ISSN 0104-6632 Printed in Brazil www.abeq.org.br/bjche Vol. 33, No. 04, pp. 985 - 1002, October - December, 2016 dx.doi.org/10.1590/0104-6632.20160334s20150210 *To whom correspondence should be addressed Brazilian Journal of Chemical Engineering A NEW BENCHMARK FOR PLANTWIDE PROCESS CONTROL N. Klafke 1,2 , M. B. de Souza Jr. 2* and A. R. Secchi 3 1 Radix Engineering and Software Development. E-mail: [email protected]2 Chemical Engineering Department, Universidade Federal do Rio de Janeiro, (UFRJ), Rio de Janeiro - RJ, Brazil. * E-mail: [email protected], 3 Chemical Engineering Program, COPPE, Universidade Federal do Rio de Janeiro (UFRJ), Rio de Janeiro - RJ, Brazil. E-mail: [email protected](Submitted: April 6, 2015 ; Revised: October 9, 2015 ; Accepted: October 16, 2015) Abstract - The hydrodealkylation process of toluene (HDA) has been used as a case study in a large number of control studies. However, in terms of industrial application, this process has become obsolete and is nowadays superseded by new technologies capable of processing heavy aromatic compounds, which increase the added value of the raw materials, such as the process of transalkylation and disproportionation of toluene (TADP). TADP also presents more complex feed and product streams and challenging operational characteristics both in the reactor and separator sections than in HDA. This work is aimed at proposing the TADP process as a new benchmark for plantwide control studies in lieu of the HAD process. For this purpose, a nonlinear dynamic rigorous model for the TADP process was developed using Aspen Plus™ and Aspen Dynamics™ and industrial conditions. Plantwide control structures (oriented to control and to the process) were adapted and applied for the first time for this process. The results show that, even though both strategies are similar in terms of control performance, the optimization of economic factors must still be sought. Keywords: Plantwide control; Aromatic complex; TADP process; Dynamic simulation. INTRODUCTION The use of recycles and heat integration in the transformation processes is a consolidated solution to increase yields and to reduce operational costs. These factors tend to increase the process complex- ity, demanding a control perspective not limited to the analysis of the individual units. Many authors point out that the need for a plant- wide perspective on control arises mainly due to these changes in the way plants are designed. Indeed, these factors lead to more interactions and therefore the need for a perspective beyond individual units, as pointed out by Stephanopulos (1984) and earlier by Buckley (1964). Larsson & Skogestad (2000) clari- fied that the term plantwide control does not mean the tuning and analysis of the behavior of each con- trol loop, but rather the control philosophy of the overall plant with emphasis on structural decisions (Morari, 1982), such as selection of manipulated (“inputs”), controlled (“outputs”) and measured vari- ables (“extra-outputs”); design of control configura- tion (a structure interconnecting outputs, setpoints and manipulated variables) and selection of control- ler type. These decisions are all taken during the basic design conception, unfortunately before the complex control studies that in general are not per- formed by process engineers. Myers (1997) defined the aromatic complex as a combination of process units that can be used to
Transcript
ISSN 0104-6632 Printed in Brazil
www.abeq.org.br/bjche
Vol. 33, No. 04, pp. 985 - 1002, October - December, 2016 dx.doi.org/10.1590/0104-6632.20160334s20150210
*To whom correspondence should be addressed
Brazilian Journal of Chemical Engineering
A NEW BENCHMARK FOR PLANTWIDE PROCESS CONTROL
N. Klafke1,2, M. B. de Souza Jr.2* and A. R. Secchi3
1Radix Engineering and Software Development.
E-mail: [email protected] 2Chemical Engineering Department, Universidade Federal do
Rio de Janeiro, (UFRJ), Rio de Janeiro - RJ, Brazil. *E-mail: [email protected],
3Chemical Engineering Program, COPPE, Universidade Federal do Rio de Janeiro (UFRJ), Rio de Janeiro - RJ, Brazil.
(Submitted: April 6, 2015 ; Revised: October 9, 2015 ; Accepted: October 16, 2015)
Abstract - The hydrodealkylation process of toluene (HDA) has been used as a case study in a large number of control studies. However, in terms of industrial application, this process has become obsolete and is nowadays superseded by new technologies capable of processing heavy aromatic compounds, which increase the added value of the raw materials, such as the process of transalkylation and disproportionation of toluene (TADP). TADP also presents more complex feed and product streams and challenging operational characteristics both in the reactor and separator sections than in HDA. This work is aimed at proposing the TADP process as a new benchmark for plantwide control studies in lieu of the HAD process. For this purpose, a nonlinear dynamic rigorous model for the TADP process was developed using Aspen Plus™ and Aspen Dynamics™ and industrial conditions. Plantwide control structures (oriented to control and to the process) were adapted and applied for the first time for this process. The results show that, even though both strategies are similar in terms of control performance, the optimization of economic factors must still be sought. Keywords: Plantwide control; Aromatic complex; TADP process; Dynamic simulation.
INTRODUCTION
The use of recycles and heat integration in the transformation processes is a consolidated solution to increase yields and to reduce operational costs. These factors tend to increase the process complex-ity, demanding a control perspective not limited to the analysis of the individual units.
Many authors point out that the need for a plant-wide perspective on control arises mainly due to these changes in the way plants are designed. Indeed, these factors lead to more interactions and therefore the need for a perspective beyond individual units, as pointed out by Stephanopulos (1984) and earlier by Buckley (1964). Larsson & Skogestad (2000) clari-
fied that the term plantwide control does not mean the tuning and analysis of the behavior of each con-trol loop, but rather the control philosophy of the overall plant with emphasis on structural decisions (Morari, 1982), such as selection of manipulated (“inputs”), controlled (“outputs”) and measured vari-ables (“extra-outputs”); design of control configura-tion (a structure interconnecting outputs, setpoints and manipulated variables) and selection of control-ler type. These decisions are all taken during the basic design conception, unfortunately before the complex control studies that in general are not per-formed by process engineers.
