Dynamic Simulation and Control of BTX Distillation Column of Bu-Ali Sina Petrochemical Complex
Ali Samadi, Mosayeb Hossein zadeh*, Mortaza Zivdar, Mohammad Abdoullahi University of Sistan and Baluchestan, Department of Chemical Engineering
[email protected]
Abstract The chemical industries are faced with an increasingly competitive environment, ever-changing market conditions, and government regulations; yet, they still must increase productivity and profitability. Dynamic plant studying is a powerful tool that helps managers and engineers link business operations to process operations. The understanding of the dynamic behavior of distillation columns has received considerable attention because distillation remains the most commonly used separation process in the chemical industry. In the present paper, the dynamic behavior of BTX distillation column of Bu-Ali Sina petrochemical complex has been studied and its results in the face of very large disturbances are presented by Aspen Dynamics simulation. Proposed control structure, predicts effect of these disturbances on purities of bottom and distillate products with rate of change about 0.1%. Keywords: Distillation Column, BTX, Dynamic Simulation, Control Structure, Aspen Dynamics.
Introduction The chemical process industry faces very challenging economic and social issues. Severe market competition needs fast responses from product innovation, process development, to production, especially for high value-added fine and specialty chemicals. The challenges of process systems engineering is concerned with the improvement of decision-making processes for the creation and operation of the chemical supply chain. It deals with the discovery, design, manufacture and distribution of chemical products in the context of many conflicting and multi-attribute goals [1]. Dynamic plant studying is a powerful tool that helps managers and engineer’s link business operations to process operations, thus enabling true Process Lifecycle Management, on the other hand, if we understand the dynamic behavior of the chemical process industries, we will search
the various control structures for them [2]. To understand the dynamic behavior of a complex chemical process, process manufacturers require a dynamic process simulator [3]. Aspen Dynamics is a state-of-the-art solution designed specifically for dynamic process simulation. Aspen Dynamics is tightly integrated with Aspen Plus; and can to analyze the dynamic behavior of chemical processes and to design the process control systems [4]. In this paper, deheptanizer column of Bu-Ali Sina petrochemical complex examined with steady-state simulation and comparison of its results with actual data. Finally with perform dynamics simulation, the purity Process Description In Deheptanizer column the feed is separated into a heavy fraction C8+ aromatics which contains nearly all components having boiling points above toluene and into a benzene/toluene fraction which contains all constituents having boiling points same as or lower than toluene. The column is equipped with 60 valve trays, tray no. 1-16 with 600 mm spacing and tray no. 17–60 with 500 mm spacing. Feed is entering the column with a temperature of 65 °C at pressure of 1.7 bar at tray no. 30. The required heat energy for operating column is generated in fuel gas heated Deheptanizer Reboiler. Circulated by Reboiling Pump the bottom product of column is heated up and partly vaporized in the heater. The top vapors of column are condensed in Condenser Overhead and collected in Deheptanizer Reflux Drum. Via Reflux Pump the condensate is partly pumped back to the column as reflux [5].
Figure 1. Deheptanizer column flowsheet
Steady-State and Dynamic Simulation of Deheptanizer Column I. Steady-State Simulation Consider a multi-component mixture to be fed to a distillation column containing N=60 theoretical stages, a total condenser, and a partial reboiler and operating at a pressure of 1.4 bar to 2.4 bar. The assumptions are (i) the pressure slope is constant on all trays. (ii) the vapor and liquid leaving each tray are in equilibrium (i.e., tray efficiency is 100%), and (iii) the column is adiabatic. The column feed, a saturated liquid, is composed of 11.97% Benzene, 21.47% Toluene, 4.84% Ethylbenzene, 4.47% Para-Xylene, 10.28% Meta-Xylene, 6.03% Ortho-xylene and other components with small mass fraction at T=338 ºK. Feed flow rate is set equal to 115390 kg/hr. The reflux ratio is chosen equal to 0.76001. Perfect agreement was found between results and the data provided by the Aspen simulation that are showed in Table 1. Table 1. Comparing simulation results and actual data
Condenser heat duty (MW) Reboiler heat duty (MW) Top temperature of column (ºK) Bottom temperature of column (ºK) Distillate rate (kg/hr) Bottom rate (kg/hr) Distillate key components mass fraction Benzene (%Wt) Toluene (%Wt) Bottom key components mass fraction Ethylbenzene (%Wt) Para-Xylene (%Wt) Meta-Xylene (%Wt) Ortho-Xylene (%Wt)
Simulation results 11.6 16.3 383 457.4 63145.6 52244.4
Actual data 11.8 16.9 381 448 63145.6 52244.4
21.88 39.24
21.88 38.86
10.54 9.84 22.67 13.31
10.60 9.85 22.67 13.31
II. Dynamic simulation Once the steady-state conditions have been established, the Aspen Plus file can be exported to Aspen Dynamics after vessel sizes have been specified. The reflux drum, column base and sump all sized to provide 5 min of liquid holdup when at 50% level. The size of reflux drum 5.1×2.8 m and the sump is 7.3×3.8 m. Trays diameter are 3.8 m.
