Journal of Applied and Industrial Sciences, 2014, 2 (2): 46-57, ISSN: 2328-4595 (PRINT), ISSN: 2328-4609 (ONLINE)
Research Article 46
Abstract-Catalytic cracking to produce products of higher octane
number is rather important and needs always to be under
investigation and development. It is not an easy process, but it is
difficult due to the deactivation of the catalyst, deposition of coke
and poisoning by heavy metals. The manipulative and controlled
parameters of the regenerator(s), reactor and firing air may be
interacting. In this study two catalyst regenerators are designed
for control loops with single-input single output (SISO). A ratio
controller for air/fuel and a temperature controller are used to
adjust the air/fuel ratio and their rate. Where the temperatures in
the two regenerators were controlled by manipulating the rate of
the inlet hot air. Levels, temperature and steam rate were also
controlled as well as the top pressure in the regenerators through
manipulation of the exit flue gas. The control strategy was
developed, the overall transfer functions were identified and the
characteristic equations were used for stability analysis, tuning
and response simulation, as shown in Tables 1 through 7 and
Figures 2 through 13.
Index Terms -: Catalytic cracking, Tuning and Stability
1. INTRODUCTION
Petroleum refinery is an industrial process plant where crude
oil is processed and refined into more useful products such
as petroleum naphtha, gasoline, diesel fuel, asphalt
base, heating oil, kerosene and liquefied petroleum gas [1].
Fluid catalytic cracking is one of the most important conversion
processes in a petroleum refinery, it also occupies very
significant position in the refinery because of its economic
benefits, and the process incorporates most phases of chemical
engineering fundamentals, such as fluidization, heat/mass
transfer, and distillation. The heart of the process is the
reactor-regenerator, where most of the innovations have
occurred since 1942 [2].
Heavy Oil vapors are cracked to gasoline and fuel oil plus
low-molecular-weight Paraffins and olefins by contact with
very hot particles of fine zeolite–silica–alumina catalyst. The
catalyst provides energy for vaporization of the feed and for the
endothermic reactions. A few percent of the feed forms
carbonaceous deposits on the catalyst, rapidly decreasing its
activity, so frequent regeneration is necessary. Spent catalyst is
continuously removed from the reactor and sent to the
*Corresponding author Email: [email protected]
regenerator, where air is introduced to burn off the ‘‘coke,’’
reheat the catalyst, and restore its activity. In early versions of
the FCC process, the reactor and regenerator were fluidized
beds placed side by side as seen in Fig. 1.
Figure1: FCC Unit (Peter 2003)
Catalyst from the reactor passed down by gravity through a
stripper, where up flowing steam displaced the hydrocarbon
vapors and maintained the solid in a fluidized state. The catalyst
then flowed in a transfer line to a point below the beds, where it
was picked up by the air stream and carried into the regenerator.
It is important to separate catalyst and vapors as soon as they
enter the reactor, otherwise the extended contact time of the
vapors with the catalyst in the reactor housing will allow for
non-selective catalytic recracking of some of the desirable
products. The extended residence time also promotes thermal
cracking of the desirable products [2]. Catalyst from the
regenerator flowed through another transfer line to a tee
junction, where it joined the oil feed and passed up into the
reactor.
