Simultaneous hydrogen and aromatics enhancement by obtaining optimum temperature profile and...

i n t e rn a t i o n a l j o u r n a l o f h y d r o g e n en e r g y 3 6 ( 2 0 1 1 ) 8 3 1 6e8 3 2 6

Avai lab le at www.sc iencedi rect .com

journa l homepage : www.e lsev ie r . com/ loca te /he

Simultaneous hydrogen and aromatics enhancement byobtaining optimum temperature profile and hydrogenremoval in naphtha reforming process; a novel theoreticalstudy

D. Iranshahi, A.M. Bahmanpour, K. Paymooni, M.R. Rahimpour*, A. Shariati

Department of Chemical Engineering, School of Chemical and Petroleum Engineering, Shiraz University, Shiraz 71345, Iran

a r t i c l e i n f o

Article history:

Received 25 January 2011

Received in revised form

23 March 2011

Accepted 4 April 2011

Available online 5 May 2011

Keywords:

Naphtha reforming

Optimization

Hydrogen permeation

Aromatics enhancement

Differential evolution method

* Corresponding author. Tel.: þ98 711 230307E-mail address: rahimpor@shirazu.ac.ir (

0360-3199/$ e see front matter Copyright ªdoi:10.1016/j.ijhydene.2011.04.023

a b s t r a c t

In this novel theoretical study, the dimensionless length of the conventional naphtha

reforming reactor has been discretized into differential segments and three different cases

have been investigated in this regard. In the first case, inlet temperature of each segment

has been optimized via differential evolution (DE) method to obtain the optimized

temperature profile along the reactors by joining the achieved inlet temperatures for each

segment on the figure. Same approach has been applied in the second case in order to

achieve optimum hydrogen permeation rate. In the third case, the optimum profiles of

temperature and hydrogen removal have been obtained using DE optimization technique

using the same approach. The objective of each optimization case is to maximize the

hydrogen and aromatics production rate. As it is discussed further, unlike previous studies,

application of optimum temperature and hydrogen permeation profiles simultaneously

boosts hydrogen and aromatics production rate significantly. 10% and 24% enhancement in

hydrogen and aromatics production rates can be achieved by applying the novel theoretical

concepts in the conventional naphtha reforming process.

Copyright ª 2011, Hydrogen Energy Publications, LLC. Published by Elsevier Ltd. All rights

reserved.

1. Introduction enhance their quality. BTX production is another usage of

1.1. Naphtha reforming

Catalytic naphtha reforming is a process throughwhich one of

the main fractions of crude oil typically having low-octane

ratings called “Naphtha” is transformed into high-octane

liquid reformates [1]. Lighter ends (C1eC5) are produced in

this process, as well. High-octane reformates are usually

blended with low-octane gasoline produced in other units to

1; fax: þ98 711 6287294.M.R. Rahimpour).2011, Hydrogen Energy P

naphtha reforming units.

Considering the importance of boosting the octane number

of gasoline fuel and, consequently, the quality of produced

reformates in this process, several research efforts have been

made to investigate the catalytic naphtha reforming process.

The related studies can be classified into two separate cate-

gories. Some researchers have investigated and modeled the

kinetics of the process; Smith [2] has simplified the sophisti-

cated mechanism of this process by presenting a simple but

i n t e r n a t i o n a l j o u r n a l o f h y d r o g e n en e r g y 3 6 ( 2 0 1 1 ) 8 3 1 6e8 3 2 6 8317

accurate kinetic model containing four dominant reactions

which present the governing reactions of themodel. Paraffins,

Naphthenes and Aromatics have been introduced as the

fundamental groups to be discussed in this model. Smith’s

model shows acceptable agreement with the experimental

data despite its simplicity. A more complex model has been

presented by Juarez and Macias [3] in which isomers of the

main groups in previous model have been considered in the

system. Less than 3% average deviation from experimental

data shows the accuracy of this model. A semi-empirical

kinetic model has been investigated by Stijepovic et al. [4] to

simulate the kinetics of catalytic naphtha reforming process.

Presence of Paraffins, Olefins, Naphthenes and Aromatics has

been considered in the system and their reactions have been

analyzed in the model. Similar studies in this field have been

done by other researchers [5e8]. The other category contains

the modifications which have been suggested by researchers

to improve the efficiency of the process. A semi-regenerative

naphtha reformer has been modeled and its operating

conditions have been optimized by Li et al. [9]. Economic and

environmental aspects have been considered in an objective

function defined by Stijepovic et al. [10] in a new simulation

and optimization for conventional naphtha reforming reac-

tors. Weifenget al. [11] have suggested a multi objective opti-

mization process to enhance aromatics production rate.

Khosravanipour and Rahimpour [12] have investigated the

dynamic behavior of a membrane reactor configuration for

naphtha reforming process by using Smith’s kinetic model.

Iranshahiet al. [13e15] have discussed the advantages of using

optimized spherical reactor configuration and also thermally

coupled recuperative reactor in order to improve the hydrogen

and aromatics production rate in naphtha reforming process.

Application of axial flow-spherical reactor and also combi-

nation of membrane tubular reactors and spherical reactors

are among the modifications which have been suggested and

discussed in previous studies [16,17]. Furthermore, various

modifications have been suggested to improve the efficiency

of the process [18e20].