Myers (1997) defined the aromatic complex as a combination of process units that can be used to
986 N. Klafke, M. B. de Souza Jr. and A. R. Secchi
Brazilian Journal of Chemical Engineering
convert petroleum naphtha and pyrolysis gasoline (pygas) into the basic petrochemical intermediates: benzene, toluene, and xylenes know as BTX.
Benzene, toluene and xylenes are produced through the catalytic reforming of naphta, but the thermodynamic proportion obtained in this process (32:36:32) is different from the market demand (55:11:34). Toluene has the lower demand and sev-eral processes are used to convert toluene and to produce, preferentially, benzene and xylenes (Serra et al., 2004).
This work focuses on the plantwide control of an aromatic complex, more precisely the Transalkyla-tion and Disproportionation Unit (TADP), whose function is the increase of xylenes and benzene pro-duction in the aromatic complex from surplus tolu-ene. This process is considered to be a technological improvement of the HDA process because, besides benzene, the TADP process also produces xylenes and generates fewer by-products with low commer-cial value.
For this purpose, a nonlinear dynamic rigorous model for the TADP process was developed using Aspen Plus™ and Aspen Dynamics™ and techniques previously employed in the HDA process were in-vestigated and compared in order to create an effec-tive control structure for the TADP process. To the knowledge of the authors, this is the first study of plantwide control applied to the TADP process.
PLANTWIDE CONTROL
According to Qiu et al. (2003), a major problem in controlling a plant is to develop effective control structures for the entire complex. For Larsson & Skogestad (2000), the design of a control structure is difficult to define mathematically, especially because of the size and cost involved for the precise formula-tion of the problem. This is the mathematically-ori-ented approach (or design of the control structure), i.e, the systematic approach for solving the plantwide control problem. An alternative is the development of heuristics based on experience and understanding of the process and is referred to as the process-ori-ented approach (Luyben, 2002; Luyben et al., 1998).
The implementation of the methodology from Luyben et al. (1998), using the process-oriented ap-proach, is composed of nine steps: i. establish control objectives; ii. determine the control degrees of free-dom; iii. establish energy inventory control; iv. set production rate; v. define product quality and safety control; vi. define inventory control; vii. check com-ponent balances; viii. control unit operations indi-
vidually and ix. use remaining control degrees of freedom to optimize economics or improve dynamic controllability.
Morari (1982) stated that "in search of a control structure considered optimizing, the main objective is to incorporate the economic objectives to the pro-cess control objectives”. In other words, "the goal is to find a function c(u,d) of process variables, that, when held constant, leads the manipulated variables automatically to their optimal working values, and with it, to the optimal operating conditions [... ]." This means that, keeping c(u,d) in their reference values cs, through the manipulated variables u, and under several disturbances d, the process is operating at its optimal steady-state.
Larsson & Skogestad (2000) introduced the con-cept of a "self-optimizing" control system, which consists of determining the best set of controlled variables in a manner that results in an economic performance of the overall process closest to the optimal value of the economic objective function. They evaluated the effects of a loss function (depar-ture from optimum) in the implementation of the reference value of the controlled variable.
The authors presented a design procedure based on a mathematically-oriented approach, but with some elements of the process-oriented approach. The procedure starts with a top-down analysis to select the controlled variables, based on ideas of self-opti-mization. At this stage, a rigorous steady-state model is needed and the operational objectives (economic steady-states) have to be defined. The result consists of one or more alternative sets of controlled variables.
This top-down analysis is followed by a bottom-up analysis, starting with the regulatory control layer. After this stage, the setpoints of the regulatory layer and some unused manipulated variables are the re-maining degrees of freedom, which can be used to control the primary controlled variables. This control layer is called the supervisory layer. Two main ap-proaches are possible for this layer: single-loops (de-centralized) controllers with feedforward connec-tions, or multivariable control. According to the au-thors, appropriately designed multivariable control-lers will have better performance, but this must be negotiated against the cost of obtaining and main-taining the models used in the controllers. In the sequence, an optimization layer is applied with the purpose to identify active constraints and compute optimal set-points cs for the controlled variables. Finally, nonlinear dynamic simulations should be performed to validate the proposed control structure.
As pointed out by Qiu et al. (2003), the HDA pro-cess has all the characteristics for plantwide control
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A New Benchmark for Plantwide Process Control 989
Brazilian Journal of Chemical Engineering Vol. 33, No. 04, pp. 985 - 1002, October - December, 2016
Table 2: Equipment dimensions and specifications.
Reactor Length 8 m Diameter 5.3 m
FEHE (Feed Effluent Heat Exchanger) UA 2823.5 kJ/(s°C) Separator Length 10 m
Diameter 3 m Steady-State Analysis for Plantwide Control Degrees of Freedom Analysis
The number of steady-state degrees of freedom determines the number of steady-state controlled variables that can be chosen. In complex processes, it is useful to sum the number of degrees of freedom of the individual units, as given in Table 3. From these rules, the degrees of freedom are calculated according to Table 4. This analysis can be verified by a balance of the 22 manipulated variables considered in this
process (see Table 5). However, 7 of the original de-grees of freedom are flowrates used to stabilize liquid levels with no steady-state effect. Thus, there are 22−7 = 15 degrees of freedom, as shown in Table 4.
For this process 49 variables were considered as controlled variables. This selection is presented in Table 6. With 15 degrees of freedom and 49 candi-dates for controlled variables, an analysis of all pos-sible structures is impractical. To avoid this combi-natorial explosion, the active constraints are first de-termined and then an optimization analysis can be applied to define the remaining set.
Table 3: Typical number of steady-state degrees of freedom for process units, based on Araújo et al. (2007b).