Other versions of FCC units had different methods of
controlling the solid flow between reactors in one
Improved Control Strategy of Residue Fluidized-bed
Catalytic Cracking Unit
Sahar .A. Salih*1, Mustafa. A. Mustafa
2, Gurashi. A. Gasmelseed
3
1Faculty of Graduate studies, University of Karary, Khartoum-Sudan
2 Department of Chemical Engineering, University of Khartoum, Khartoum- Sudan
Email: [email protected] 3Department of Chemical Engineering, University of Science and Technology, Khartoum- Sudan
Email:[email protected]
(Received: December 01, 2013; Accepted: April 04, 2014)
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Journal of Applied and Industrial Sciences, 2014, 2 (2): 46-57, ISSN: 2328-4595 (PRINT), ISSN: 2328-4609 (ONLINE)
‘‘single-vessel’’ unit, the reactor was placed on top of the
regenerator. However, the biggest change came after the
introduction of very active zeolite catalysts and the realization
that much of the cracking took place in the transfer line carrying
catalyst into the reactor. Current designs feature a riser reactor,
a tall, small-diameter pipe, where all the cracking occurs as
catalyst particles are carried upward at high velocity by the oil
vapors. The gas–solid suspension is discharged through
cyclones into a vessel that serves as a stripper and a feed
reservoir for spent catalyst. The regenerator is a large reactor
(up to 18 m in diameter) with a bed depth of 10–15 m, and it is
often the largest vessel in the refinery. Some steam is fed to the
bottom of the riser to strip any hydrocarbon and maintain
fluidization until the feed oil is vaporized [3]. Gas and solid exit
the riser horizontally through swirl nozzles that make some of
the solids drop out prior to the cyclones. Steam is introduced at
several points in the multistage stripper to maximize
hydrocarbon removal. The regenerator is operated in the
turbulent regime at superficial velocities of 0.3–1.0 m/sec,
which is over 100 times the minimum fluidization velocity.
Entrainment of fines is severe, and the top of the regenerator is
crowded with many sets of two-stage cyclones. The cyclones
recover over 99.99% of the entrained solids, which are returned
to the bed through dip legs discharging below the top of the
bed. Most of the oxygen is consumed in the reactor, but the
catalyst is not completely regenerated. Because of solids
mixing, there is a wide distribution of residence times and a
corresponding distribution of carbon content on the catalyst
particles. Typically, over 90% of the carbon is burned off.
Two-stage regenerators are used in some refineries to with
operational problems due to the high nonlinearity of such
systems [3]. Both CO and CO2 are produced as the coke burns,
and some CO is oxidized in the gas phase, the rest of the CO
can be burnt to generate steam. Oxidation of CO above the bed
can lead to large, undesirable temperature increases, and some
catalysts are promoted with platinum to favor CO oxidation in
the bed [3].
Control of FCCU
The control problem of fluid catalytic cracking (FCC) units is a
challenging task due to its model complexity, non-linear
dynamics, constrained variables and cross-coupling interaction
between inputs and outputs [4]. Baker developed optimal
system of a two cascade closed-loop system which takes the
conversion percentage as the optimal variable because it is the
direct measurement to the degree of reaction and can be
calculated online from the products distribution of FCCU, used
a neural network to predict this conversion percentage online
and at real-time because there may be a large time-delay to
calculate the conversion percentage. Based on this, closed-loop
optimization is achieved by the uses of online observation for
feeds property and adaptive intelligent optimal method and the
yield of light oil increases about 0.6% [5]. ChenZiluan
Developed a design of multivariable feedback control
configurations for composition control at the riser output for
FCC units. Numerical simulations on a non-linear dynamical
model operating in the partial-combustion mode are used to
show the effectiveness of several multivariable control
configurations under disturbances and uncertainty parameters
[6]. Raluka developed a dynamic simulator of the fluid catalytic
cracking (FCC) pilot plant, The operation of the pilot plant
permits the execution of case studies for monitoring of the
dynamic responses of the unit, by imposing substantial step
changes in a number of the manipulated variables [7].
Madhusudana developed a case study of an object-oriented
model for automatic generation of a fluid catalytic cracking unit
(FCCU) reactor/regenerator is presented [8]. Bollas applied the
calculation of the optimal set points by considering the
closed-loop dynamics, focusing in particular on rigorous
handling of input saturation effects [4].
The main objectives of this study is to develop a control
strategy for tight control of the residue Fluidized-bed Catalytic
Cracking Unit (RFCCU) for improvement of performance of
the Base Case shown in Fig. 2 as well as to identify the control
functions, stability analysis, tuning and response simulation of
the RFCCU.
II. MATERIALS AND METHODS
Two control strategies were developed as shown in Fig. 1 and
Fig. 2.