Naphtha feed

Recycled

Fig. 1 e Schematic diagram of a conven

1.2. Hydrogen

Efficient, high performance and low cost technologies for

producinghydrogenareurgentlyneededtoencouragehydrogen

utilization in the future. Hydrogen can be produced by several

processes, including the steam reforming of methane and

naphtha reformers [21]. Refineries consume hydrogen in big

amounts for removing sulfur and nitrogen compounds and

producing lighter fuels. During the past decade, crude oil has

been getting heavier and contains more sulfur and nitrogen,

while the clean fuel specifications are progressively tightened

along with the legislation for environmental protection.

Consequently,moreandmorehydrotreatingandhydrocracking

processes are constructed, and hydrogen is now becoming

a critical issue to the world’s refiners [22e24]. Consequently,

studies should be directed to applying a membrane technology

in naphtha reactors to enhance hydrogen production rate in

refineries to solve these urgent needs.

1.3. Optimization method

Utilizing modern optimization techniques such as simulated

annealing (SA) [25], evolution strategies (ESs) [26], genetic

algorithms (GAs) [27,28] and differential evolution method

(DE) [29] have handled the issues raised previouslywhile using

traditional optimization methods. The modified differential

evolution (MDE) algorithm utilizes only one set of population

as against two sets in original DE at any given point of time in

a generation. Such an improvement reduces the memory and

computational efforts [30]. The DE algorithm can be applied to

find the minimum total annualized cost of the non-

equilibrium reactive distillation for the synthesis of ethylene

glycol, which is a MINLP optimization problem [31]. Chen et al.

[32] proposed a MDE algorithm to improve the searching effi-

ciency of simple differential evolution algorithm (DE). The

computational results of the batch plant design problem

obtained highlight the clear superiority of DE since its best

found solutions always lie very close to the Branch-and-

Hydrogen rich make

Off gas

Reformate

Catalysts

tional naphtha reforming reactor.

Table 1 e Specifications of reactors, feed, product andcatalyst of CR.

Parameter NumericalValue

Naphtha feedstock 30.41 � 103 Kgh�1

Reformate 24.66 � 103 Kgh�1

H2/HC mole ratio 4.74 e

LHSV 1.25 h�1

Mole percent of

hydrogen in recycle

69.5 e

Diameter and length

of 1st reactor

1.25, 6.29 m

Diameter and length

of 2nd reactor

1.67, 7.13 m

Diameter and length

of 3rd reactor

1.98, 7.89 m

Distillation fraction

of naphtha feed

and reformate

TBP Naphtha

feed (�C)Reformate

(�C)IBP 106 44

10% 113 73

30% 119 105

50% 125 123

70% 133 136

90% 144 153

FBP 173 181

Typical properties

of catalyst

dp 1.2 mm

Pt 0.3 wt%

Re 0.3 wt%

sa 220 m2g�1

rB 0.3 Kgl�1

3 0.36 e

Bound optima [33]. Angira and Santosh [34] discussed about

the application and evaluation of a modified version of Trig-

onometric Differential Evolution (TDE) algorithm. Application

of optimum operating conditions in the mentioned studies

has enhanced the production rate of the desired products,

Furnace

Naphtha R

Feed Stream

Catalysts

Twenty Optimized

Segments

Fig. 2 e Schematic diagram o

significantly. The main advantage of the present research

compared with previous studies is the application of the

optimum temperature profile and hydrogen removal along the

reactors. As it can be noticed from previous works, inlet

conditions of the reactors have been chosen to be the main

decision variables of the optimization process.

1.4. Objectives

In the present study, the length of naphtha reforming reactor

has been discretized into twenty segments. Regarding this,

differential evolution (DE) method has been used to obtain the

optimized temperature profile and hydrogen removal by

obtaining the inlet optimum values for each segment and

joining them on the figures along the reactor. Three cases

have been discussed; in the first case, only the temperature

profile has been optimized. In the second case, the amount of

hydrogen removal has been optimized along the reactor. And

the final case is a combination of optimized temperature

profile and hydrogen removal along the reactor. The effect

of operating under optimized temperature and hydrogen

removal conditions on the reactor performance is investigated

in the following sections and compared with the performance

of conventional tubular reactor (CTR). The optimization

results demonstrate that the third case excels both hydrogen

and aromatics production rates as discussed further.

2. Model description

2.1. Conventional naphtha reforming process (CTR)

The conventional catalytic naphtha reforming process has

been discussed in our previous studies, completely [13e17].

However, a brief summary of the process has beenmentioned

in this section. A simple schematic diagram of the conven-

tional process has been presented in Fig. 1. The catalytic

naphtha reforming reactions are carried out over commercial

Pt/Re/Al2O3 (0.3% Platinum, 0.3% Rhenium) catalyst. Endo-

thermic naphtha reforming process occurs in three adiabatic

eforming Reactors

Removed

Hydrogen

Product Stream

f the optimized reactors.

reactors. Three inter stage heaters have been applied to avoid

the reduction of the temperature and consequently, naph-

thene dehydrogenation reaction rate. The feed stream has

been combined with a recycle stream which contains

hydrogen in order to control the molar H2/HC ratio and coke

formation. Maintenance of H2/HC molar ratio in a specified

range may control the coke formation in the system. Table 1

presents the catalyst specifications and operating conditions

of the conventional process.

