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CONTROL STUDIES OF A COMPLEX GAS PHASE REACTOR SYSTEM D. B. Aldren and P. I (; ! 1'/(, l:.:lIgi IlI'ITillg [)('jmr/lllfII/,

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Abstract. A dynamic model of a continuous gas phase reactor has been developed . The purpose of this model has been to improve the understanding of a highly complex exothermic mu l ti-stage reaction system with the objectives of increasing both plant throughput and reaction se l ectivity . The model has been used to examine the dynam i c relationships between the main variables ; feed rates, operating temperatures and heat inputs . Th e simulation studies described in this paper are a significant advance in e xplaining

the behaviour and control of the reactor. increasing plant output are indicated .

Methods o f improving this contro l and of

INTRODUCTION The plant being studied is a continuous gas phase reactor system which includes a fluidised bed fo ll owed by reactors in series . The plant was designed , built and commissioned in a very short timescale with only limited data avai lab l e from pilot plant trials. During the post -commissioning

Reaction 1 requires a catalyst and is carried out in a fluidised cata l yst bed . Reactions 2 & 3 take place both in the fluidised bed catalys t d isengagement space and in a downstream secondary reactor .

period difficulties were experienced in maintaining

steady s tate operat i on and realising design production rates . The optimisation of the complex system proved difficult due to the large number of plant variab l es which could be adjusted . A dynamic model was built to study the interactions of the process , plant and control systems . The primary objective was to improve the product make by impr oving the understanding of the system and developing operating st r ategies . This paper out l ines the development of the dynamic model and its subsequent use to assist plant operation and examine alternative control systems. THE PLANT AND PROCESS For comme rcial reasons , the specific details of the process described in this paper c annot be given. However the process invo l ves sequential gas phase reactions; the dominant react i o n s are

is is is is

The main control sytems for the reactor include a

i ndependent f l ow control for the f eeds A, Band C , and diluent Nitrogen.

b

contro l of the f l uidised bed temperature using circulating heat trans f er oi l.

c

control of heat input , to the transfer pipe and secondar y reactor walls , us ing electrica l tracing,

Contro l of reaction 1 in the fluidised bed had been good , however, control of reaction 2 and 3 in the reactor headspace and secondar y r eactor had been poor . The reaction is exothermic with the heat being removed by temperatu r e inc rease of the gases , which inc l ude di luent nitrogen , and heat losses to ambient. This heat balance which essentially governs the temperature and extent

1 A + B + C X + P 2X+B Y+ P Y+B Z+P where X Y Z P

Figure 1 illustrates the overall reactor systeM. The use of a secondary tubular reac tor is t o increase the yield o f product Y. For sequential reactions it is known that yie ld is encouraged by a plug flow system , Figure 2 indicates the increase in yield compared to that for a single stage system .

a reaction intermediate the desired product an over -r eacted by - product an inert by- product

of reaction is sensitive to changes in reacto r

Other reacti ons occur with both further intermediates and by- products being formed . Components X, Y and Z account for some 75% of the total products. The reactions have also been simplified by igno ri ng under reaction for 1 , ie a ll A is reacted with X, and by consider ing compounds with simi l ar extents of reaction together. This assumption is defended on the grounds that the purpose of the model was to predict the dynamic variati on in Y made rather than to predict the complete product spectrum .

(ii

feed rates , bed temperature a nd trace heating inputs . With r elative l y sma ll reaction exotherms and significant heat capac iti es i n th e equipment walls , there are several l ong l ags in the system and steady state contro l i s difficu lt to achieve. To improve the contro l and to al l ow operation at h i gher rates, a better unde r standing f o r the system response was required . To achieve this understanding f or a comp l ex interactive system, it was decided to develop a dynamic mode l o f the reactions occurring downstream o f the fl uidised bed .

68

D. B. Aldren and P.

J.

losses to the surro undings. 'The heat balance for the gas flow assumes a well mixed CSTR. The MACRO has been configured to allow additional N2 and 'B' flows at spe c ified inlet temperatures. A heat flowrate term has also been included to allow for catalyst carry over, say from the fluidised bed into headspace. In practice this facility was not used.

DYNAMIC MODEL The dynamic simulation language used to model the plant is the 'Advan c ed Continuous Simulation Language', ACSL (ref 1 ) . The language is a high level, FORTRAN based, user friendly package which may be used interactively to give on-line control of the simulation. The models are prepared from an equation or block diagram description. Libraries of commonly used model elements have been created within ICI enabling complete models to be easily and quickly assembled using a building block approach, The 'lumped' modelling technique, which assumes homogeneous elements, has been used extensively; with distributed systems being modelled by dividing into a finite number of lumped elements in series. The dynamic elements of the model include the reactor headspace, transfer pipe and the secondary reactor.

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3.

TRANIO: models a temperature transmitter as a first order lag with a selectable time constant This was used for temperature measurements throughout.