Process Unit Degrees of Freedom Each external feed stream 1 (feedrate) Splitter n-1 split fractions (n is the number of exit streams) Mixer 0 Compressor, turbine, and pump 1 (work) Adiabatic flash tank 0* Liquid phase reactor 1 (holdup) Gas phase reactor 0* Heat Exchanger 1 (duty or net area) Columns (e.g. distillation) excluding heat exchangers 0* + number of side streams
*Add 1 degree of freedom if pressure is set (need an extra valve, compressor, or pump).
Table 4: Number of steady-state degrees of freedom analysis.
Process Unit Degrees of Freedom External feed streams 4 × 1 = 4 Splitters (purge) 1 × 1 = 1 Compressor(*) 1 × 0 = 0 Adiabatic flash(**) (separator) 1 × 0 = 0 Gas phase reactor (**) 1 × 0 = 0 Heat exchangers in recycle section (***) (furnace and cooler) 2 × 1 = 2 Heat exchangers in three distillation columns 3 × 2 = 6 Three distillation columns, two of it with one sidestream each 0 + 2 × 1 = 2 Total 15
* Considering fixed power in the compressor. ** Assuming no adjustable valves for pressure control (fully open valve ahead of the separator). *** The FEHE duty is not a degree of freedom because there is no adjustable bypass.
990 N. Klafke, M. B. de Souza Jr. and A. R. Secchi
Table 6: Selected candidate controlled variables for the HDA process (excluding levels).
Y1 A9/A10 flow rate Y26 Separator liquid outlet toluene mol fraction Y2 Fresh toluene flow rate Y27 Separator liquid outlet xylene mol fraction Y3 Recycle flow rate of toluene Y28 Gas recycle ethane mol fraction Y4 Reactor inlet temperature Y29 Gas recycle propane mol fraction Y5 Reactor outlet temperature Y30 Gas recycle benzene mol fraction Y6 Separator temperature Y31 Total flow rate of hydrocarbons to the reaction section Y7 Bentol feed flow rate Y32 Hydrogen mol fraction in the reactor outlet Y8 Fresh gas feed flow rate Y33 Production rate (flow rate in benzene and stabilizer columns) Y9 FEHE hot side exit Y34 Production rate (flow rate in the toluene column) Y10 Steam flow rate at the separator outlet Y35 Temperature in an intermediate stage of stabilizer column Y11 Liquid flow rate at the separator outlet Y36 Temperature in an intermediate stage of benzene column Y12 Purge flow rate Y37 Temperature in an intermediate stage of toluene column Y13 Separator pressure Y38 Pressure at the top of stabilizer column Y14 Furnace heat duty Y39 Pressure at the top of benzene column Y15 Cooler heat duty Y40 Pressure at the top of toluene column Y16 Toluene conversion at reactor outlet Y41 Benzene mol fraction in stabilizer column sidestream Y17 Trimethylbenzene conversion at reactor outlet Y42 Propane mol fraction in stabilizer column sidestream Y18 Hydrogen / hydrocarbons ratio in the reactor inlet Y43 Benzene mol fraction in benzene column sidestream Y19 Recycle gas flow rate Y44 Benzene mol fraction in benzene column sidestream Y20 Mixer ethane mol fraction Y45 Xylene mol fraction in toluene column bottoms Y21 Mixer propane mol fraction Y46 Toluene mol fraction in toluene column bottoms Y22 Separator overhead vapor ethane mol fraction Y47 Ethylbenzene mol fraction in toluene column bottoms Y23 Separator overhead vapor propane mol fraction Y48 Toluene mol fraction in toluene column overhead Y24 Separator overhead vapor benzene mol fraction Y49 Xylene mol fraction in benzene column overhead Y25 Separator liquid outlet benzene mol fraction
A New Benchmark for Plantwide Process Control 991
Brazilian Journal of Chemical Engineering Vol. 33, No. 04, pp. 985 - 1002, October - December, 2016
Primary Controlled Variables
In this case study there are three valuable prod-ucts of the distillation columns: the composition of benzene in the sidestreams of the stabilizer and ben-zene columns and the composition of xylene in the bottom of the toluene column. As these are the main products of the unit, their specification in these streams must be considered as active constraints.
The composition of toluene in the recycle stream to the unit is also a pre-defined variable, since an increased content of xylenes in the recycle stream demands higher energy consumption, and may also cause an undesired concentration of ethylbenzene in the process. Thus, this composition is also consid-ered to be an active constraint. Just as considered for xylene, it is not interesting to recirculate back the benzene to the reaction section; therefore, in the bottom of the benzene column, benzene composition must be controlled. The bottom stream of the stabi-lizer column will be manipulated in order to control the concentration of benzene in the bottom. These six specifications for the distillation columns con-sume six steady state degrees of freedom, thus leav-ing 15 − 6 = 9 remaining degrees of freedom.
The following constraints were considered active for the reaction and separation sections: separator temperature, A9/A10 feed flow rate, fresh toluene flow rate, Bentol flow rate, separator pressure, H2/HC ratio and reactor inlet temperature. These constraints are not degrees of freedom since their values should be set. Consequently, the remaining number of de-grees of freedom is: 15 − 6 − 7 = 2, which signifi-cantly reduces the number of possible sets of con-trolled variables. Optimization Analysis for Selection of Remaining Degrees of Freedom
The equation that describes the profit function (J) [M$/year] to be maximized is described as:
9 10 9 10
2 2
( ) (
)
B B X X f f Tol Tol
A A A A Bentol Bentol
H H fuel fuel CW CW
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Reactor inlet hydrogen/hydrocarbon ratio
21 3HHC
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Feed flow rates (fresh toluene, bentol and stream A9/A10)
1984 kg / hTolF = (3)
9 10 67595 kg / hA AF = (4)
126443 kg / hBentolF = (5) Reactor temperature
697 KreactorT = (6) Benzene purity in the sidestream of stabilizer and benzene columns
, 97.00%B estabx ≥ (7)
, 99.99%B benzenex ≥ (8) Xylene purity in the bottom of the toluene column
68.00%Xx ≥ (9) Toluene purity in the recycle stream
98.00%Tolx ≥ (10) Separator inlet temperature
_ 500 Kin sepT = (11) Separator pressure
224.3 PaseparadorP = (12)
All flow rates and concentrations are non-nega-tive variables.