2.2. Novel optimized model

In the new configuration, the optimum temperature and

hydrogen removal profiles are determined along the reactors

and the effect of these optimized values on themain products

yield and the conversion of reactants are investigated. As

discussed before, the decision variables of the optimization

procedures applied in the previous studies were the inlet

conditions of the reactors. The superiority of the presented

model to the previous one is the optimization of the temper-

ature profile and amount of hydrogen removal along the

reactors which significantly affect the hydrogen and

aromatics production rate. Fig. 2 shows the scheme of the

procedure. Three cases are considered during the optimiza-

tion process of this specific problem. In this regard, the reactor

length is divided into twenty segments and material and

energy balances are evaluated considering optimized values

of the hydrogen removal and the temperature profile. In the

first case, the inlet temperature of each segment has been

optimized in a way to achieve the optimized temperature

profile by a combination of the obtained optimized inlet

temperature of the sections. Same procedure has been applied

in the second case for the amount of hydrogen removal along

the reactor and the third case is a combination of previous

cases. A scheme of the segment in Fig. 2 illustrates that the

mass and energy balances can be developed based on this

element by considering hydrogen removal.

3. Reaction kinetics

3.1. Naphtha reforming process

In order to simplify the calculation procedure, the suggested

model by Smith [2] has been used in this research. Although

themodel is simple, the results obtained from thismodel have

Table 2 e Comparison between model prediction and plant da

Reactor No. Inlet temperature (K) Inlet pressure (KPa)

1 777 3703

2 777 3537

3 775 3401

Reactor No. Outlet temperature (K)

Plant CR Deviation%

1 722 727 0.7%

2 753 751 0.3%

3 770 771 0.1%

acceptable agreement with industrial data which will be dis-

cussed in the model validation section. According to the

Smith’s model, four dominant reactions are investigated in

the naphtha reforming process as the main governing reac-

tions of this system, the reactions and the rate equations are

as follows:

1. Dehydrogenation of naphthenes to aromatics.

Naphthenes ðCnH2nÞ4Aromatics ðCnH2n�6Þ þ 3H2

DH1 ¼ 71 kJ=mole

r1 ¼�kf1

��Ke1pn � parp

�(1)

2. Dehydrocyclization of naphthenes to paraffins.

Naphthenes ðCnH2nÞ þH24Paraffins ðCnH2nþ2ÞDH2 ¼ �36:9 kJ=mole

r2 ¼�kf2

��Ke2pnph � pp

�(2)

3. Hydrocracking of naphthenes to lower hydrocarbons.

Naphthenes ðCnH2nÞ þ n=3H24Lighter ends ðC1 � C5ÞDH3 ¼ �51:9 kJ=mole

r3 ¼�kf3

�pn (3)

4. Hydrocracking of paraffins to lower hydrocarbons.

Paraffins ðCnH2nþ2Þ þ ðn� 3Þ=3H24Lighter ends ðC1 � C5ÞDH4 ¼ �56:6 kJ=mole

r4 ¼�kf4

�pp (4)

In the mentioned rate equations, kf and Ke are forward rate

constants and equilibrium constants, respectively. Rase [35]

has investigated these constants and the following equa-

tions have been derived:

ta for fresh catalyst [27].

Catalyst distribution (wt%) Input feedstock (Mole%)

20 Paraffin 49.3

30 Naphthene 36

50 Aromatic 14.7

Aromatic in reformate (Mole%)

Plant CR Deviation%

57.7 56.2 2.7%

Table 3 e Comparison between predicted production rateand plant data [27].

Time(day)

Naphthafeed (ton/h)

Plant(kmolh�1)

Model(kmolh�1)

0 30.41 225.90 221.5802 �1.91

34 30.41 224.25 222.5122 �0.77

62 31.00 229.65 227.9313 �0.75

97 30.78 229.65 226.7749 �1.25

125 31.22 229.65 230.7985 þ0.50

160 31.22 229.65 231.2730 þ0.71

188 28.55 211.60 209.8377 �0.83

223 30.33 222.75 224.7291 þ0.88

243 31.22 233.05 232.1821 �0.37

298 30.67 228.65 228.1752 �0.21

321 30.76 227.64 229.0932 þ0.64

398 42.35 317.30 324.5555 þ2.28

425 42.32 317.94 324.4826 þ2.05

461 42.32 317.94 324.6987 þ2.12

490 42.32 317.94 324.8622 þ2.17

524 42.32 313.09 325.0433 þ3.81

567 42.54 317.94 327.0586 þ2.86

610 42.54 313.90 327.2581 þ4.25

717 37.86 286.15 289.3742 þ1.12

771 38.51 282.10 294.9026 þ4.53

kf1 ¼ 9:87 exp

�23:21� E1

�(5)

kf2 ¼ 9:87 exp

�35:98� E2

�(6)

kf3 ¼ kf4 ¼ exp

�42:97� E3

�(7)

ke1 ¼ 1:04� 10�3 exp

�46:15� 46;045

�(8)

ke2 ¼ 9:87 exp

��7:12þ 8000

�(9)

In the above equations, E is the activation energy and T is the

absolute temperature in K. The activation energies have been

optimized in order to minimize the difference between calcu-

lated and observed values of aromatic production yield and

outlet temperature. The optimized values are presented here:

E1 ¼ 36:3 kJ=mol

E2 ¼ 58:5 kJ=mol

E3 ¼ 63:8 kJ=mol

4. Mathematical modeling

4.1. Conventional model

The conventional catalytic naphtha reforming reactors have

beenmathematically modeled in order to simulate the results

of the industrial reactors. The validity of this model has been

checked by comparison of the obtained results and the

experimental data which is discussed further. Smith’s kinetic

model has been used in this research. Despite its simplicity,

the accuracy of this model is acceptable as it can be seen in

model validation section. A one-dimensional model has been

utilized considering the following assumptions:

� Steady state conditions have been investigated in this

research.