Control Loops Identification
1. Temperature control, Riser temperature versus
regenerated catalyst from the second regenerator.
2. Catalyst level control versus regenerated catalyst from
the first regenerator.
3. Pressure control for second and first regenerators,
manipulating exit flue gas.
4. Steam rate versus set point.
5. Level in the reactor versus spent catalyst from the
reactor to regenerator 1.
6. Temperature in the second regenerator versus hot air
flow rate to the second regenerator.
7. Temperature in the first regenerator versus hot air flow
rate to the first regenerator.
8. Local feedback control of the hot air to the first and
second regenerator versus desired value or set point.
9. Ratio control of fuel/air ratio.
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Journal of Applied and Industrial Sciences, 2014, 2 (2): 46-57, ISSN: 2328-4595 (PRINT), ISSN: 2328-4609 (ONLINE)
Figure2: Physical Diagram of the Base Case Control Strategy of RFCC
Figure 3: Physical Diagram of RFCCU Control Strategy
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Journal of Applied and Industrial Sciences, 2014, 2 (2): 46-57, ISSN: 2328-4595 (PRINT), ISSN: 2328-4609 (ONLINE)
Mathematical models were developed for loop 1 through loop 4 and parameters of the transfer functions were cited from the
literature [9, 10].
Transfer function identification:
Loop 1:
Figure 4: loop 1 block diagram with the identified transfer functions
The chr-eq = 1+OLTF = 0 :
)1......(..............................05.108.18252.50356.3344.8s sss
Loop 2:
Figure 5: loop2 block diagram
The chr-eq is:
.......(2)........................................0.........40.85.3s21.52s30.1s
Loop 3:
Figure 6: loop 3 block diagram
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Journal of Applied and Industrial Sciences, 2014, 2 (2): 46-57, ISSN: 2328-4595 (PRINT), ISSN: 2328-4609 (ONLINE)
The chr-eq is:
)3.(........................................02.97.924.2037.1044.1 ssss
Loop 4:
Figure 7: loop4 block diagram
The chr-eq is:
)4( ........................................012.37.924.2037.1044.1 ssss
Stability Analysis and Tuning:
Taking loop 1 as an example:
1- Routh –Hurwitz Technique:
The chr-equation is:
)5..(..............................019.42.428.53344.0 ssss
The ultimate gain Ku and ultimate period Pu were inserted in to Ziegler-Nicolas table and the adjustable parameters are determined
and tabulated in the following table.
ku=9.5, Pu=9.8s.
Table 1
Z.N adjustable parameters of loop1
The same is repeated for each loop and summarized as shown in the Table 2:
Type of controller kc (min)i
(min)
D
P 4.75 - -
PI 4.27 8.16 -
PID 0.57 4.9 1.22
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Journal of Applied and Industrial Sciences, 2014, 2 (2): 46-57, ISSN: 2328-4595 (PRINT), ISSN: 2328-4609 (ONLINE)
Table 2
Summary of the adjustable parameters of the four loops using Routh-Hurwitz method
Loop Number mode kc (min)i
(min)
D
1 P 4.75 - -
PI 4.27 8.16 -
PID 0.57 4.90 1.22
2 P 7.96 - -
PI 7.16 0.73 -
PID 9.55 0.44 0.10
3 P 4.1 - -
PI 0.48 5.51 -
PID 0.57 33.1 0.83
4 P 5.28 - -
PI 4.75 4.43 -
PID 6.33 26.6 0.67
2- Root locus method:
Establishing the OLTF from equations 1,2,3 and 4 , Root Locus
method was applied.
The OLTF of loop 1 is:
)6.........(........................................)15)(18(1)(0.2s
2OLTF
)16.0(
sss
kc
Applying MATLAB software for loop1:
Figure 8: root locus of loop 1
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Journal of Applied and Industrial Sciences, 2014, 2 (2): 46-57, ISSN: 2328-4595 (PRINT), ISSN: 2328-4609 (ONLINE)
The ultimate gain and ultimate period are:
Ku=1.91, Pu=9.99s.