It is considered that all by-products (purge, distil-late vapor of stabilizer and benzene column) are sold as fuel. Additionally:
1. pB, pX, pf, pTol, pBentol, pA9A10, pH2, pfuel, pCW, pPow and pVap are the prices of feed of benzene, xylene, fuel gas, toluene, bentol, A9/A10 fraction, hydrogen, fuel for the furnace, cooling water, power to the compressor, and steam, respectively (see data in Table 7);
2. FB, FX, Ff, FTol, FBentol, FA9A10 and FH2 are the flow rates of benzene, xylene, fuel gas, toluene, ben-tol (mixture of benzene and toluene), A9/A10 fraction, and hydrogen, respectively, Qfuel, QCW and QVap are heat duties of fuel for the furnace, cooling water, and
992 N. Klafke, M. B. de Souza Jr. and A. R. Secchi
Brazilian Journal of Chemical Engineering
steam, respectively, and WPow is the power to the compressor;
The constant setpoint strategy is simple, but will
not be optimal, as a result of disturbances. The effect of these factors (or, more specifically the loss) de-pends on the choice of the controlled variables, and the goal is to find a set of controlled variables in which the loss is acceptable. In order to identify the structure that satisfies that condition, an analysis of the model was carried out using the resources of op-timization of Aspen Plus™. The objective function described in Equation (1) was set up with its con-straints. Concentration variables with no active con-
straints were pre-selected, because they have a significant impact on the objective function. The optimal value of these variables was calculated and two disturbances were applied to the process (D1 and D2, +10% and -10% A9/A10 feed flow rate, re-spectively). The decision variables were the concen-trations (mol fractions) from Table 6.
Variables defined as optimal from the standpoint of self-optimizing control were those with less de-viation from their optimal value, which implies that the constant setpoint policy has the least impact on the profit function. Table 8 presents the results. It should be noted that the present approach is simpler than that performed by Araújo et al. (2007b) who calculated the loss with each variable in the assumed sets kept at its nominal optimal setpoint.
From the described methodology, the selected variables should have been: (i) the separator liquid outlet toluene mol fraction and (ii) the mol fraction of xylene in the reactor outlet. However, as the TDAP process includes a disturbance of toluene ahead of the separator, due to a fresh stream in the feed of the benzene column, it was decided to change the first selected variable by another one. Therefore, comparing with the results obtained by Araújo et al. (2007b) for the HDA process, who considered the set composed of mol fraction of methane (inert) in the outlet of the mixer and mol fraction of toluene in the outlet of the quencher, the mol fraction of ethane (inert) at the mixer outlet was considered. With these changes the methodology cannot be considered rig-orously self-optimizing. The impacts of this choice are evaluated in the following sections.
Table 8: Effect of disturbances on optimal values of the selected variables.
Candidate Controlled Variable Nominal Value Absolute Variation of Nominal Value
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olled by manr. The exceptow of benzented variable, e level of the
emperature C
Since the opct both in re
October - Decem
Strategy O
ure proposedn this presentDP process. Ture were de
following iUp” analysis.
Regulatory
objective of mooth oper
ed by the upally it is a dea set of outp
lly these varperatures.
of Unstable M
tion section order to stabiy Araújo et ainlet temperaof the heat dfect on the temlevels in thesump drum ostabilized. H
utput flow raeption is theer column wt duty due to
ic behavior oe control of to stabilize ture must be cycle loop. Asel pressure iled, rather thin Araújo etariable remadistillation c
nipulating thetion is the stane in the side
since the hee condenser.
Control
peration of tecycle gas se
mber, 2016
Oriented to
d by Araújo t work from The items in
efined duringitems are the
Control Str
the regulatoration, followpper layers ecentralized ctput variableriables are p
Modes
one temperilize the reacal. (2007b), ature of the
duty of the femperature. e separator aof the distillHere it was ates to controe level of thwhich is conto the absenc
of pressure ithe pressure the gas/vapocontrolled ats in the TADis an active han the presst al. (2007b)ains the flowcolumn, pree heat duty oabilizer coluestream is useat duty is u
the separatoreparation and
9
the Contr
et al. (2007the HDA pr
n the first stagg the analyse second pa
ructure
ory layer is wing the seof the contrcontrol systes at given seressure, leve
rature must bctor operatioit was chosereactor by th
furnace, whic
and the reflulation columnchosen to mol these varie reflux dru
ntrolled by thce of distilla
is usually fain the proce
or inventoriet some point DP process, th
constraint ansure in the r); however th
w rate of purgessure is coof the conde
umn, where thsed as manipused to contr
r has great imd in the dist
993
rol
7b) ro-ge sis
art,
to et-rol em et-els
be on. en he ch
ux ns
ma-ia-um he ate
st, ess es. in he nd re-he ge
on-en-he
pu-rol
m-il-
994 N. Klafke, M. B. de Souza Jr. and A. R. Secchi
Brazilian Journal of Chemical Engineering
late section, its temperature should be controlled. The manipulated variable chosen in this case is the heat duty of the condenser.