� Axial dispersion is assumed to be negligible.

� Plug flow pattern is considered in each side of the reactor.

� Heat loss is neglected.

As it can be seen in model validation section, the applica-

tion of these assumptions may not affect the accuracy of the

model. However, it can clearly simplify the calculation

procedure. By application of the discussed model, the

following mass and energy balance equations can be

achieved:

Dejv2Cj

vx2�v

�uCj

þrBaXmi¼1

vijri¼0 j¼1;2;.;ni¼1;2;.;m (10)

keffv2Tvx2

�ruCp

�T� Tref

��þ rBaXmi¼1

DHiri ¼ 0 (11)

In order to solve these equations, the following boundary

conditions have been applied:

x ¼ 0� > Cj ¼ Cj0; T ¼ T0 (12)

x ¼ L� >vCj

vx¼ 0;

¼ 0 (13)

5. Optimization

As previously mentioned, this novel theoretical model has

been presented to maximize the aromatics and hydrogen

production rate. Therefore, the objective function in this

optimization procedure is defined as follows:

Sum ¼ YoutH2

=YinH2

þ Youtaromatic=Y

inaromatic (14)

where Yout and Yin are the mole fractions in the outlet of the

third reactor and the inlet of the first reactor, respectively.

Three cases have been investigated in this research: in the

first case, the temperature profile has been optimized; while in

the second case, the amount of hydrogen removal along the

reactor can be optimized. The third case is a combination of

the first and second cases. Deactivation of the catalysts

mainly occurs due to two phenomena in this process: Sin-

tering and Coke formation. The temperature of the system

should be controlled to avoid sintering phenomenon. When

reducing the partial pressure of hydrogen however, the cata-

lyst can be fouled and the operation cycle shortened. The

effect of the hydrogen pressure reduction can be compensated

with a lower temperature in the first reactor, thus decreasing

the rate of formation of coke precursors. It has also been

considered that the H2/HC molar ratio has a minimum

acceptable value; this could compensate for the activity

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1

Mass of catalyst (Dimensionless)

0 0.02 0.04 0.06 0.08 0.1 0.12 0.14 0.16 0.18 0.2

Case 1

Case 3

0.2 0.25 0.3 0.35 0.4 0.45 0.50

Case 1

Case 3

0.5 0.55 0.6 0.65 0.7 0.75 0.8 0.85 0.9 0.95

Case 1

Case 3

Fig. 3 e Temperature profile of (a) the conventional reactor (b) first reactor (c) second reactor and (d) third case.

decline. Coke formation can be controlled by adjustment of

molar H2/HC ratio. In the temperature profile in the naphtha

reforming process should not exceed 550 �C or 823 K as

mentioned in literature [36,37]. However, to obtain more

acceptable answers, the upper limit of the temperature profile

has been set at 800 K. It may jeopardize the catalyst activity if

the H2/HC molar ratio reaches a value less than 4.73 [12].

Therefore, the following constraints have been applied in the

optimization procedure:

� 4:73 (15)

Ti � 800 K (16)

Penalty function has been applied in the optimization

procedure to eliminate the unacceptable answers automati-

cally. By using a penalty parameter, the defined constraints

are inserted in the procedure. Therefore, the objective func-

tion defined in this optimization problem is as follows:

Results ¼ �Sumþ 105X6

G2i (17)

G1 ¼ max�0;�4:73� ðH2=HCÞ1

�(18)

G2 ¼ max�0;�4:73� ðH2=HCÞ2

�(19)

G3 ¼ max�0;�4:73� ðH2=HCÞ3

�(20)

G4 ¼ maxf0; ðT1 � 800Þg (21)

G5 ¼ maxf0; ðT2 � 800Þg (22)

G6 ¼ maxf0; ðT3 � 800Þg (23)

By application of Differential Evolution (DE) method, the

objective function has been minimized and, therefore, the

terms which represent the hydrogen and aromatics produc-

tion rate has been maximized.

6. Results and discussion

6.1. Model validation

The conventional model has been validated considering

observed plant data for conventional packed bed reactor at

0 0.02 0.04 0.06 0.08 0.1 0.12 0.14 0.16 0.18 0.2

mass of catalyst (Dimensionless)

oval (km

Case 2

Case 3

0.2 0.25 0.3 0.35 0.4 0.45

oval (km

Case 2

Case 3

0.5 0.55 0.6 0.65 0.7 0.75 0.8 0.85 0.9 0.95 1

oval (km

Case 2

Case 3

Fig. 4 e Hydrogen removal profiles for (a) first reactor (b) second reactor and (c) third case.

steady state conditions. Table 2 presents the plant data and

predicted mole fractions of the components in the output of

the process. Model results show acceptable agreement with

the plant data. By utilizing the PONA Test in Stan Hop Seta

apparatus, each component (Paraffins, Naphthenes and

Aromatics) has been analyzed. The aromatic is tested espe-

cially by ASTM 2159 equivalent to UOP 273 method.