Inserting the values of ku and Pu into Z-N, the adjustable parameters for loop 1 are:
Table 3
Z.N adjustable parameters of loop 1
Table 4
Summary of the adjustable parameters for loop 1,2,3 and 4 using Root-Locus method
Loop Number mode kc (min)i
(min)
D
1 P 0.96 - -
PI 0.86 8.33 -
PID 1.15 49.95 1.25
2 P 0.49 - -
PI 0.44 0.72 -
PID 0.59 4.3 0.11
3 P 1.06 - -
PI 0.96 5.42 -
PID 1.28 32.5 0.81
4 P 0.56 - -
PI 0.50 4.37 -
PID 0.67 26.2 0.66
3- Bode plot method
The OLTF of loop 1 is:
Applying MATLAB software for loop 1:
Type kc (min)i
(min)D
P 0.96 - -
PI 0.86 8.33 -
PID 1.15 49.95 1.25
)7..(..................................................)15)(18(1)(0.2s
2OLTF
)16.0(
sss
kc
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Journal of Applied and Industrial Sciences, 2014, 2 (2): 46-57, ISSN: 2328-4595 (PRINT), ISSN: 2328-4609 (ONLINE)
Figure 9: Bode diagram of loop 1
From bode plot: ku=9.71, Pu=9.68s.
Inserting the values of ku and Pu into Z-N, the adjustable parameters for loop 1 are:
Table 5
Z-N adjustable parameters of loop1
Type kc (min)i
(min)D
P 4.86 - -
PI 4.37 8.07 -
PID 5.83 48.4 1.21
The same was repeated for loops1, 2,3and 4: Table 6
Summary of the adjustable parameters for loop 1, 2, 3 and 4 using Bode method
Loop Number mode kc (min)i
(min)
D
1 P 4.86 - -
PI 4.37 8.07 -
PID 5.83 48.4 1.24
2 P 8.00 - -
PI 7.20 0.72 -
PID 9.60 4.30 0.11
3 P 4.15 - -
PI 3.74 5.42 -
PID 4.98 32.5 0.81
4 P 5.28 - -
PI 4.75 4.43 -
PID 6.33 26.60 0.67
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Journal of Applied and Industrial Sciences, 2014, 2 (2): 46-57, ISSN: 2328-4595 (PRINT), ISSN: 2328-4609 (ONLINE)
Offset investigation
The forcing input:
Applying the method above for loops 1, 2,3and 4 and taking unit step change in the input, the offset are determined and tabulated in
the following table:
Table 7
Offset investigation values of loops 1, 2, 3 and 4
Loop Number Method of tuning
1 Routh 0.1
Bode 0.09
R.locus 0.03
2 Routh 0.05
Bode 0.03
R.locus 0.29
3 Routh 0.10
Bode 0.11
R.locus 0.32
4 Routh 0.24
Bode 0.24
R.locus 0.60
The System Responses:
Using the highest gain from the four loops for each method and taking a step change in the input the following responses are
realized:
ss
idCt
1)(,1)(
idC
)11..(................................................................................1
)(
....(10)................................................................................1)(
(9)....................1......... valueidealid
C , (s)] y [s0s
lim C
:where
)8.......(............................................................id
C C,offset
ss
idC
tCid
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Journal of Applied and Industrial Sciences, 2014, 2 (2): 46-57, ISSN: 2328-4595 (PRINT), ISSN: 2328-4609 (ONLINE)
Figure 10: Response of loop 1
Figure 11: Response of loop 2
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Journal of Applied and Industrial Sciences, 2014, 2 (2): 46-57, ISSN: 2328-4595 (PRINT), ISSN: 2328-4609 (ONLINE)
Figure 12: Response of loop 3
Figure 13: Response of loop 4
III. RESULTS AND DISCUSSION
The control system in the Reference Case as shown in Fig. 2
needs to be renewed, better by adaptive controllers as these
types of controllers can adapt themselves according to the
change of catalyst activity, temperature and pressure. These
types of controllers are costly, hence a less expensive control
system is developed in this study to replace the existing control
system in application to date as in Fig. 3. It is observed that in
the existing control system depicted in figure 3, the level inside
the regenerator and the temperature in the riser are controlled
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Journal of Applied and Industrial Sciences, 2014, 2 (2): 46-57, ISSN: 2328-4595 (PRINT), ISSN: 2328-4609 (ONLINE)
by manipulating the regenerated catalyst flow rate by two slide
valves which are very interacting, at the same time the hot air
rate is not controlled.