The composition control of distillation columns in general is slow due to liquid and gas transport delays as well as large liquid holdup along the col-umn, and the measurement is time consuming and more expensive than temperature control. Therefore, the temperatures are also controlled in the distillation columns in order to avoid fluctuations on a short time scale. The Slope Criterion method (Luyben, 2006) was used. The procedure for selecting the control tray in this method consists of analyzing the temperature profile at the steady state and finding the location in the column that exhibits the largest change in temperature from one stage to another. It was applied and the selected tray for temperature control of T-02 was number 4; number 36 for T-03, and number 46 for control of T-04. Design of Supervisory Control Structure
The purpose of the supervisory layer is to keep the primary controlled variables in their optimal setpoints. The supervisory layer was adapted from
Araújo et al. (2007b). In addition to the previously established composition controllers, an anticipatory control to calculate the ratio H2/HC is also needed, since this is an active constraint. In the steady-state analysis, the control of the composition of xylene at the outlet of the reactor (by manipulating the setpoint of reactor inlet temperature controller) and the con-trol of ethane in the mixer output by manipulating the flow of recycle gas were defined. Table 9 sum-marizes all the control loops defined in Strategy 1. The supervisory control structure − composed of the primary xylene composition controller (R-01_CC cascaded with the temperature controller R-01_TC); the ethane composition controller V-01_CC, and the feedforward controller − is shown in Figure 4 that presents the control structure for this strategy. Tuning of the Controllers
Only P (proportional) control was adopted for liq-uid levels; for other control loops, PIs (proportional-integral) controllers were employed. The conserva-tive Tyréus-Luyben (Luyben et al., 1998, 1997) tun-ing rules (Kc = Ku/2.2; τI = 2.2 Pu; Ku and Pu are re-spectively the critical gain and period) were used.
Table 9: Summary of the control loops of Strategy 1.
In the metecycles shouall" effect. Ionsidered nease the prodtreams of staottom of theure is used fo
Steps 1 anegrees of fre
Step 3: The controlled b
Step 4: Throduction rat
Step 5: Thmainly by twThe separatioizer column erature cont
The separatioene column he boilup of ure of the moontrol of thehe top comphe temperatuoluene colum
Brazilian J
Strategy Or
thodology ould be fixed iIn addition, cecessary onlducts were abilizers ande toluene colfor obtaining nd 2: Controeedom as mahe inlet tempeby manipulat
he feed flow te is fixed; he quality owo componeon of propan
helps to pretroller to set on of benzen
is easy. As the column
ost sensitive e desired proosition is us
ure controllermn is also co
A
Journal of Chemi
Fi
riented to th
f Luyben et in order to avcompositiony for sale prconsidered td benzene column. The nthe control sl objectives de previouslerature of theting the fuel A9/A10 tha
of benzene cents: propan
ne and benzeevent this bt the boilup ne and toluea result, onby controllintray. To achduct, an on-l
sed to adjust r. The bottomonsidered a
A New Benchmar
ical Engineering
igure 4: Con
he Process
al. (1998), void the "sno
controllers roducts. In tto be the siolumns andnine-step prostructure. and analysisy; e reactor shoin the furnac
at determine
can be affecne and toluene in the stay using a teof the colum
ene in the bne can establng the tempeieve the qualine analyzerthe setpoint
m stream of saleable stre
rk for Plantwide P
Vol. 33, No. 04,
ntrol structure
the ow-are this ide-the
oce-
s of
ould ce; the
cted ene. abi-em-mn.
ben-lish era-ality r of t of the
eam
becarreatiotoptheergxy
fixthrstatheumate20macolatratthesepbe arepuindrec
the
Process Control
pp. 985 - 1002,
e of Strategy
cause it conrries all the acted in the pon control isp, which shoe bottom of gy consumpt
ylene; Step 6: The
xed and fourree distillatioabilizer colume manipulate
mn pressure, e good resu11), so the fanipulated vlumns, pressting the flowte of condene yield of thparator shalloperated at
e two optionurge flow ordicates the cycle loop, th
Seven liquie separator l
October - Decem
y 1.
ntains xyleneheavy com
process, the to prevent
ould be recythe column,tion in the s
e toluene recr pressures mon columns amn, the flow
ed variable thbut this con
ults in termflow rate of
variable. In sure control rate of cooli
sation at the he reactor, thl be opened maximum re
ns to control r the fresh inventory o
he flow of freid levels are evel and two
mber, 2016
e product. Amponents gen
main purposthat the tolu
ycled to the , causing an sections of p
cycle flow rmust be conand in the gaw rate of vaphat directly anfiguration dms of separaf the sidestre
the benzenecan be don
ling water fo top. In ordehe valve in and the com
ecycle gas. Tthe gas preshydrogen. Oof hydrogen
resh hydrogene presented i
wo levels (ref
9
As this streanerated or nse of composuene from thprocess, exiincreased e
purification
rate should bntrolled: in thas loop. In thpor product affects the cooes not geneation (Klafk
eam is used e and toluenne by manipr adjusting th
er to maximithe top of thmpressor sha
Therefore, thessure loop: thOnce pressun in the gn is chosen. n the procesflux and sum
995
am not si-he its
en-of
be he he is
ol-er-ke, as ne
pu-he ze he all ere he
ure gas ss: mp
99
dtrindfldbthtr
toinreraddththdchinlian
locacom
96
rums) in eacrol the level onto the stabirum of the low rate of crum by the enzene columhe level of trolled by the
Unlike theoluene column the bottom ecycle of toluate was chorum, which istillate in thhe reflux druhe toluene reesired. Therhosen to conventory of imits large fnd ensures th
Step 7: Eoop to prevean be controomponents (
moved by the
ch column. Tof the separailizer columstabilizer co
cooling watewithdrawal
mn, the flowthe reflux dbottom flow
e other colummn is high so
of the columuene. Theref
osen to conthas greater
he toluene cum level, theecycle streamrefore the floontrol this le
toluene in flow variatiohe componen
Ethane is punt its accumolled by the (A8
+) generae bottom stre
The most direator is with th
mn. The leveolumn is coner and the levl of bottom
w rate of sidedrum and thew rate. mns, the boio that the comn is small cfore, the rebotrol the leve
effect. If thcolumn was en the flow rm would varow rate of fevel since it
the processons in the rnt balance forged from t
mulation and flow of pur
ated or not eam of the t
Fi
N. Klafke, M
Brazilian Jou
ect way to che flow of fl
el of the refntrolled by vel of the sustream. In
estream contre sump is c
ilup rate of ontent of xylecompared to oiler steam flel in the suhe flow rateused to contrate of liquidry, which is fresh toluenet represents s. This scherefining sector toluene; the recycle its compositrge. The heareacted are oluene colum