Steady state conditions have been considered in the

present research. However, by application of a catalyst deac-

tivation model [38], this conventional model has been also

validated by comparison of the theoretical and experimental

data for 800 operating days. This comparison has been pre-

sented in Table 3.

6.2. Discussion

As previously discussed, three cases have been studied in this

research; for each case, the reactors have been divided into 20

different segments. For each segment, the inlet temperature

has been optimized in the first case and the combination of

the optimized inlet temperatures provides us with an opti-

mized temperature profile along the reactors. The same

approach has been used in the second case. However, the

amount of hydrogen removal has been investigated in this

case. The third case is a combination of these two cases.

Fig. 3(a)e(d) presents the temperature profiles of the

system. In Fig. 3(a), the temperature profile of CTR has been

presented for comparison. Since naphtha reforming reactions

are predominantly endothermic, the reaction side tempera-

ture decreases abruptly along the reactors. In the first reactor,

the inlet concentration of naphthenes and n-paraffins is high,

therefore the reactions take place well and the temperature

drops abruptly. However, the reaction rate decreases at the

end of the first reactor owing to a decrease in the reaction side

temperature. Consequently, the outlet stream from the first

reactor is preheated via furnace before entering the second

reactor (see Fig. 1). In the second reactor, the same abrupt

temperature drop as the first reactor is not observed because

the most concentration of the naphtha feed is consumed in

the first reactor which lessens the reaction rates in the second

reactor. Ultimately, the lowest temperature drop is observed

in the third reactor owing to the least concentration of the

naphtha feed and the proceeding of the reactions along the

reactor. Optimized temperature profiles of cases 1 and 3 have

been shown in Fig. 3(b)e(d) for three reactors. As it can be seen

in the first case, the temperature profile of the first reactor is

lower compared with the conventional reactor. The temper-

ature profile increases in the second reactor and it reaches its

maximum limit in the third reactor. The objective of this

optimization procedure is to maximize the hydrogen and

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1

Case 1

Case 2

Case 3

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1

Case 1

Case 2

Case 3

Fig. 5 e (a) Aromatics and (b) hydrogen production for each case.

aromatics production yield. As it can be seen in the “Reaction

Kinetics” section, aromatics and hydrogen are mainly

produced via the first endothermic reaction. Higher temper-

ature profile may increase the production yield of these

materials. However, as it can be noticed from the optimization

procedure that, by using lower temperature profile in first

reactor, the production load may be shifted to the second and

third reactors. By using this strategy, fuel depletion in the

second and third reactors, whichmay have higher production

potential due to their operating conditions, can be avoided. In

this way, the amount of produced hydrogen and aromatics in

the first reactor may not be satisfactory, but it may boost the

final production yield.

To justify the optimized temperature profile obtained in

the third case, one should consider the hydrogen removal

along the reactors which have been shown in Fig. 4(a)e(c) for

the second and third cases. Owing to the in situ hydrogen

removal from the reaction side in the third case, a certain

amount of heat is removed which leads to a temperature

reduction. Therefore, the optimized inlet temperature of the

first reactor should be higher compared with the first case.

First, the hydrogen removal increases through the first reactor

slightlywhich leads to temperature reduction as it can be seen

in Fig. 3(b). As the hydrogen removal profile reaches its

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1

Case 1

Case 2

Case 3

Fig. 6 e (a) Paraffins and (b) naphth

maximum in the first reactor, the temperature profile

increases with reducing hydrogen removal.

Hydrogen and aromatics are mainly produced in the

second and third reactors. Therefore, hydrogen removal and

temperature should be increased in order to maximize the

rate of the first reaction. In order to compensate the heat

removal which occurs as a consequence of hydrogen removal,

the heaters should provide enough heat to increase the

temperature profile of the system along the second reactor.

Consequently, both hydrogen removal and temperature

profile increase along the second reactor to maximize the

reaction rate as it can be seen in Fig. 3(c) and Fig. 4(b). A slight

reduction in the temperature profile at the end of the second

reactor is mainly due to shifting a part of the production load

to the third reactor.

In order to investigate the temperature profile and

hydrogen removal in the third reactor, the reactor length has

been hypothetically divided into three zones; in the first zone,

the approach of the second reactor continues and both

hydrogen removal and temperature profile increase to maxi-

mize the reaction rate and, consequently, production yields.

In the second zone, fuel depletion plays the main role in

reduction of the reaction rate and temperature profile. The

rate of hydrogen removal decreases in this zone, as well. The

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1

Case 1

Case 2

Case 3

enes conversion for each case.

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1

Case 1

Case 2

Case 3N

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1

Case 1

Case 2

Case 3

Fig. 7 e (a) Naphthene dehydrogenation rate and (b) H2/HC molar ratio for each case.

Table 4 e Underneath area of the reaction rate for eachcase.

Cases FirstReactor

SecondReactor

ThirdReactor

Summation

CR 52.34 29.81 12.24 94.41

Case 1 40.15 50.56 26.62 117.34

Case 2 53.18 30.47 13.31 96.97

Case 3 40.77 58.64 21.77 121.19

profile of hydrogen removal reaches its maximum. In order to

control the H2/HC molar ratio, the hydrogen removal

decreases. Consequently, the heat transfer due to hydrogen

removal decreases and thismay justify the slight temperature

increase of the system at the end of the third reactor (third

zone) in the third case.

