Pressure-Driven Dynamic Simulation for Improving the Performance of

Ind. Eng. Chem. Res. 2009, 48, 9195–9203

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Pressure-Driven Dynamic Simulation for Improving the Performance of a Multistage Compression System during Plant Startup Xiongtao Yang, Qiang Xu,* Chuanyu Zhao, Kuyen Li, and Helen H. Lou Dan F. Smith Department of Chemical Engineering, Lamar UniVersity, Beaumont, Texas 77710

Multistage compression systems (MSCS) are the most important and valuable facilities in chemical plants, whose failure may cause severe accidents and/or tremendous economic loss. Thus, operation for MSCS needs sufficient care under various situations, especially during plant startup. This paper employs rigorous pressuredriven dynamic simulations to examine and improve operation safety of the cracked gas compression system during an ethylene plant startup. For safety consideration, antisurge process design and control strategies are dynamically evaluated along with startup procedures. Operating point trajectory for each compressor and their potential safety problems are identified. Assisted by the rigorous dynamic simulation, the plant startup procedure is improved with better safety performance. Introduction Quite often, production capacity of a chemical plant depends on the reliability, stability, and sustainability of its compression system. Multistage compression systems (MSCS) are the most important and valuable facilities in chemical plants, whose failure may cause severe accidents and/or tremendous economic loss. Thus, operation for MSCS needs sufficient care under various situations, especially during plant startup. When analyzing previous startup cases, a smooth startup of the compression system has been proved to be essential in plant and environmental safety. However, many past startup cases fail due to surging compressors as the discharge of the system slowly builds up pressure, which caused severe equipment damage and unnecessary flaring.1 Thus, safe, reliable, and sustained compressor operations under critical conditions (e.g., turnarounds or process upsets) are major concerns for the plants, which have to employ effective constraint control for the compression system. Control of complex compression systems in a chemical process presents big challenges, which involve plant startup automation, effective compressor surge protection, antisurge margin control, flare emission reduction, and startup time reduction.2 Thus, the operation of a compression system needs sufficient care to avoid dangerous situations for compressor operation, which can damage compressor internals, reduce compressor lifetime, and diminish the profit due to downtime and costly repair.3 Commonly, large centrifugal compressors have four operating limits, which are part of their operating characteristics shown as a map of operating envelope. The compressor operations should be well-controlled within this operating envelope to ensure safety. Figure 1 shows a typical operating envelope with the boundary limits defined below. Minimum Operating Speed. This is the minimum speed for acceptable operation of a compressor. Below this value, the compressor may be shut down or go into an “idle” condition. Maximum Allowable Speed. This is the maximum operating speed for the compressor. Above this value, stresses may rise above prescribed limits and rotor vibrations may increase rapidly, which will easily damage the compressor shaft and other internals. * To whom correspondence should be addressed. Phone: 409-8807818. Fax: 409-880-2197. E-mail: [email protected].

Surge. This is the operation at which the compressor cannot add enough energy to overcome the system resistance or the developed compressor head drops below the discharge pressure.4 This causes a rapid flow reversal. As a result, high vibration, temperature increase, and rapid change in axial thrust can occur. These occurrences can damage rotor seals, rotor bearings, and the compressor driver. Usually, the compressor manufacturer recommends a minimum flow at certain operating speed, which gives rise to the surge limit line on the operating envelope. Stonewall (Choke). For high-speed equipment, as the flow rate increases, the velocity of the gas/fluid can approach the gas/fluid’s sonic speed somewhere within the compressor stage. It may occur at the impeller inlet “throat” or at the vaned diffuser inlet throat. Stonewalling can cause vibration and fatigue failure that can damage the entire compressor over time. Thus, the compressor manufacturer often recommends a limit for highflow rate operation. Because of the potential safety and economic concerns, it is impossible to test the control strategies for improving the performance of a real compressor system before high-fidelity virtual evaluations are conducted. Since a compression system can experience various transient operations, including startup, shutdown, process upset, and equipment/instrument failure, and these operations are dynamic in nature, the steady-state simulation (SS) is not adequate to address issues associated with transient operations, such as startup capability, compressor surge protection, and stability of operation.5 In the absence of virtual tests, many plants are using a trial-and-error approach to modify operating procedures to gain expensive and sometimes painful

Figure 1. Sketch of the compressor operating envelope.