4.

CONTB: models a three term controller with selectable tuning parameters. This was used for temperature control of the heat tracing on the transfer pipe and secondary reactor.

5.

MOTOR: models a valve actuator with selectable stroke time for th e tlitro g c n c ontrol . valve.

As with all models, there is a compromise between too simple a system description and too much complexity which leads to excessive computation time and overspecification of parameter s . To achieve a time and cost effective model, certain assumptions have to be made. In this model the following assumptions were made

6.

GVALV: models a gas valve with selectable characteristics. This was used for the additional Nitrogen flow control to the fluidised bed. The valve sizing gives a maximum Nitrogen flowrate of 100 mass units/hour

a A simple non-dynamic and empiri c al model was chosen to describe the fluidised bed. This model was based on previous laborato ry and kinetic studies and describes the di s tribution of major reaction c omponents leaving the fluidised bed. The model related the concentration of 'X' to the primary parameters, bed temperature, residence time, and 'B/A' feed ratio. For a given 'X' concentration, the distribution of 'y' and '2' were calculated.

a

Continuous calculation o f the component distribution from the fluidised bed allowing the bed and feed flowrates to be c hanged during simulations.

b

The inital section of the model calculates, the Arrenhius constants, the initial concentrations for each cell, the average specific heat of the gas, and converts flowrates from mass to molar.

Main Assumptions

b Reactions 2 and 3 are described as first order Arrhenius type expressions

cU.Y) dt ~)

dt

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= A, exp (-E/ RT)

(X)

(B)

A, exp (-E/ RT )

( Y)

(B)

dt d(Y)

dt

where (B), E is both T is R is

Additional features included in the model are:

The main inputs to the model include Flowrates for A, B, C and Nitrogen Bed temperature Wall set point temperatures Typical outputs include for each cell

(X), (Y) and ( Z) are molar concentration s activation energy, assumed the same for reactions absolute temperature the universal gas constant

c The reactor sytem was described as a series of continuous stirred tank reactors (CSTRs) or well mixed vessels. The flow pattern in the reactor disengagement headspace will be complex; a simple 2 cell model was however considered to be adequate on the basis of previous plant data. Although the transfer pipe and secondary reactor are more properly described by a plug flow model, most of the reaction is complete before the gases reach this section and no significant loss in accuracy should occur if a CSTR model is used for each unit. This simplification allows the definition of a basic model element (the cell) to describe the various reaction stages.

Product distributions Gas temperatures Wall temperatures SH1ULATION STUDIES The model has been used for both steady state and dynamic simulation studies. Steady state simulations may be carried out by effectively ignoring the large time constants of the reactor walls and insulation eg by setting wall and insulation densities to small values. Steady state results have already been used to determine stable operating points for the plant to give improved product yields. This report is concerned with dynamic simUlation. Dynamic simulation runs were carried out

The basic cell a

on the existing plant control system to obtain a better understanding of the response of the reactor to changes in the main control variables,

b

on alternative control systems and potential plant developments

The basic cell with typical input and output is shown in Fig 3. The model consists of the following specific elements (MACROs) and standard elements from the ICI libraries. 1.

2.

REAC: describes the reaction kinetics for a CSTR for reactions 2 and 3. In addition the MACRO calculates the heats of reaction and component concentrations.

HPAN: describes the heat and mass balance for the gas flow reactor wall, insulation and heat

For these runs, the model was used to describe the system response, from steady state, to a step change in one of the main operating parameters.

Complex Gas Phase Reactor Svslem The base case operating point used in the majority of the simulation runs is described by the following

69

Transfer pipe wa l l temp set point 350 degC

a ' B ' flowrate of 330 units/hour the transter pipe wa l l temperature set point was increased from 350 to 390 degC . Fig 9 shows the response of the gas temperatures in the transfer pipe and secondary reactor increasing by 20 degC in 0.4 hrs Fig 10 shows the effect on the product concentrations in the transfer pipe and exit the secondary reactor . TIle transfer pipe wall temperature takes approximate l y 0.3 hours to reach the new setpoint . Th e wa l l temperatures must be optimised as part of the overa l l plant operating strategy .