The temperature profile of the second case has not been

optimized. Therefore, it will be approximately the same as the

conventional reactor. In thefirst reactor, the temperatureprofile

of the system in the second case is significantly higher than the

third case. This leads to higher reaction rate and, consequently,

higher hydrogen production. The concentration of hydrogen

increases in the system. Accordingly, more hydrogen may be

removed from the system without a significant reduction in

H2/HC molar ratio. Therefore, higher hydrogen removal profile

can be seen in the second case in Fig. 4(a).

At the entrance of the second reactor, the temperature

profile of the second case is higher than the third case. This

justifies higher hydrogen removal profile of the second case

according to the previously discussed reason. A low temper-

ature profile of the second case in the second reactor leads to

a low reaction rate and hydrogen production. Therefore, as it

can be noticed from Fig. 4(b), the hydrogen removal should

decrease in order to keep the H2/HC molar ratio in the

acceptable range.

At the entrance of the third reactor, the temperature profile

and the reaction rate of the second case is slightly higher

compared with the end parts of the second reactor. This may

allow the hydrogen removal profile to increase a little.

However, as the reaction rate decreases, the hydrogen

removal profile reduces.

The legislative requirements for sulfur removal from

gasoline and diesel have increased hydrogen use in the

refineries; hence, refiners are looking for ways to maximize

their hydrogen yields [1].On the other hand, the increasing

demand for high-octane gasoline motivates refineries to

devise some new technologies and fundamental changes in

their available complex. Fig. 5(a) and (b) show aromatics and

hydrogen production for all discussed cases in this research.

As it can be seen, highest aromatics and hydrogen production

can be achieved by application of the third case where both

hydrogen removal and temperature profile have been

optimized. Therefore, applying some hydrogen removal

techniques such as membrane technology can shift the ther-

modynamic equilibrium of the first reaction (naphthene

dehydrogenation) to the products side and consequently,

paraffins may convert to naphthenes through the reverse

dehydrocyclization reaction in accordance with the Le Cha-

telier’s principle and enhance the aromatic and hydrogen

yields. As it can be noticed from these figures, in cases 1 and 3

the hydrogen and aromatics production in the first reactor are

significantly lower than the ones in the conventional reactor

due to lower temperature profile and, consequently, reaction

rate. High temperature and reaction rate of the second reactor

in the first and third cases boost the production rate. Finally,

the achieved results show 24 and 10% increase in aromatics

and hydrogen production, respectively.

Conversion of paraffins and naphthenes can be seen in

Fig. 6(a) and (b). Higher conversion of these reactants results in

higher production rate of the desired products. Clearly,

utilizing the optimized reactor configurations (especially

cases 1 and 3) excels the conversion of the reactants in this

process. Consequently, higher aromatic and hydrogen yield

are anticipated in optimized configurations compared with

CTR (see Fig. 5).

Fig. 7(a) and (b) illustrate the rate of the first reaction, as

well as the H2/HC molar ratio. According to the first reaction,

a great deal of hydrogen can be produced. Obviously, lower

reaction rate of the conventional reactor compared with

optimized cases justifies higher production rate in the sug-

gested reactor configurations. The area under the curves

implies the proceeding percentage of the reactions. The

underneath area of the reaction rates for each case has been

presented in Table 4. The first reaction proceedswell along the

first reactor and it is the predominant reaction in the first

reactor. The H2/HC ratio has been shown for each case in

Fig. 7(b). In the conventional process and also in the first case

of optimization, the produced hydrogen remains in the

system. The H2/HCmolar ratio increases along the CTR owing

to continuous hydrogen production; therefore, it increases as

the reactions proceed. However, this ratio decreases accord-

ing to the hydrogen removal in cases 2 and 3. It is worth

mentioning that this ratio must be in an acceptable range to

prevent coke formation on the surface of the catalysts. The

recycled hydrogen can adjust the H2/HC molar ratio through

the reactors to prevent polymerization and coke formation

which can increase the risk of catalyst deactivation.

7. Conclusion

In this novel theoretical study, the temperature profile and the

amount of hydrogen removal from the systemwere optimized

through three different cases. In the first case, each reactor

length was divided into twenty different segments. For each

segments, the optimized inlet temperature was calculated in

order to boost the final hydrogen and aromatics production.

Combination of these values leads to the optimum tempera-

ture profile of the system. Same approach was utilized for the

second case to predict the optimumhydrogen removal profile.

In the third case, both temperature and hydrogen removal

were simultaneously optimized. Generally, the best results

were obtained by application of the third case. Aromatics and

hydrogen production improved 24% and 10% by using this

optimization technique. Optimization results indicated that

shifting the main load of the production form the first reactor

to the second and third reactors can enhance the production

rate due to prevention of sudden fuel depletion. Furthermore,

the optimization results demonstrate the superiority of the

optimized configuration to the conventional reactor from the

operational view point. Thus, operating under optimized

conditions and devising some technologies such as mem-

brane for hydrogen removal can properly improve the main

products yield and the reactor performance and also address

the hydrogen and high-octane gasoline demands in refineries.

This mathematical modeling provides a primary insight for

evaluating the performance of the novel configuration in

refineries, however; experiments should be supplemented to

such a theoretical work to have an entire judgment for future

plant design.