10.1021/ie900212v CCC: $40.75  2009 American Chemical Society Published on Web 09/24/2009

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Figure 2. Pressure-driven DS methodology for chemical plant startup.

experiences.6 Consequently, the rigorous dynamic simulation (DS) models have to be gradually developed and employed to provide the insight of operations and investigate the system dynamic responses under critical conditions. DS is well-known for operation training simulators.7-9 It has been increasingly used in refinery, chemical, and petrochemical industries, to examine critically the potential process operational risks, perform design optimizations, identify production limiting constraints, and validate the dynamics or time-dependent behaviors of the process.6,10-12 DS can be used to predict the operating point trajectory under various transient scenarios and evaluate measures that can reduce the risky operations.5 Several studies on compression systems with the application of DS have been reported. Robertson and Cameron developed a case study for the shutdown of multistage centrifugal compressors.13 Their first-principle based model was able to predict the occurrence accurately using perturbation reduction methods. Dolph used the DS to improve compressor control strategies for fluidized catalytic cracking unit under emergency situations.14 Very recently, Bernard studied a propylene compressor trip problem based on dynamic simulation. He studied drum level control issues among different compression stages that related to heat and material balance of propylene flows in the refrigeration system.7 The developed compressor models were simplified without consideration of operating envelopes. Wu and her colleagues employed DS to conduct compressor control system validation and improvement to support liquefied natural gas (LNG) compressor operation under operational disturbances.3 The study was in LNG area. Dynamic behaviors and safety issues during plant startup operations were not addressed. On the basis of current literature survey, there is still a lack of study on rigorous DS for the entire MSCS during plant startup. Since the MSCS is the most important part during a plant startup, its dynamic simulation should be performed by rigorous pressure-driven models. Pressure-driven DS is quite different from flow-driven simulation. Ordinary DS (flow-driven DS) is a good approach to cope with systems where the streams’ flow

rates are determined from material balance and are unaffected by downstream pressures. Pressure-driven DS, however, determines the flow rates by both upstream and downstream pressures, and thus system pressure boundaries have to be given before simulation. Pressure-driven DS models are generally more rigorous than flow-driven models. For instance, they can simulate reverse flow scenarios that flow-driven models are usually unable to handle. Generally, pressure-driven models consist of two types of models: pressure node models which set the pressure (i.e., tank, reactor, separator) and flow node models which describe the pressure drop and flow relationship (i.e., valve, pump, and pipe). Note that if two pressure nodes have flow relations, they must be connected through a flow node. In this paper, a rigorous pressure-driven DS methodology has been developed and used to study the dynamic performance of a cracked gas compression (CGC, a typical MSCS) system during an ethylene plant startup. The dynamic simulation helps the plant identify an improved startup procedure for better safety performance. General Methodology for Pressure-Driven Dynamic Simulation The developed rigorous pressure-driven DS methodology is the extension of previous work.15 It integrates the modeling activities and data acquisitions at three interactive stages as shown in Figure 2. At the first stage, model development starts with a setup of the SS model. During the modeling, pressure node and flow node models will be modeled and connected respectively. Meanwhile, system pressure boundaries and equipment dimension data need to be specified. Then SS is conducted to ensure the pressure balance and consistency among the entire modeling system, which is particularly required for pressuredriven modeling. The developed SS model should be validated by plant design data and/or some normal steady-state data obtained from a DCS (distributed control system) historian, during which model tuning and support from industrial expertise are usually necessary.


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Figure 3. Flow sheet of the five-stage CGC system.

If the system SS is satisfied, it should be transferred to the pressure-driven DS environment at the second stage. Two major types of data should be included to support the model transition. First, process control information including control strategies and parameters from a current plant P&ID (piping and instrument diagram) is needed. Second, new operating data from the plant DCS historian and/or industrial expertise are required to perform dynamic model validation. After validation, the DS model is ready for the third modeling stage. Before the system dynamic model is applied for the startup simulation, the entire model system should be adjusted to run at the initial state of startup, where initial feed data, initial valve opening position, and initial control parameters are required. Such adjusting activities need sufficient care because the initial state of the system DS model usually involves low-load running equipments and more auxiliary recycle streams than normal operations. As reported, the model transition task presents the most challenging step for the entire DS startup simulation.15 After the initial state of a startup is obtained, the DS model is ready to run for testing the startup procedures provided by the plant. Supposedly, the DS results will identify unexpected or unsafe operation conditions, which will be fed back to the plant operation group to recheck their previous operating procedures. The modified startup procedures will be iteratively tested until the DS model identifies viable/optimal operating strategies for the plant startup operation. Note that, during model tuning and troubleshooting, on-site industrial expertise is very important and required at every stage. CGC Process System Description In ethylene plants, the feedstock is sent through furnaces for thermal cracking. The effluent mixture from the furnaces is forwarded to the quench tower, where the cracked gas is cooled and partially condensed. Quench tower overhead vapor is sent to a five-stage CGC system for compression, so that the cracked gas will be at the desirable pressure for downstream separation. The CGC system is a vital and complex section in ethylene