Secondary reactor wall temp set point 350 degC

Al ternative Control Systems

This base case corresponds to a final reactor exit gas composition of

Sensitivity trials using the model indicated that the headspace gas temperature could be controlled by several methods, with improvements in the overall contro l of reaction. The most practical and simple method is to control the flow of diluent Nitrogen to the bed. The advantages of controlling the nitrogen are; it does not affect the stochiometry of the reactions, it is readily available a reasonable cost and presents no post processing problems. The model has been used to examine the effects of controlling the upper head space gas temperature by adjusting the nitrogen flowrate between 0-100 units/hour above a base flowrate of 125 units/hour , required to fluidise the bed. The control l er set-point has been initiated to approximately .the 'talue found ;,n previous results for ~he same I B t flowrates. A simulation run with 'B ' increased from 330 - 35 0 units/hour has been undertaken. The controller tuning parameters used were

Flows to the fluidised bed

Fluidised bed temperature

X Y Z Others

3% 50% 20% 27%

A B C N2

100 350 100 150

Mass Mass Mass Mass

units/hour units/hour units/hour units/hour

350 degC

molar molar molar molar

Extensive sensitivity trials have been undertaken to examine both over and under reaction. The simulations included in this paper give an indication of the plant responses and the main interactions

Gas Temperature Control The headspace gas temperature has no direct closed loop control system on the existing plant . The temper~ture is manipulated by adjusting the flow controller setpoints . The transfer pipe and secondary reactor control systems were originally designed to control the gas temperatures by manipulating the heat input to the respective walls by means of electrical heat tracing. The model was used to confirm that the control systems were impractical due to the large difference between the gas residence times and the thermal time constants of the walls eg for the transfer pipe the gas residence time is typically 4 seconds whereas the thermal time constant of the wall is approximately 1200 seconds. The model was used to investigate the effect of reconfiguring the control sytems to maintain constant wall temperatures. Installation on the plant has prevented damage to the heat tracing from high temperatures and stabilised the plant by el i minating oscillations in the wall temperatures . This modification is considered part of the existing control sytems throughout the rest of the study . Response to 'B ' flowrate changes As both these simulation runs and p l ant experience indicate that the system is particularly sensitive to changes in the 'B ' flow, this response will be examined in some detail. The 'BI f l owrate was reduced from 350 to 330 units/hour at 0 . 5 hours simulation time . Figs 4 and 5 shows the rapid reduction in the gas temperatures throughout the plant eg headspace temperatures drop by 30 deg C in a few minutes. The gas temperature continues to fall at a reduced rate after 8 hours . Fig 6 shows the headspace wall temperature responses confirming the long time constants. Fig 7 and 8 show the gas component concentrations exit the secondary reactor. The initial rise in product concentration is followed by the s l ow reduction as the simu l ation continues. The results demonstrate the difficulties experienced by plant operators in attempting to maximise product make at acceptable by- product concentrations. Responses to reactor wal l temperature changes The transfer pipe has been chosen to demonstrate the effect of changing the wa l l temperature , achievedby changing the contro l ler setpoint . With

Proportiona l gain; 10 . 0 Integral action ; 40 seconds Derivative action ; 400 seconds Fig 12 shows the exit product concentration and the main waste by-product concentration increasing by 0.5 and 1% respectively . The simple closed loop control system is difficult to tune to give improved response. Some of the factors limiting the performance of the contro l system are; the measurement time constant of 15 secs, the valve stroke time of 10 secs, the lag of the ni crogen flow through the fluidised bed (not model ' ed) and the limited heat capacity of the nitrogen entering the headspace at the bed temperature of 350 degC. The lags are significant when compared to the gas residence time of the headspace which is typically 40 secs. The simulation demonstrates the headspace temperature can be controlled to improve product yield. Further developments such as introducing nitrogen at a reduced temperature directly to the headspace have been simulated with improved control. However , no plant data on the effects of the mixing in the heads pace are availab l e. The simple control sy.6'-~ 1!I would require minimum plant modifications , whereas the more comp l ex schemes would require significant and cost l y changes . CONCLUSIONS The mode l explains the observations .From the plant that the reactor system is difficult to contro l ie it is not easy to maintain optimum product concentrations in the off gas. The simulation runs indicate the highly sensitive and non-linear response of the 'B' flow, the rapid response of the reacting gas system and the long lags of the reactor walls. With variations in feed rates , general "noise", and limited off gas analyses (only every few hours) it is not sur prising that good steady control is difficu l t to achieve . Plant experience and the model resu l ts have already shown that the original strategy

D. B. Aldrell and P.

70

of controlling the secondary gas temperatures by adjusting the electrical heat input into the t r ansfer pipe could be improved. This work has shown t hat maintaining a constant environment in the transfer pipe and secondary reactor , by controlling wa l l temperatures , is more appropriate and that change has already been made. This study has also shown that the control of the reactor could be improved by headspace temperature c l osed loop control Further simulat i on runs and plant validation work are underway to confirm these advantages .

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Further work is continuing to improve product yield with several developments in c luding those outlined in this paper being inve stigated in more detail. REFERENCES ACSL User Guide/Reference Manual, MGA Associates USA Dynamic Model Libraries Vol 1, PANMAC & CEGMAC, User Guide/Reference Manual, Control Applications , ICI Engineering Dept .

The dynamic modelling has formed part of a wider de- bottlenecking and development study. The results of the overall study have been that plant performance has improved from operating at 70% of design capac i ty to operating for sustained periods at 200% design.

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