igure 5: Con
M. B. de Souza Jr.
urnal of Chemica
on-luid flux the
ump the
rols on-
the ene the
low ump e of trol d in not e is the
eme tion
gas tion avy re-
mn,
whdrutemtheprevenconpuov
vidingsep
lishof of umreqproco
blepar1 pvarstrin
ntrol structure
and A. R. Secchi
al Engineering
here the steaum. The benmperature ane benzene cessure contrntory of toluntrol of the r
urge flow andver the invent
Step 8: At tdual units cag water is dparator tempStep 9: Th
hed. In this sthe controllthe plant. T
mns should quirements ooducts as comes from theThe final st
e 10 presentsring Tables 9presents fourriables are c
reams of the the distillat
e of Strategy
i
m flow contzene invento
nd level contcolumn and ols in the s
uene is accoureflux drum id pressure cotory of hydrohis point then be establisefined as merature contr
he basic regstep there is flers to optimThe flow ratbe determin
of the columnntaminants. e steady-statetructure can bs the implem9 and 10, it r more contrconcentrationstabilizer ante of the to
y 2.
trols the leveory is accountrols of the rvia the tem
stabilizer colunted for thrin the toluenontrol of theogen; e control loopshed, the flow
manipulated vrol.
gulatory stratfreedom to s
mize cost andtes of refluxned based ons and the poThe selectio
roposed for thane concenhe flow rate nd the purgtrategy 1 alsctor output xb), that justifeactor tempe
The stabiliisturbances aers of benzenies. Strategyolumn, whicer. Figure 8 sional constridestream, Ehe second str
The control eflux flow rainear behaviorevent conta
with propanewith constant
avior for ttream flow r
Results fo
7: Reaction n of ethane c
w rate (V-01_CC.PV) withy 1; (c) – varnipulation of ashed lines).
r the reactiontration is pof recycle ge flow rate so presents oxylene concfies the diffe
erature (Figurizer column and these arene and toluey 1 presents ch is the botshows that inraint of benEquation (7),
rategy preseof the benzate in Strateor, as it somamination we. Additionat setpoint didthe disturbarate. or the benzen
section supeconcentration_CC.OP) forh the manipriation of eth
f purge flow .
on section. Tperformed bas in Strategin Strategy
one more coentration con
erence in the re 6b and d).absorbs the
e minimized ene columns one more cottoms compon both stratenzene compwas not sati
ented a lowerzene composegy 1 presen
metimes mustith toluene aally, the vad not guaranance in the
ne and toluen
N. Klafke, M
Brazilian Jou
ervisory conn in the mixer strategy 1.
pulation of thane concenrate (V-01_C
The control y manipulat
gy 1 (Figure 2 (Figure 7
ntroller, the ntroller (Figbehavior of
. impacts of by the contrfor both stra
ontroller in tosition contregies the opeposition in isfied, althour loss of pursition with
nts a more nt act in orderand other timariables chontee optimal
A9/A10 fe
ne columns
M. B. de Souza Jr.
urnal of Chemica
ntrol under der outlet (V-0 (b) – variatthe setpoint
ntration in thCC. OP) for
of ting 7a) 7c). re-
gure the
the rol-ate-this rol-era-the
ugh rity. the
non-r to mes sen be-
feed
are
nouman Str
thestrzencociaturmu
benmoflothinothaendoChStrres
and A. R. Secchi
al Engineering
disturbance o01_CC. PV) tion of xylen
of reactor he overhead o
strategy 2. C
ot shown hermns and bothce are effecti
rategy 3 – M
Strategy 1 e constraint oream of T-02ne product implex, increally light garbance in theum purity is
The componzene columol fraction, ow rate of diis configurat
ote that this soat this columsures that va
o not significahanges in corategy 1 aresulting in the
i
of 10% in A9
with the manne concentrat
temperatureof separator Controlled/m
re due to spah strategies, tively absorbe
Modification
presented diof the benzen. Although th
intended for easing the coses, correspe adjacent coan importantsition contro
mn, more spis accomplisistillate vapoion is kept colution is on
mn is a highariations in tantly alter thontrol structue shown in e Strategy 3.
9/A10 flow raanipulation otion in react
e (R-01_CC.(V-01_CC.P
manipulated v
ace reasons. the impacts ed (Klafke, 2
n in the Stra
difficulties tone compositithis is not a s
sale outsideontent of im
ponds to a sonsumer unitt constraint. ol of the sidepecifically oshed by maor. The refluconstant. It inly plausible h reflux ratithe flow of dhe flows insidure of T-02
Figure 9 a
ate. (a) – f recycle or outlet .OP) for PV) with variables
For both coof the distur2011).
tegy 1
o comply wiion in the sidstream of bee the aromat
mpurities, espignificant dit, so the min estream of thf the propan
anipulating thux flow rate is important due to the fao type, whic
distillate vapde the columin relation
and Table 1
ol-rb-
ith de-en-tic
pe-is-ni-
he ne he in to
act ch
por mn.
to 11,
Figure
Tag T02_CondPCT02_DrumLCT02_CC03 T02_TC T02_CC02 T02_SumpLC
T-02 pressT-02 refluT-02 side T-02 tempT-02 bottoT-02 reboi
Process Control
pp. 985 - 1002,
ance of 10%
egy 1 control
ol loops of S
Controlled vsure
ux drum level stream propane
perature controlom benzene coniler level
October - Decem
in A9/A10 fee
l structure of
Strategy 3.
variable
e concentration tray
ncentration
mber, 2016
ed stream flo
f T-02.