plants. It consists of a series of compressors, drums, pumps, and a network of heat exchangers (see Figure 3). In flash drums, fluid is separated into two phasessliquid and vaporsor three phasessliquid, water, and vapor. In the two-phase drums, liquid is knocked out or recycled back to the previous stage drum, and vapor goes to the next stage. In those three-phase drums, the hydrocarbon liquid is knocked out of the system and water is fed back to the previous stage drum. Meanwhile, the vapor stream goes to the downstream stage. A caustic/water wash tower is positioned between the thirdstage discharge drum and the fourth-stage suction drum. The imported cracked gas may contain CO2, which will cause freezing problems in the downstream cold separation section, as well as contamination of ethylene product if handled incorrectly. Thus, CO2 is removed by the caustic wash tower before entering the fourth-stage suction drum. The condensate stripper accepts the hydrocarbon liquid feed from the fifth-stage suction drum. After this feed stream is heated and distillated, top products go back to the fourth-stage suction drum and bottom products flow out of the system. The dryer drum is located after the fifth-stage discharge drum, the vapor from this drum goes to the cold box, and light hydrocarbon is spilled back to the fifth-stage suction drum, while heavy hydrocarbon is circulated to the fifth-stage discharge drum. Figure 3 also shows the major control information for the CGC system. The first-stage suction drum pressure is controlled by regulating the turbine driving speed. The five compressors have the same rotation speed, since all the compressors share the same shaft and are driven by the turbine. There exist two minimum flow loops: the low-pressure recycling stream from the third stage to the first stage (see KB31 in Figure 3) and the high-pressure recycling stream from the fifth stage to the fourth stage (see KB54 in Figure 3). The caustic tower is not included in either of the minimum flow loops. KB31 is manipulated by a flow controller to control the third-stage discharge flow rate, and KB54 is designated to control the fifth-stage discharge flow rate. To provide surge protection for the compressor, the set

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points for these controllers are very conservative, and thus, the minimum flow valves are frequently open during normal operations. As the five compressors are sequentially connected and the head at each stage is sequentially increasing, this causes the operating envelope at each stage to be different. Qualitatively, this may cause such a problem that an operation with same flow rate that is near the surge point on the first-stage compressor may be close to the stonewall limit on the third or higher stage compressions. During the normal operation, this problem can be inherently avoided because a significant portion of cracked gas will be condensed and knocked out of the system at the second-stage discharge drum. Thus, the volume flow rate of cracked gas flowing to the third stage will be reduced, and the stonewall limit will not be violated. During the plant startup, however, a light feedstock (mainly methane, ethane, ethylene, propylene) will be used to shorten the entire plant startup. As the light feedstock has smaller molecular weight, surge is possible to occur on the first-stage compressor. To avoid this, a large volume of gas will be sent to the CGC system. The light feedstock has no condensation during the CGC system. Thus, the large volume gas probably causes stonewalling in downstream stages. Therefore, special control consideration for the CGC section during plant startup should be given. In this case study, a recycling stream from the second discharge drum to the first stage suction drum is built (see KB21 in Figure 3), which targets to control the operation point at the third stage away from the stonewall limit. CO2 contained in the cracked gas must be removed by the caustic tower. As mentioned, the existing CGC system minimum flow loops do not flow through the caustic tower. In order to get the caustic tower in service before cracked gas is introduced, a minimum flow loop, the so-called KB51, has to be introduced. This will allow stabilizing the caustic tower and help clean up the cracked gas before it enters the cold box. However this flow loop has a considerable pressure drop when the gas enters the first suction drum, resulting in a big temperature drop. Because the startup gas is wet, hydrate can be formed if the temperature falls below about 50 °F. To avoid this problem, KB51 is taken out directly from the fifth-stage compressor before the compressed gas is cooled. To start up an ethylene plant, cracked gas from each cracking furnace needs to be brought up to the CGC system sequentially and, then, sent to the downstream manufacturing process to produce on-specification products. During startups, the off-spec product streams are usually sent to the flaring system for destruction, which causes tremendous raw material loss and significant air pollution problems.16 An important method to minimize flaring during ethylene plant startup is to recycle the major off-spec product stream back to the input of the CGC system for reuse. Considerably, this gives rise to the new challenges for the CGC startup operations that have to be carefully investigated. Therefore, the pressure-driven DS has been conducted in this paper to study the dynamic performance and safety problems of the CGC system during an ethylene plant startup. Modeling for the CGC System Modeling a CGC system starts at developing the steady-state process model, which is already shown in Figure 3. To speed up the computation without the sacrifice of the simulation accuracy, one simplification in this study is that heating/cooling duties of heat exchangers are lumped into duties of their closest downstream drum. Thus, the temperature control loops in Figure

