- Email: [email protected]
Optimal operation of an ethylene plant utility system
OPl'IMAL OPERATION OF AN ETHYLENE PLANT UTILITY SYSTEM N. Petracci, A.M. Eliceche, A. Bandoni and E.A. Brignole
PLAPIQUI, UNS - CONICET 12 de Octubre 1842 - 8000 BahIa Blanca - ARGENTINA
ABSTRACT The algorithm developed allows the selection of the pressure and temperature conditions of the high, medium and low pressure vapor headers and the deaerator pressure of an ethylene plant utility system. The utility system optimization can be done simultaneously with the ethylene plant optimization including four decision variables: conversion and dilution ratio of the pyrolysis reactor, cracked-gas compressor inlet pressure and demethanizer column pressure. Their values are calculated, solving a Nonlinear Programming subproblem where the modeling equations of the utility system and the ethylene plant are considered. A rigorous simulation of the utility system is carried out using a water property prediction package. There is a strong integration between the ethylene plant and the utility system due to the generation of high steam pressure in the pyrolysis reactor or the use of residual gas as fuel gas in the boilers. The sensitivity of the profit function with respect to the ethylene and utility plant optimization variables is shown for different ethylene prices optimal solutions. KEYWORDS: Utility Syste_, Ethylene Plant, Opti_ization.
INTRODUCTION The utility system provides power to drive the process units, high, medium and low pressure steam, treated and cooling water for the ethylene plant. The main units, as shown in Fig. I, are high, medium and low pressure headers, boilers, turbines, heat exchangers, flash drums, deaerator, let down stations, vents and other units associated with steam systems.In a previous work, Petracci et al. (1991) developed a Mixed Integer Nonlinear Programming (MINLP) algorithm to select the drivers configuration (electrical motors or steam turbines) simultaneously with some continuous optimization variables such as the deaerator pressure and flow rates. The solution procedure to solve the MINLP problems alternates between Nonlinear Programming (NLP) and Mixed Integer Linear Programming subproblems. They solve the NLP subproblem by successive linearizations. The ethylene plant and the headers conditions were kept constant. The main purpose of this work is to include the temperature and pressure of the steam headers as continuous optimization variables. They can be optimized for fixed operating conditions of the ethylene plant or both plants can be optimized simultaneously in the NLP subproblem. The NLP subproblem is solved by a Successive Quadratic Programming approach due to the fact that the system including the continuous optimization variables of the utility and ethylene plants is highly non linear. 5147
SI48
European Symposium on Computer Aided Process Engineering-2
ETHYLENE PLANT OPTIMIZATION
The optimization studies are carried out for a 250000 Tons/year ethylene plant using ethane-propane mixtures as feedstocks. The optimization package (Diaz et al. (1992» is supported by a tailor made plant simulator based on realistic reduced plant models. More than 400 equipment, economic and process parameters can be studied in the simulator, that computes more than 3000 process and economic variables. This package is used to study the effect of utility variables on the process economic sensitivity. In Fig.! the main features of the utility system are shown. Three steam pressures are available: high, medium and low. There are three main turbines: cracked gas compressor (XC1) ,ethylene (XC2) and propylene (XC3) refrigeration compressors. The ethylene compressor also drives the ethylene splitter heat pump system. The ethylene plant is a complex, interacting and very integrated plant, where about 50 X of the high pressure steam (HP) is generated in the pyrolysis furnaces. The XC! is a condensation turbine, however XC2 and XC3 are back pressure turbines that work between medium and low pressure and high and medium pressure respectively. The sensitivity studies of the utility system is based on a rigorous simulation of this sector. There are two alternative objective functions: maximum gross benefit or maximum ethylene production. The continuos variables related to the utility systems are: temperature (HPST) and pressure (HPSP) of the high pressure steam, medium steam pressure (MPSP) I low pressure steam (LPSP) and dearetor pressure.
r-"~~
'JlB9' MBIO san
'!'y
I I.
y
I
1I
r.--. f
<
!
I ~=r==r===F=~~~ Waste ~ i"----Heat ~ . I SOiler , - !
!
.
!