Nomenclature

a catalyst activity

ar moles of aromatics formed, kmol h�1

Ac cross-section area of reactor, m2

cp specific heat capacity, kJ kmol�1 K�1

dp particle diameter, m

Ed activation energy of catalyst, J mol�1

Ei activation energy for ith reaction, kJ kmol�1

Fi molar flow rate of component i

hf heat transfer coefficient, W m�2 K�1

keff effective thermal conductivity, W m�1 s�1

kf1 forward rate constant for reaction (1),

kmol h�1 kgcat�1 MPa�1

kf2 forward rate constant for reaction (2),

kf3 forward rate constant for reactions (3),

kf4 forward rate constant for reactions (4),

Ke1 equilibrium constant, MPa3

Ke2 equilibrium constant, MPa�1

L length of reactor, m

Mi molecular weight of component i, kg kmol�1

Mw average molecular weight of the feedstock,

kg kmol�1

n moles of naphthenes formed, kmol h�1

NA molar flow rate of aromatic, kmol h�1

Ni molar flow rate of component i, kmol h�1

p moles of paraffin formed, kmol h�1

Pi partial pressure of ith component, kPa

P total pressure, kPa

Q volumetric flow rate, m3 s�1

ri rate of reaction for ith reaction, kmol kgcat�1 h�1

R gas constant, kJ kmol�1 K�1

sa specific surface area of catalyst pellet, m2 kg�1

T temperature of gas phase, �Kyi mole fraction for ith component in gas phase

Greek letters

3 void fraction of catalyst bed

m viscosity of gas phase, kg m�1 s�1

r density of gas phase, kg m�3

rb reactor bulk density, kg m�3

ΔH heat of reaction, kJ kmol�1

Subscripts and superscripts

ar aromatic

cal calculated

h hydrogen

i numerator for reaction

j numerator for component

n naphthene

out outlet

p paraffin

Abbreviations

CR conventional reactor

FBP final boiling pint, �CHC hydrocarbon

IBP initial boiling pint, �CLHSV liquid hourly space velocity, h�1

Pt platinum

Re rhenium

TBP true boiling point, �K

r e f e r e n c e s

[1] Aitani AM. Catalytic naphtha reforming. In: Encyclopedia ofchemical processing; 2005. doi:10.1081/E-ECHP-120039766.

[2] Smith RB. Kinetic analysis of naphtha reforming withplatinum catalyst. Chem Eng Prog 1959;55(6):76e80.

[3] Juarez JA, Macias EV. Kinetic modeling of naphtha catalyticreforming reactions. Energy Fuels 2000;14:1032e7.

[4] Stijepovic MZ, Ostojic AV, Milenkovic I, Linke P. Developmentof a kinetic model for catalytic reforming of naphtha andparameter estimation using industrial plant data. EnergyFuels 2009;23:979e83.

[5] Ramage MP, Graziani KP, Krambeck FJ. 6 Development ofMobil’s kinetic reforming model. Chem Eng Sci 1980;35:41e8.

[6] Ramage MP, Graziani KR, Schipper PH, Krambeck FJ, Choi BC.A review of Mobil’s industrial process modeling philosophy.Adv Chem Eng 1987;13:193e266.

[7] Krane HG, Groh AB, Schuhnan BL, Sinfeh JH. Reactions incatalytic reforming of naphtha. In: Paper presented in fifthworld petroleum congress; 1960.

[8] Kmak WS. A kinetic simulation model of the power formingprocess. In: AIChE national meeting; 1972.

[9] Li J, Tan Y, Liao L. Modeling and optimization of a semi-regenerative catalytic naphtha reformer. In: Conference oncontrol application; 2005.

[10] Stijepovic MZ, Linke P, Kijevcanin M. Optimization approachfor continuous catalytic regenerative reformer process.Energy Fuels 2010;24:1908e16.

[11] Weifeng H, Hongye S, Shengjing M, Jian C. Multi objectiveoptimization of the industrial naphtha catalytic reformingprocess. Chin J Chem Eng 2007;15(1):75e80.

[12] KhosravanipourMostafazadeh A, Rahimpour MR. Amembrane catalytic bed concept for naphtha reforming inthe presence of catalyst deactivation. Chem Eng Process2009;48:683e94.

[13] Iranshahi D, Rahimpour MR, Asgari A. A novel dynamicradial-flow, spherical-bed reactor concept for naphthareforming in the presence of catalyst deactivation. Int JHydrogen Energy 2010;35:6261e75.

[14] Rahimpour MR, Iranshahi D, Bahmanpour AM. Dynamicoptimization of a multi-stage spherical, radial flow reactorfor the naphtha reforming process in the presence of catalystdeactivation using differential evolution (DE) method. Int JHydrogen Energy 2010;35(14):7498e511.

[15] Iranshahi D, Bahmanpour AM, Pourazadi E, Rahimpour MR.Mathematical modeling of a multi-stage naphtha reformingprocess using novel thermally coupled recuperative reactorsto enhance aromatic production. Int J Hydrogen Energy 2010;35(20):10984e93.

[16] Iranshahi D, Pourazadi E, Paymooni K, Bahmanpour AM,Rahimpour MR, Shariati A. Modeling of an axial flow,spherical packed-bed reactor for naphtha reforming processin the presence of the catalyst deactivation. Int J HydrogenEnergy 2010;35(23):12784e99.

[17] Rahimpour MR, Iranshahi D, Pourazadi E, Bahmanpour AM.A comparative study on a novel combination of sphericaland membrane tubular reactors of the catalytic naphthareforming process. Int J Hydrogen Energy 2011;36(1):505e17.