The system depicted in Fig. 3 was developed in this study, the
transfer functions were identified and the overall transfer
functions were calculated the characteristic equations as well as
the closed loop and open loop transfer functions were
determined as seen in tables 1 through 7. Routh Hurwitz,
Root-Locus and Bode methods are used for stability analysis
and tuning. All the systems in all control loops are shown to be
stable. The tuning methods of Routh and bode give
asymptotically equal parameters but with regard to the gain
Root Locus does not in agreement with the two other methods
as shown in tables 3 and 4. The method that gives the highest
sensitivity is selected for simulation of the results, upon a step
change in the input, the results are shown in figures (10
thtough13). Summary of the adjustable parameters are
tabulated in tables (1, 2, 3 ...7), the system is recommended to
be transformed to digital control system.
IV. CONCLUSIONS
In conclusion the control system of the RFCC in the Reference
Case should be superseeded by either an adaptive control
system or by the system developed in study. It is concluded
that with the exception of root locus, the methods of stability
analysis and tuning are found to be identical and each of them
can confidently be used for tuning. The response of each loop
was stable, with minimum oscillation and very short recovery
time as seen in Figures 1 through 13.
Acknowledgement
The authors wish to thank the Graduate College for Higher
Studies and Research of Karary University for their help and
encouragement. This paper is generated from a research thesis
in partial fulfillment for Ph.D. in Chemical Engineering at the
University of Karary (Sudan).
REFERENCES [1]. Gary, J.H. and Handwerk, G.E.(1984). Petroleum Refining
Technology and Economics, Second Edition, Marcel Dekker, Inc.
[2]. Reza .S (2000).Fluid Catalytic Cracking Handbook, Second
Edition, Gulf
Publishing Company.
[3]. Peter .H (2003). Chemical Reactor Design, Marcel Dekker, Inc. -
New York Basel.
[4]. Bollas G. M., Lappas A.A and Vasalos I. A (2002). An
Integrated Riser-Reactor Dynamic Model for the Simulation of Pilot
and Commercial FCC units.
[5]. Baker.R, Swartz.C.L.E, Young. J.C, (2004). ‘framework Input’,
Computers & Chemical Engineering, Volume 28, Issue 8, Pages
1347- 1360.
[6]. ChenZiluan.W, Chen.X.M and Jiang Q.C (2003). ‘Optimal
Control of Fluid Catalytic Cracking Unit’, IFAC.
[7]. Raluka.R, Serban P.A, Zoltan K.N and Mircea.V.C 20 (2009).
dynamic modeling and nonlinear model predictive control of a Fluid
Catalytic Cracking Unit , Computers &Chemical
Engineering, Volume 33, Issue 3 , Pages 605-617.
[8]. Madhusudana.R Rao, Rengaswamy.R, A.K. Suresh& K.S.
Balaraman April (2004). ‘Industrial Experience with
Object-Oriented Modelling: FCC Case Study ’, Chemical Engineering
Research and Design, Volume 82, Issue 4, Pages 527-552.
[9]. Stephanopoulos.G (1984). Chemical Process Control: an
Introduction to Theory and Practice, Prentice-Hall India.
[10].Carlos. A. Smith (2006). ‘Principle and practice of automatic
control process’, John Wiely and Sons, ink, pages (157-325).