Selecting Temperature Control Tray i. Slope Criterion: The right graph in Figure 2 gives the temperature profile at design conditions. The left graph shows the differences between the temperatures on adjacent trays. The location of the tray with the largest slope is stage 42. There is another tray (stage 15) that has a slope that is almost as large.
Figure 2. collumn temperature profile and slope
ii. Sensitivity Criterion: The upper graph in Figure 3 gives the openloop gains between tray temperatures and the manipulated variable reboiler heat input . Very small increases from the steady-state values (+0.1%) of the two inputs are used. These curves show that both stages 42 and 15 is sensitive to changes in heat input.
Figure 3. collumn sensitivity analysis
Figure 4. Control structure of BTX column
Figure 4 shows the plantwide control structure developed for this column process. Conventional PI controllers are used in all loops. All level loops are proportional with KC=2. The temperature profile given in Figure 2 indicates that the temperature on Stage 42 can be used to maintain column temperature. The temperature controller has a 1 min dead time and this temperature controller is tuned by using relay-feedback tests to obtain ultimate gains and periods and then applying Tyreus-Luyben tuning rules. Table 2 shows all controllers parameters that used in dynamic simulation. Table 2. The controller parameters used in the BTX column
Real Controller Model Controlled Variable Manipulated Variable SP Transmitter Range OP OP Range Dead Time
PC
TC
LC1
LC2
PI
PI
P
P
Top Pressure of The Column Condenser Heat Duty 1.4 bar 0 - 2.8 bar 11.6 MW 0-24 MW 12 20 min
42nd Stage Temperature Reboiler Heat Duty 426 ºK 350 - 500 ºK 16.3 MW 0 - 32 MW 1 min 6.713 17.16 min
Reflux Drum Level Distillate Rate
Sump Level Bottom Rate
1.4 m 0 - 2.8 m 63145.6 kg/hr 0 - 140000 kg/hr 2 9999 min
4.65 m 0 - 9.3 m 52244.4 kg/hr 0 - 110000 kg/hr 2 9999 min
Results and Discussion Several large disturbances are made to test the ability of the proposed control structure. These disturbances include column feed flow rate and feed temperature.
Figure 5. 10% feed flow rate disturbances
A. Feed Flow Rate Disturbances: Figure 5 gives results for 10% changes in the set point of column feed flow controller. The disturbances are made at 1 hr. Stable regulatory control is achieved. Most of the transients die out in less than 4 hr. Distillate and bottom compositions are maintained quite close to their steady values. In a simple distillation column, the reflux ratio would not change with throughput.
Figure 6. 10 ℃ feed temperature disturbances
B. Feed Temperature Disturbances: Figure 6 gives results for changes in the column feed temperature. The design value is 65ºC. Curves show results for an increase in feed temperature to 75ºC. Conclusions A control structure for the BTX column process has been tested. It handles large disturbances and maintains both temperature and pressure close to the specified values and their die outs are less than 4 hours. The main question the choice of control structure is that how much these disturbances affect on purities of bottom and distillate products, results showed that these changes in purity are about 0.1%. Acknowledgements The authors wish to acknowledge support from R&D section of Bu-Ali Sina Petrochemical Complex. References [1] I.E. Grossmann, Challenges in the new millennium: product discovery and design, enterprise and supply chain optimization, global life cycle assessment, Computers & Chem. Eng, 29 (2004) 29-39. [2] B.W. Bequette, Process Dynamics Modeling: Analysis and Simulation, Prentice Hall PTR, New Jersey, 1998. [3] Aspen Tech Company (
[email protected] (Engineering Suite)). [4] H. Yeomans, I. E. Grossmann, Disjunctive Programming Models for the Optimal Design of Distillation Columns and Separation Sequences, Ind. Eng. Chem, 39 (2000)1637-1648. [5] Third Aromatics Plant, Bandar Imam, Operating Manual, Eds500-1 (General & Process), Process Description, 1998, pp. 3-5.