[18] Rahimpour MR, Vakili R, Pourazadi E, Iranshahi D,Paymooni K. A novel integrated, thermally coupled fluidizedbed configuration for catalytic naphtha reforming to

enhance aromatic and hydrogen productions in refineries.Int J Hydrogen Energy 2011;36(4):2979e91.

[19] Iranshahi D, Pourazadi E, Bahmanpour AM, Rahimpour MR.A comparison of two different flow types on performance ofa thermally coupled recuperative reactor containing naphthareforming process and hydrogenation of nitrobenzene. Int JHydrogen Energy 2011;36(5):3483e95.

[20] Iranshahi D, Pourazadi E, Paymooni K, Rahimpour MR.Enhancement of aromatic production in naphtha reformingprocess by simultaneous operation of isothermal andadiabatic reactors. Int J Hydrogen Energy 2011;36(3):2076e85.

[21] Onozaki M, Watanabe K, Hashimoto T, Saegusa H,Katayama Y. Fuel 2006;85:143e9.

[22] Alves JJ, Towler GP. Analysis of refinery hydrogendistribution systems. Ind Eng Chem Res 2002;41(23):5759e69.

[23] Hallale N, Moore I, Vauk D. Hydrogen: liability or asset. ChemEng Prog 2002;98(9):66e75.

[24] Liu F, Zhang N. Strategy of purifier selection and integrationin hydrogen networks. ChemEng Res Des 2004;82:1315e30.

[25] Kirkpatrik S, Gelatt CD, Vechhi MP. Optimization bysimulated annealing. Science 1983;220(4568):671e80.

[26] Schwefel HP. Numerical optimization of computer models.New York: John Wiley & Sons; 1981.

[27] Goldberg DE. Genetic algorithms in search, optimization, andmachine learning. Reading, MA: Addison-Wesley; 1989.

[28] Davis L. Handbook of genetic algorithms. New York: VanNostrand Reinhold; 1991.

[29] Price K, Storn R. Differential evolution e a simple evolutionstrategy for fast optimization. Dr. Dobb’s J 1997;22:18e24.

[30] Babu BV, Angira R. Modified differential evolution (MDE) foroptimization of non-linear chemical processes. ComputChem Eng 2006;30(6e7):989e1002.

[31] Babu BV, Khan M. Optimization of reactive distillationprocesses using differential evolution strategies. Asia-PacificJ ChemEng 2007;2(4):322e35.

[32] Fang Q, Chen D, Yu H, Wu X. Differential evolution algorithmbased on eugenic strategy and its application to chemicalengineering. Huagong Xuebao/J Chem Industa Eng 2004;55(4):598e602.

[33] Ponsich A, Coello CAC. Differential evolution performancesfor the solution of mixed-integer constrained processengineering problems. Appl Soft Comput J 2011;11(1):399e409.

[34] Angira R, Santosh A. A modified trigonometric differentialevolution algorithm for optimization of dynamic systems2008. IEEE Congress on Evolutionary Computation, CEC; 2008.Article number 4630986. pp. 1463e8.

[35] Rase HF. Chemical reactor design for process plants. JohnWiley & Sons Inc; 1977.

[36] JessA,HeinO, KernC.Deactivation anddecoking of a naphthareforming catalyst. Stud Surf Sci Catal 1999;126:81e8.

[37] Behin J, Kavianpour HR. A comparative study for thesimulation of industrial naphtha reforming reactors withcorresponding pressure drop on catalyst. Pet Coal 2009;51(3):208e15.

[38] Rahimpour MR. Operability of an industrial catalytic naphthareformer in the presence of catalyst deactivation. Chem EngTechnol 2006;5:29.

Simultaneous hydrogen and aromatics enhancement by obtaining optimum temperature profile and...

Documents

Transcript of Simultaneous hydrogen and aromatics enhancement by obtaining optimum temperature profile and...

Non-thermal hydrogen in the Venus exosphere - The ionospheric source and the hydrogen budget

SAFETY STANDARD FOR HYDROGEN AND HYDROGEN ...

2Amino5-nitropyridinium hydrogen selenate

Control of chemoselectivity in hydrogenations of substituted nitro- and cyano-aromatics by cluster-derived ruthenium nanocatalysts

Design of a Hydrogen Community

Time and frequency domain analysis of hydrogen permeation across PdCu metallic membranes for hydrogen purification

Naphtha reforming process development methodol - Archive ...

Hydrogen Sulfide Regulates Homocysteine-Mediated Glomerulosclerosis

Hydrogen Atom - nanoHUB

Determination of mercury in naphtha and petroleum condensate by photochemical vapor generation atomic absorption spectrometry

2Amino3-nitropyridinium hydrogen oxalate

Hydrogen on demand installation

Process Intensification of Hydrogen Plants and Naphtha Crackers

a) Revenue from operation - Oriental Aromatics

Hydrogen in N-Methylacetamide: Positions and dynamics of the hydrogen atoms using neutron scattering

Hydrogen Sulfide and Urogenital Tract

EBTAX: The Conversion of Ethane to Aromatics via Catalytic ...

Selective Aromatics extraction from hydrocarbon mixtures

REVAMP OF NAPHTHA HYDROTREATING PROCESS IN AN IRANIAN REFINERY

Mechanochemical synthesis of hydrogen-storage materials ...