3 are applied to manipulate flash drum cooling duty instead of the heat exchanger duty. This simplification will have the same vapor flows, identical head, and flow as the rigorous model but can significantly reduce the modeling complexity and computational load. This strategy has been demonstrated by Bernard as it will reduce the number of inputs and keep the dynamic simulation easy to converge.8 After the model is set up to match the P&ID of the CGC system, it is initialized with parameters obtained from the real plant. Those parameters include the following: compressor performance curves; flash drum tower dimension data such as vessel type, geometry, and holdup level; valve pressure drop; control strategies; and controller parameters. The results of SS simulation are compared with the plant data, and it is confirmed that the model simplification does not affect the simulation results. After the SS model is validated, it is exported to the pressure-driven DS environment. Note that the entire SS model is developed with the commercial software tool, Aspen Plus, and the pressure-driven DS model is implemented in Aspen Plus Dynamics. All the control strategies and control parameters are then setup as shown in Table 1. Since completed DS validation data are not available from the real plant, a qualitative check in terms of DS response trend and time has been conducted and accepted by plant engineers. Startup operation is the transient operation of system/plant from the initial state to normal operation conditions. Thus, to simulate the startup procedure, the DS model needs to be adjusted to the initial conditions for startup. To shorten the startup time, the light component mixtures will be used to “warm up” the entire plant to the initial condition. Under the conditions for startup, the entire ethylene plant including the CGC system, cold box, and recovery sections are running stably without any fresh feed. Meanwhile, all the production streams from a downstream process will be totally recycled back to the input of CGC. As expected, a light hydrocarbon mixture containing hydrogen, methane, ethane, ethylene, and propylene will be circulated in the CGC system at the initial conditions for startup. Note that tuning the DS model to the initial condition for startup requires sufficient care, because the initial state involves lowload running equipments with multiple recycles. As a result, it may be difficult to get the model to converge. After the initial state is attained, the dynamic model is ready to run the startup procedures provided by the plant. It should be noted that in a pressure-driven model, all of the flow rates in the flow sheet must be determined by the pressures boundaries of system and pressure/flow relationship within each units. To make the flow sheet suitable for a pressure-driven simulation, valves are required between feeds and flash drums, drums and drums, and outlet streams and drums in the steadystate model before turning it into a dynamic model. In the dynamic model, the valve flow coefficients are adjusted to meet the hydraulic constraints. Simulation Results and Analysis With the developed DS model, startup procedures can be input to the model for a virtual test. Figure 4 shows a practical plant startup procedure, which includes dynamic changes of the flow rate for cracked gas feed, the controlled compressor outflow, and various recycle streams. Note that the cracked gas feed from heavy naphtha cracking furnaces (the first two furnaces) is incremented in two ramps for each of the first two furnaces with a 30 min duration in between. The feed from the light naphtha cracking furnaces (the third-seventh furnaces) are also incremented in two ramps for each furnace but without any idle


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Table 1. Control Strategy for the CGC System controller