Kc (%44.
0.26.
0.
9
ow rate.
%/%) τI (min)19 85.82 -
42 11.8821 19.811 112 -
999
)
10
thcoTwsiM S
Ftu
dcerapmap(benotoTcou
tharth
000
The resulthe proposed onstraint in t
The change inwas also effince the pro
MM$/year ag
Strategy 3
Figure 10: Siurbance of 10
The HDA evelopment essing heavyaw materialsroducts. Alth
mercial namel. (1993). Thlantwide cobased on Aranted approacriginally defo develop co
This process omplex and nits have bee
The initialhat, in terms re similar. Hhe heavy aro
ts presented regulatory c
the benzene n Strategy 1 fective throufit J obtaine
gainst 2.3 MM
idestream co0% in A9/A10
CONCL
process hasof a new t
y aromatic cos, and produhough this pes, here it is his work wantrol - the aújo et al. (2ch (based o
fined for the ontrol structu unit was effects of t
en discussedl results obtof control p
However, whomatic feed
in Figure 1control is efcompositionwhich gener
ugh the ecoed with StraM$/year for S
omposition in0 flow rate fo
LUSIONS
s become obechnology components, aucing fewer
process has acalled TAD
s based on tcontrol stru
2007b)) and tn Luyben eHDA procesures for the inserted int
the interactiod. tained in thisperformance,hen a disturba
was applied
N. Klafke, M
Brazilian Jou
10 indicate tffective and n was complirated Strategonomic aspetegy 3 was Strategy 2.
n T-02 with dor strategy 3.
bsolete with capable of padding value
unwanted bassociated co
DP, as in Dastwo methodsucture approathe process-o
et al. (1998)ss and used hTADP proce
to an aromaon between
s work show both strategance of 10%d, the modif
M. B. de Souza Jr.
urnal of Chemica
that the
ied. gy 3 ects 2.8
dis-.
the pro-e to by-
om-s et s of ach ori-)) – here ess. atic the
wed gies
% in fied
Strthiforchconcoobconof
wibe iestecingit conMoor top
An
An
An
Cn
Cn
Cn
cudcsJKc
τI
Ar
Ar
and A. R. Secchi
al Engineering
rategy 1 didis disturbancr constant nanges in the ntrol were cmposition co
btained. So, ntrol implemthe profit ofThe TADP
ide point of vused as a ne
s, replacing chnologicallyg. Its complea promisingntrol strategodel Predicti
Distributedphides et al.,
n Aromn carb
n+ Cut cowith ncomp
n- Cut cowith ncomp
n Hydroatoms
n+ Cut con carb
n- Cut con carbContrManipDisturContrObjecPropoIntegr
raújo, A., Skplication ofI - steady-scontrol. Co1237 (2007
raújo, A., Sk
i
d not guarance and for thnominal setconfiguratio
arried out anontrol and ecit is conside
mentations aif the TADP u
process, apview for the ew challengethe conventiy more up-toexity and ecog scenario wies may be ive Control (d Model Pr
2013).
NOMENC
matic hydrocabonsomposed of an carbon atomonent omposed of an carbon atomonent ocarbon coms omposed of hbon atoms ofomposed of hbon atoms ofrolled variablpulated variarbance variabrolled variablctive functionortional gain ral time cons
REFERE
kogestad, S. f plantwide cstate optimizontrol Enginea).
kogestad, S.
ntee optimalhe set of vart-point. Becon of the stabnd better resuconomic perfered that futiming at the
unit must be spproached frfirst time in
e for problemional HDA po-date and monomical imp
where more rtested, such
(EMPC) (Ellredictive Co
CLATURE
arbon compo
aromatic hydms of the lig
aromatic hydms of the hea
mpound with
hydrocarbonf the lighter chydrocarbonf the heavier le able ble le reference vn
stant
RENCES
and Govatsmcontrol to thezation and seering Pract
and Hori, E
l behavior friables chose
cause of thabilizer columult in terms formance weture plantwide improvemesought. rom the planthis work, ca
m-control stuprocess, bein
more challenportance makrecent proce
h as Economis et al., 201ontrol (Chri
ound with
drocarbons hter
drocarbons avier
n carbon
ns with component ns with component
value
mark, M., Ae HDA Proceself-optimizinice, 15, 122
E. S., Applic
for en at,
mn of
ere de
ent
nt-an
ud-ng
ng-ke
ess mic
4) is-
Ap-ess ng
22-
ca-
A New Benchmark for Plantwide Process Control 1001
Brazilian Journal of Chemical Engineering Vol. 33, No. 04, pp. 985 - 1002, October - December, 2016
tion of plantwide control to the HDA Process II - regulatory control. Industrial and. Engineering Chemistry Research, 46, 5159-5174 (2007b).
Buckley, P. S., Techniques of Process Control. John Wiley & Sons, Inc., New York (1964).
Christofides, P. D., Scattolini, R., de la Peña, D. M. and Liu, J., Distributed model predictive control: A tutorial review and future research directions. Computers and Chemical Engineering, 51, 21-41 (2013).
Das, J., Bath, Y. S. and Halgeri, A. B., Transalkyla-tion and Disproportionation of Toluene and C9 Aromatics Over Zeolite Beta. Indian Petrochemi-cals Corporations Limited (1993).
Ellis, M., Durand, H., Christofides, P. D., A tutorial review of economic model predictive control methods. Journal of Process Control, 24, 1156-1178 (2014).
