) economic optimization of operation and 3) control and adjustment of product compositions and operating costs. The first models were based on reducing the process to a combination of two-product distillation calculations because of the available computer power. More recently, the computer calculation is able to handle the crude tower as is however, the two-product combinations are useful to guide technical supervision of the operation (Figs. 4 and 5). 

Benali, M. and Aydin, B. (2010) Ethane/ethylene and propane/propylene separation in hybrid membrane distillation systems Optimization and economic analysis. Separation and Purification Technology, 73 (3), 377-390. 

Equations to calculate the capital cost of all the equipment and the energy cost of the heat added to the reboiler are needed to perform economic optimization calculations. The major pieces of equipment in a distillation column are the column vessel (of length L and diameter D, both with units of meters) and the two heat exchangers (reboiler and... 

The economic optimal process flowsheet was obtained by minimization of the total annual cost (TAG) with five design variables IPA distillate composition (XD2) in the recovery column, total number of stages for the heterogeneous azeotropic column and the recovery column (Ni and N2), and the two feed stages (Api and Apa). The product specification of IPA is set to be ultrapure (99.9999 mol%) to be used in the semi-conductor industry. The product specification of water is set to be 99.9 mol%. In each simulation run, the IPA product specification is achieved by varying the reboiler duty of the heterogeneous azeotropic column, and the water product specification is achieved by varying the reboiler duty of the recovery column. The entrainer makeup flowrate will be very small to balance the entrainer loss from the two bottom streams. 

Figure 12.2 shows the economically optimized flowsheet of the extractive distillation system. A solvent is added near the top of the extractive column. Acetone goes out the top of this column, while the bottoms is fed to the solvent recovery column where chloroform is... 

Extensive design and optimization studies have been carried out for this sequence (108). The principal optimization variables, ie, the design variables that have the largest impact on the economics of the process, are the redux ratio in the azeo-column the position of the tie-line for the mixture in the decanter, determined by the temperature and overall composition of the mixture in the decanter the position of the decanter composition on the decanter tie-line (see Reference 104 for a discussion of the importance of these variables) and the distillate composition from the entrainer recovery column. 

While process design and equipment specification are usually performed prior to the implementation of the process, optimization of operating conditions is carried out monthly, weekly, daily, hourly, or even eveiy minute. Optimization of plant operations determines the set points for each unit at the temperatures, pressures, and flow rates that are the best in some sense. For example, the selection of the percentage of excess air in a process heater is quite critical and involves a balance on the fuel-air ratio to assure complete combustion and at the same time make the maximum use of the Heating potential of the fuel. Typical day-to-day optimization in a plant minimizes steam consumption or cooling water consumption, optimizes the reflux ratio in a distillation column, or allocates raw materials on an economic basis [Latour, Hydro Proc., 58(6), 73, 1979, and Hydro. Proc., 58(7), 219, 1979]. 

The results received form the optimization using inherent safety as the objective function are somewhat different compared to those calculated with an economic objective function earlier (Hurme, 1996). With the inherent safety objective function the simple distillations were favoured more than with the economic function. Exceptions are cases where the extractive distillation could improve separation very dramatically. This is because in simple distillations only one column is required per split, but in extractive distillation two columns are needed, since the solvent has to be separated too. This causes larger fluid inventory since also the extraction solvent is highly flammable. The results of the calculation are well justified by common sense, since one of the principles of inherent safety is to use simpler designs and reduce inventories to enhance safety. 

From a thermodynamics basis, the transesterification reaction favors the formation of methylphenyl carbonate (Equation 7.4), whilst its further disproportionation in a second-stage continuous reactive distillation column affords DPC with selectivity >99%. Although both reactions occur at a relatively high temperature ( 473 K), optimization of the reaction conditions and engineering design would allow a productivity that fitted with the economics [17, 27]. 

Estimation of column costs for preliminary process evaluations requires consideration not only of the basic type of internals but also of their effect on overall system cost. For a distillation system, for example, the overall system can include the vessel (column), attendant structures, supports, and foundations auxiliaries such as reboiler, condenser, feed neater, and control instruments and connecting piping. The choice of internals influences all these costs, but other factors influence them as well. A complete optimization of the system requires a full-process simulation model that can cover all pertinent variables influencing economics. 

A state-of-the-art RO seawater system processes 50 million gallons per day with 50% feedwater recovery as potable water product using a 940-psi ( 65 bar) feed pressure [12]. These high pressures and flows are now routinely accommodated economically with compact vessels and high productivity membranes. An optimized thermal distillation plant with the same feedwater requires 1014 Btu/gal [78.5 (kwh)/m3] of water produced [8], while the state-of-the-art seawater RO system has an energy cost of only 2.2 (kwh)/m3 [8,12]. Using the current paradigm... 

Another class of separation problem attacked has been that of designing the most effective thermally coupled distillation column arrangement to separate a multicomponent mixture. Sargent and Gaxninibandara (1975) present a general column superstructure which they optimize. Imbedded in the superstructure are all the alternative thermally coupled and ordinary column sequences to be considered. The optimization eliminates those portions of the superstructure which are not economic leaving, hopefully, the optimal substructure. 

The previous section assumed that product composition (or product flow) requirements are fixed. In this very common situation, the optimum design minimizes the costs of achieving these requirements. Often, product specs are not fixed, but depend on economics. Even when a product must obey a "less than" purity spec, better purity may fetch a better price. The better price may justify additional investment in equipment and/or a higher operating cost. Here, a design must optimize product purity value versus distillation cost. This optimization is also important in an operating column and is commonly performed by on-line computer control. It is outlined below, and discussed in detail elsewhere (1,2). 

For separation of liquefied gases, the critical temperature of the distillate may be lower than the cooling water temperature, and refrigeration is nseded. The economic balance is still primarily between the first favorable and first unfavorable effects, but the refrigeration complicates the analysis. Optimization is required for selecting the best pressure, and can be lengthy and tedious if correctly performed. Shortcuts often lead to nonoptimum conclusions. Each case must be considered on its own merits. An example of such an optimization for an ethylene-ethane separation column, as well as of some optimization pitfalls, is described elsewhere (7). 

The simulator packages such as Aspen Plus and Hysys may be useful in analyzing distillation column systems to improve recovery and separation capacity, and to decrease the rate of entropy production. For example, for the optimization of feed conditions and reflux, exergy analysis can be helpful. A complete exergy analysis, however, should include both an examination of the exergy losses related to economic and environmental costs and suggestions for modifications to reduce these costs. Otherwise, the analysis is only theoretical and less effective. 

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