PV

MV

PC1 TC1 LC1 TC2 LC2 LC3 TC3 LC4 TC4 LC5 TC9 TC5 LC6 LC7 TC6 LC8 LC9 TC8 LC11 LC12 LC13 FC1 FC2 FC3 FC4 TC7 LC10 PC2

first suction drum pressure first suction drum temperature first suction drum liquid level second suction drum temperature second suction drum water level second suction drum heavy hydrocarbon liquid level third suction drum temperature third suction drum liquid level third discharge drum temperature third discharge drum liquid level dryer overhead stream temperature caustic/water wash tower top temperature caustic/water wash tower liquid level fourth suction drum liquid level fifth suction drum temperature fifth suction drum water level fifth suction drum heavy hydrocarbon liquid level fifth discharge drum temperature fifth discharge drum liquid level dryer water level dryer heavy hydrocarbon liquid level third discharge flow rate fifth discharge drum top flow rate second discharge flow rate fifth discharge (KB51) flow rate condensate stripper stage 14 temperature condensate stripper sump level condensate stripper top pressure

compressor speed heating duty first suction drum bottom flow rate cooling duty second suction drum bottom water flow rate heavy hydrocarbon flow rate from the second suction drum cooling duty third suction drum bottom flow rate cooling duty third discharge drum bottom flow rate cooling duty heating duty caustic/water wash tower bottom flow rate fourth suction drum bottom flow rate cooling duty fifth suction drum bottom water flow rate fifth suction drum bottom drum heavy hydrocarbon flow rate cooling duty fifth discharge drum bottom flow rate dryer bottom water flow rate dryer drum heavy hydrocarbon flow rate recycle flow rate from stage 3 to stage 1 recycle flow rate from stage 5 to stage 4 recycle flow rate from stage 2 to stage 1 recycle flow rate from stage 5 to stage 1 condensate stripper heating duty condensate stripper bottom flow rate valve opening

waiting between two furnaces. These entire dynamic changes are also the input of the DS model. Also note that the startup simulation is actually started at the beginning of the first hour, before which the CGC system is at its initial conditions. As the dynamic operation of the first-stage compressor determines the shaft speed changes, which is very critical for CGC operation, special analysis should be conducted. Figure 5 gives the dynamic response of the first suction drum pressure and compressor speed. As shown, the pressure of the first suction drum drops quickly at the beginning of the startup. This is because when the heavy naphtha cracked gas begins to come in the first-stage suction drum, the recycled flow rate from the third-stage discharge to the first-stage suction is reduced quickly to maintain the constant flow rates, which results in a pressure reduction. In turn, this causes the compressor speed decrease correspondingly to pull back the pressure (see Figure 4). When the pressure exceeds the set point at 4.2 h due to the recycle flow rate increment at KB31, the compressor speeds up to take more gas out, then makes the pressure return to the set point. The simulation result also shows that the compressors are

running within the compressor speed limits. Thus, the onsite control strategy is effective for first-stage pressure control during the startup period. Figures 6-8 show the dynamic temperature-pressure-flow rate (TPF) responses of the inputs to the first-stage, the fourthstage compressors, and the CGC system output. Note that the third-stage and the fourth-stage compressors are separated by the caustic wash tower, which makes the operation of the fourthstage compressor as critical as the first-stage compressor. Generally, as the cracked gas feed comes in the CGC system, the flow rates increase and finally reach their new steady-state

Figure 5. Simulation result for the first-stage suction drum.

Figure 4. Plant startup procedure.

Figure 6. TPF plot for the input stream of the first-stage compressor.

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Figure 7. TPF plot for the input stream of the fourth-stage compressor.

Figure 10. Dynamic performance of the first-stage compressor during the plant startup.

Figure 8. TPF plot for the output stream of CGC system.

Figure 11. Dynamic performance of the second-stage compressor during the plant startup.

Figure 9. Molecular weight response of different streams during the startup.

value, i.e., the normal operation condition. Since the pressures of these streams are the same as the pressure of their associated suction drums, the pressure response generally follows the controller set point change according to the startup procedure. Temperatures changes are not significant with the maximum 15 °F difference occurring at the dip between the sixth and tenth hours in Figure 6. This happens exactly when the light naphtha cracked gas comes into the system. The flow rate of the new feedstock increases very quickly, which is accompanied by flow rate reduction of KB21 according to the startup schedule. Meanwhile, the flow rates for recycling feed from downstream and KB51 also drop (see Figure 3). All these flow rate reductions from high pressure streams cause both pressure and temperature drops in the first-stage suction drum. Figure 9 shows the dynamic changes of molecular weight (MW) at the first-stage inlet, the fourth-stage inlet, and the output stream from the CGC system. The MW data is important information to characterize compressor operation status, because too low/high MW under a fixed mass flow rate may cause dangerous surge/stonewall situations. To identify the dynamic performances of the five compressors, the operating status for