Jeanneret, J. J., Rekoske, J. E., Lentz, R. A. and Shete, R., Managing alkyl groups in an aromatic com-plex. 13th Saudi-Japanese Symposium on Cata-lysts in Petroleum Refining and Petrochemicals, Saudi Arabia (2003).
Klafke, N., Application of Plantwide Control Fun-damentals to the Transalkylayion and Despropor-tionation of Toluene (TADP) Process. M.Sc. Dissertation, School of Chemistry, UFRJ (2011).
Larsson, T. and Skogestad, S., Plantwide control - a review and a new design procedure. Modeling, Identification and Control, 21(4), 209-240 (2000).
Luyben, W. L., Plantwide Dynamic Simulators in Chemical Processing and Control. Marcel Dekker
Inc., New York (2002). Luyben, W. L., Tyreus, B. D. and Luyben, M. L.,
Plantwide Process Control. McGraw-Hill, USA (1998).
Luyben, M. L., Tyreus, B. D. and Luyben, W. L., Plantwide control design procedure. AIChE Jour-nal, 43(12), 3161-3174 (1997).
Luyben, W. L., Distillation Design and Control Us-ing Aspentm Simulation. John Wiley & Sons Inc., New Jersey (2006).
Morari, M., Integrated plant control: A solution at hand or a research topic for the next decade? Chemical Process Control-II, United Engineering Trustees, 467-495 (1982).
Myers, R. A., Handbook of Petroleum Refining Pro-cesses. 2nd Ed., McGraw-Hill, USA (1997).
Ouguan, X., Hongye, U., Jianbing, J., Xiaoming, J. and Jian, C., Kinetic model and simulation analy-sis for toluene disproportionation and C9-aromat-ics transalkylation. Chinese Jornal of Chemical Engineering, 15(3), 326-332 (2007).
Qiu, Q. F., Rangaiah, G. P. and Krishnaswamy, P. R., Application of a plant-wide control design to the HDA process. Computers and Chemical Engi-neering, 27, 73-94 (2003).
Serra, J. M., Guillon, E. and Corma, A., A rational design of alkyl-aromatics dealkylation–transal-kylation catalysts using C8 and C9 alkyl-aromat-ics as reactants. Journal of Catalysis, 227, 459-469 (2004).
Stephanopoulos, G., Chemical Process Control. Pren-tice-Hall, Inc., New Jersey (1984).
APPENDIX Kinetics of Reactions of the TADP Process
The kinetic model (Ouguan et al., 2007) is pre-sented below. In this model, r is the reaction rate, a is the mass fraction (%), φ is the function of catalyst deactivation which is assumed as uniform for all reactions and equal to 1 in this work, k is the kinetic constant of reaction and K is the chemical equi-librium constant. The components involved are: tolu-ene (Tol), benzene (B), xylenes (X), methylbenzene (MB), ethylbenzene (EB), propilbenzene (PB), tri-methylbenzene (TMB), and C10A.
Disproportionation of Toluene (Reversible)
21 1
1
.. B xTol
a ar k aK
φ ⎛ ⎞= −⎜ ⎟
⎝ ⎠ (A1)
1002 N. Klafke, M. B. de Souza Jr. and A. R. Secchi
Brazilian Journal of Chemical Engineering
2 22
2 .. B EBTol
a ar k aK
φ ⎛ ⎞= −⎜ ⎟
⎝ ⎠ (A2)
Transalkylation of Toluene with Trimethylbenzene (Reversible)
3 33
... X XTol TMB
a ar k a aK
φ ⎛ ⎞= −⎜ ⎟
⎝ ⎠ (A3)
4 44
. .. EB EBTol TMB
a ar k a aK
φ ⎛ ⎞= −⎜ ⎟
⎝ ⎠ (A4)
Dealkylation (Irreversible)
5 5. . MEBr k aφ= (A5)
66 . . PBr k aφ= (A6) Disproportionation of Trimethylbenzene (Rever-sible)
1027
77
.. X C A
TMBa a
r k aK
φ⎛ ⎞
= −⎜ ⎟⎝ ⎠
(A7)
The kinetic constant of the ith reaction is defined
by the Arrhenius equation:
0 .exp , ( 1 7)aii i
Ek k iRT
⎛ ⎞= − = −⎜ ⎟⎝ ⎠
(A8)
The chemical equilibrium constants are calculated
as follows, for reactions 1 to 4 and 7, where Mc is the molecular weight of the component C. The ther-modynamic constant Kepi is given by Equation (A14).
1 1 2.. B X
epTol
M MK KM
= (A9)
2 2 2.. B EB
eTol
pM MK K
M= (A10)
2
3 3..
X
l Mep
To T B
MK KM M
= (A11)
2
4 4 .. EB
Tole
TMBp
MK KM M
= (A12)
102 2
7 7 2
..e
X C A
Bp
TM
M MK K
M= (A13)
exp , ( 1 4,7)iepi
GKRT
i⎛ ⎞− = −⎜ ⎟⎝ ⎠
Δ= (A14)
The kinetic parameters are presented in Table A1.
Table A1: Kinetics parameters of the model, based on Ouguan et al. (2007).
Direct reaction Reverse reaction Reaction k0i, s-1 Eai,
kJ mol-1 k0i/K, s-1 (Eai)inv =
Eai - ΔG, kJ mol-1
1 9.106 x 1010 102 3.269 x 1011 94.8 2 9.534 x 1013 150 1.567 x 1015 134.1 3 5.712 x 1010 96.77 1.273 x 1011 92.07 4 6.001 x 1013 150 2.804 x 1015 127.8 5 6.126 x 1010 101.8 - - 6 3.263 x 1010 95.8 - - 7 3.213 x 109 106 1.338 x 1011 84.7