I
X
i t! I _._._._.~._.~.L._._._._
!
ii
"l
0/
~=====~=!====r===~==~~=~~==~~='J
L.P.
i
Header
~
i
~
f
Deaerated Water I
~
i
?Y
~
VacuulI Condenser
I
l.....-._•••__ . ..:J._.~ ......J
i
ii
BFW Pump
'-------l
~~~~=:~T:'-'-'----'-'--HMB'--~--::,--J -
Cooling Water
XB XC
!I
I
Water ._j Make-up '--- reateH--- - Water
Motor Pumps Turbine Pumps Turbine Compressors
Fig.1 Utility Systea
The process optimization variables of the ethylene-plant are: ethane conversion (CONV) and steam dilution rate (DR) of the pyrolisis reactor, cracked gas compressor inlet pressure (IP) and demethanizer column pressure. Economic and
SI49
European Symposium on Computer Aided Process Engineering-2
process data required for the economic evaluations are shown in Table 1. Table 1.Costs, prices and feed data Ethane 111.85 Fuel gas 0.095 Electricity 0.072 Makeup water 0.387 Cooling water 0.01 Ethylene 340. Subproducts 140.
u$s/Ton u$s/Nm3 u$s/Kr u$s/m u$s/m~
u$s/Ton u$s/Ton
Feed flow rate (Kg/h)
36375.
Feed composition (molar fraction %) Methane 1.4 94.3 Ethane Propane 4.3
SENSITIVITY ANALYSIS The non linear programming subproblem has been solved using the Successive Quadratic Programming code OPT implemented by Biegler et al . (1985) • The variations in operating conditions allowed in the real plant are included in the NLP subproblem as lower and upper bounds on the optimization variables (Table 2). Case I corresponds to the normal operating conditions of the ethylene and utili ty plants and is the initial point used for the optimization. The relative contribution of the ethylene and utility system to the variation of the objective function from an initial conditionis studied by computing the incremental benefits obtained by optimizing both sectors independently. The results shown in Table 2 and 3 indicate that at the ethylene price of 340 u$s/Ton the main contribution to the benefit objective function lies in t.he utility sector. However when the initial demethanizer column pressure is increased to 32 bar the contribution of both sectors is of the same order (Table 4). The reason for this is that the demethanizer pressure in Case I is very close to the optimum value. The last column of Tables 2 and 3 give the benefit and operating conditions for the optimum point. A comparison between the utility demands at Case I and for the optimal solution are given in Table 3. It is interesting to study the effect of ethylene price variations on the ethylene plant and utility system optimization. For an ethylene price of 450 uts/Ton the optimal solution for the utility system is the same as before (Table 5) but there is a significant decrease in the optimum value of the cracked gas compressor inlet pressure
(IP)
and an in crease o f
the dilution
ratio.
Both
variables increase the ethylene yield at the expense of higher operating costs. These changes are justified at the higher ethylene price condition.
Table 5. Opti.al point (ethylene price: 450 u$s/Ton) Benefit U$S/h 8036.
CONY
DR
IP
58 0.4 0.45
DP HPST
HPSP
MPSP
29 450
52
22
LPSP
DEAP
3
0.1
The benefit variation with respect to conversion, dilution ratio, inlet pressure, demethanizer pressure and high pressure steam temperature is shown in Figures 3 to 7. The sensitivities were obtained at the optimal solution point for twc ethylene prices. CACE 17 Suppl- K
5150
European Symposium on Computer Aided Process Engineering-2
Table 2. Optiaization for an ethylene price of 340 u$sITon.
Variable/ unit CONV/% DR IP/(Kg/cm 2) r DP " HPSP " MPSP " LPSP " DEAP " HPST oC. BENEFIT ETHYLENE
Lower Bound
Upper Case I Bound
58.00 67.00 60.50 0.20 0.40 0.26 0.20 0.60 0.41 29.00 33.00 29.65 48.00 52.00 50.30 18.00 22.00 19.20 3.00 5.00 3.55 0.10 1. 50 0.37 370.00 450.00 386.00
u$s/h kg/h
Table 3.
4629.5 28595.
Process Utility Overall Optimum Opt Inua Optimum 58.42 0.22 0.37 29.00 50.30 19.20 3.55 0.37 386.00
60.50 0.26 0.41 29.65 52.00 22.00 3.00 0.10 450.00
58.28 0 .30 0.55 29.00 52.00 22.00 3.00 0.10 450.00
4643.5 28652.
4793.6 28595.
4818.2 28866.
Main Deaands for Case I and Optiaal Solution
Cracked gas eomp. Ethylene compo Propylene camp. Boiler steam Furnace steam Cooling water Natural gas
Units
Case I
Opt. Point
HP HP HP
17210. 10556. 6158.
16911. 10823. 6197.
kg/hr kg/hr tn/hr kg/hr
93816. 98861. 7688. 9284.
74392. 98251. 7220. 8357.
Table 4. Benefit variation with different Deaethanizer Coluan Pressure DP
Profit
mrr. with Proe.Opt.
Diff. with UtiLOpt.