Figure 12. Dynamic performance of the third-stage compressor during the plant startup.

each compressor is tracked during the startup and shown in Figures 10-14. Note that the operation status of every compressor at any time needs to be evaluated during the startup. Thus, the operating point and envelope shown in Figure 1 have to be augmented by another dimension of time. This results in the 3D figures shown in Figures 10-14. In each figure, the operating


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compressor theory. The behavior of a common compressor can be explained using both the adiabatic and polytropic process. The industry accepted practice is to use adiabatic equations for a single-stage compressor, while using polytropic equations for all other situations. In our study, the polytropic equations are employed to study the CGC performance. The polytropic compression process involves heat transfer. It is an irreversible variable entropy process, which is described by the following equations:

( )

Pout Vin ) Pin Vout

n

)β

(1)

n k ) η n-1 k - 1 pol

(2)

k) Figure 13. Dynamic performance of the fourth-stage compressor during the plant startup.

() Cp CV

(3)

where Pout is outlet pressure; Vout is outlet volume flow rate; Pin is inlet pressure; Vin is inlet volume flow rate; n is the polytropic coefficient; β is compression ratio; ηpol is polytropic efficiency; k is heat capacity ratio; and Cp and CV are constant pressure and volume heat capacity, respectively. Note that eq 1 for the polytropic compression already embeds the polytropic efficiency. The advantages to using the polytropic approach include: (i) Polytropic calculation is easier to perform, especially in the determination of discharge pressure. (ii) The sum of the polytropic head for each stage of compression equals the total polytropic compressor head, which does not hold true for adiabatic head calculation. (iii) Polytropic efficiency is independent of the thermodynamic state (pressure, temperature, and molecular weight) of the gas undergoing compression. In reality, the polytropic efficiency curve needs to be determined by the inlet volume flow rate and compressor speed. The general form of the polytropic head equation is Hp )

Figure 14. Dynamic performance of the fifth-stage compressor during the plant startup.

envelope forms a “closed wall”, which can not be touched by the operating point at any time. Such dynamic performance evaluation provides the most valuable insights to the CGC system, which can only be accomplished through rigorous dynamic simulation. As shown, the results clearly demonstrate all compressors are running within the closed wall. Therefore, the compressors are virtually running safely. To ensure the simulation results are fundamentally reliable, the results are double checked according to basic polytropic

1545ZinTin n [βn-1/n - 1] MW n - 1

(4)

where Zin is the inlet compressibility factor; Tin is inlet temperature; Hp is compressor head; MW is molecular weight; n is the polytropic exponent; and R is the gas constant. On the basis of the above equations, when compressor input data (Pin, Vin, Fmr, Tin, MW), part of output data (Vout), and the compressor ηpol are given, the discharge pressure (Pout) and compressor head (Hp) can be rigorously calculated. To verify the DS simulation results that have been obtained, the Pout and Hp of five compressors at the end of startup are calculated based

Table 2. Compressor Performance Comparison between DS Results and Polytropic Equations compressors

stage 1

stage 2

stage 3

stage 4

stage 5

77.02 2407190.00 105.07 31648.70 1374797.37 0.71 1.169 29.30

127.02 1375160.00 107.08 30188.50 805743.14 0.72 1.174 27.84

247.74 678693.00 89.06 31912.00 388260.54 0.69 1.175 27.77

155.58 155.62 21782.60 21767.60

249.14 249.00 21649.20 21602.71

505.16 505.02 21057.70 21029.66

given data Pin (psi) Vin (ft3/h) Tin (°F) Fmr (lb mol/h) Vout (ft3/h) ηpol K MW (lb/lb mol)

20.69 9447600.00 108.34 32359.90 5217774.99 0.79 1.177 28.92

Pout from DS (psi) Pout from polytropic equation (psi) Hp from DS (ft) Hp from polytropic equations (ft)

43.10 43.11 23720.60 23699.75

39.10 4908970.00 105.04 32259.70 2690817.06 0.77 1.167 30.49 calculation comparison 81.82 81.82 22262.10 22237.33

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on eqs 1-4. The comparison is shown in Table 2. It shows the DS results are very reliable. Note that polytropic efficiency in the case study is actually provided by the plant as a constant at each stage, according to manufacturing practice. On the basis of the validated DS model, the original startup procedure is investigated to seek operational improvement opportunities. As mentioned before, the first-stage compressor speed has approached 4440 rpm between the second and the fifth hour, which is too close to the lower limit speed (4419 rpm) at the beginning of the startup. Note that too quickly changing of the compressor speed during the startup may cause the compressor to run out of its operating envelope, which should be avoided at any possibility. Although the first-stage compressor is still in feasible operation, however, it might have potential possibilities to run out of the operating envelope due to some unpredicted uncertainties, such as feed flow rate and pressure disturbances. To comprehensively consider the inherent safety of compression system during plant startup, operation procedures need to be carefully developed to balance startup safety and startup speed. Aggressive operations that have potential danger to a process system should be adjusted with a lower operating change rate. To thrust such a solution, detailed analysis for the startup procedure has been conducted to identify the root cause that pushes the operating speed to the lower limit. As shown in Figure 4, the third and the fifth compressor discharge flow rates are constant before they are manipulated to increase at the time of the third hour. When the heavy naphtha cracked gas comes in at the time point of 1 h, the recycled flow rate from the third stage discharge to the first stage suction cuts back quickly (see Figure 5). A similar cut back occurs for the recycling stream from the fifth stage discharge to the forth stage suction. Since these recycling streams are at higher pressures than that of the cracked gas input, the cut back of the recycled gas influences the pressure reduction in the first suction significantly. To maintain the gas throughput, the compressor speed has to decrease. On the basis of the analysis, recycle cut-back time delay or magnitude reduction will supposedly avoid the sharp decrease of compressor speed and the significant reduction of pressure. With the help of DS, it is found if the starting time to increase the discharge flow rates of the third and fifth stages shifts from the third hour to the first hour, the speed starts to decrease with the startup and dip at the speed of 4466 rpm. Because the startup procedure is adjusted to mitigate the upset from feed flow rate increase, the pressure of the first-stage suction drum becomes more stable than before. For comparison, the new startup procedure and the simulation results for the first-stage compression is shown in Figures 15 and 16. The results demonstrate that rigorous dynamic simulation is very important for CGC system on safety operation and optimal startup procedure identification. On the basis of the developed DS model, this work can be extended in the future to advance current control strategies to improve CGC system performance under mild disturbances, plant turnaround, and emergency situations. Also note that theoretically, simultaneous consideration of startup speed and safety will involve a multiobjective optimization problem. In current practice, however, people would like to consider the startup issue as a hierarchical problem, which means startup safety always has higher priority than startup speed. Thus, this paper presents a precautionary way to improve the startup performance based on dynamic simulation, process analysis, and engineering experience. The simulation results in

Figure 15. Improved startup procedure.

Figure 16. TPF plot for the first-stage suction drum under the improved startup procedure.

this paper have shown the benefits. Certainly, to optimize the startup strategy based on rigorous multiobjective optimization is a wonderland for the problem if startup safety and speed could be well-quantified and integrated. This will present a very challenging task that requires a great deal of research effort in the future. The development of this work has provided a solid foundation for future thrusts. Concluding Remarks Multistage compression systems are the most important and valuable facilities in the chemical plants, whose failure may cause severe accidents and/or tremendous economic loss. Rigorous dynamic simulation is an efficient and effective way to improve MSCS operation performance, especially during plant startup. In this paper, a rigorous pressure-driven DS methodology has been developed and employed to study the safety performance of an MSCS during an ethylene plant startup. On the basis of the DS, precise dynamic responses and operating point trajectories for each compressor are disclosed. An optimal startup procedure with better safety performance is also obtained. Acknowledgment This work was in part supported by the Texas Commission on Environmental Quality (TCEQ) and Texas Air Research Center (TARC). Special thanks should be given to Dr. Jihong Wu from KBR. Inc. and Mr. Andre Bernard from NOVA Chemicals (Canada) Ltd. for their kindly support. Literature Cited (1) Krietenstein, S.; Taylor, M. Flare minimization at Dow Freeport; AIChE Spring National Meeting: Atlanta, GA, April 10-14, 2005.

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ReceiVed for reView February 6, 2009 ReVised manuscript receiVed July 22, 2009 Accepted September 7, 2009 IE900212V

Pressure-Driven Dynamic Simulation for Improving the Performance of

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