DifL with Global Op
Case I
29.65
-t629.5
14
164
188.7
Case II
32.00
4514.4
129
195
308.8
5151
European Symposium on Computer Aided Process Engineering-2
lIOOO
4950 4900
---.c...
4850
(i}
4800
..
4700
..... ~
'0 a.
4150
4650 4600
~
. ... __•.---a 310
380
.----
390
COO
410
420
<130
440
450
4850
8OIlO 7950 7900
4600
'C'
.c
-e-,
-..
~
lIOOO
;;--.........
~<=::~
4750· 4700
.-:
4050
7800
4600
780Il
7750
4550
7750
7700
4500
0
31
30
29
-...
~ 4800 ;;:::
0
a.
4150
-----.....------. ~
-------
4650
4800
8050
4950 - -- --
eooo
4900
1950
-
7700
eoso
'C'
-.. ...__·_··_ ----.---a ~
7900
7850
1650
7800
a.
1800
0
4100
4650
7750
02 -
-
o-"':.3:--:-0.35---~-.l7700
-025
0.4
Dilution Ratio
Fig.6
Fig .5
4950 -
- - -
-~
'C' 4850
.c
4800 4150
6050
- - - ----
4900
• -' .
.-- -..
8OIlO 7950
- - - . - .~
1llOO 7850
4'00
1800
4600
7750
4800
0.2
03
71150
;;::: 4150
7900
Conversion (%)
a::
-
.c:
o,58-O:-6--0 12::--- ""0.64~----~--l 7700 0.66 0.68
~ ~ a
3J
Fig.4
------------
4100
32
7850
Demethanizer Col. Pressure (kg/cm2 r)
4950
s: -.
1900
a.
Fig .3
'C' 4850
1950
7850
HPS Temperature (oC)
4900
8OIlO
0.4
0.45
0.5
0.55
Inlet Pressure (kg/cm2 r)
Fi g. 7
0.6
1700
S152
European Symposium on Computer Aided Process Engineering-2
Table 6. Sensitivity of opti.ization variables CONV
.1x
10.
DR
IP
DP HPST
HPSP MPSP
0.2
0.4
4.
80.
4
4
2.
LPSP DEAP 1.4
ABenefits (340 u$s/Ton)
72
24 38 -272
182
14
66
-27
-10
6Benefits (450 u$s/Ton)
140
99 32 -151
185
5
63
-32
-11
A sensitivity study of the optimization variables in the near optimum region was carried out for the two ethylene prices considered. The results obtained are given in Table 6 in which the variations in optimization variables and their effect on the plant benefits are shown. These results indicate that for both price levels the utility variables playa significant role in the plant optimal operation. High pressure steam temperature (HPST) and medium pressure steam pressure (MPSP) are the most sensitive among the utility variables. All the process optimization variables have a significant effect on the objetive function, however at the higher ethylene price the sensitivity of the benefits with respect to the ethylene conversion and ethane dilution ratio are greater than for the 340 u$s/Ton case. The sensitivity of the utility variables does not change with ethylene price because they influence the costs term of the objetive function.
CONCLUSIONS Significant benefits can be achieved by optimization of continuous variables of the utility system. The high pressure steam temperature is the more sensitive utility variable, followed by the medium steam pressure. The optimal control of both variables leads to important savings in operating costs. For low ethylene price conditions, an increase in cracked gas compressor inlet pressure and a decrease in demethanizer pressure from normal operating conditions are clearly justified. The sensitivity with respect to conversion and dilution ratio increases with the ethylene price. These results show the economic potential of overall optimization of ethylene plants process and utility systems.
REFERENCES Biegler, L.T. and J. E.Cuthrell (1985). Improved Unfeasible Path Optimization for sequential Modular Simulators II: The Optimization Algorithm. Comp.and Chern. Engn., 9 (3), 257. Diaz M.S., J.A.Bandoni, N.Petracci, L.Aparicio and E.A.Brignole (1992). Estructural and Parameter Optimization of an Ethylene Plant, ESCAPE I, Helsingor, Denmark. Petracci. N.• E.A.Brignole and A.M.Eliceche (1991). Utility System Optimal Operation. Computer-Oriented Process Engineering (L.Puigjaner and A.Espunia ed.). p 387, Elsevier.
PLAPIQUI, UNS - CONICET 12 de Octubre 1842 - 8000 BahIa Blanca - ARGENTINA
ABSTRACT The algorithm developed allows the selection of the pressure and temperature conditions of the high, medium and low pressure vapor headers and the deaerator pressure of an ethylene plant utility system. The utility system optimization can be done simultaneously with the ethylene plant optimization including four decision variables: conversion and dilution ratio of the pyrolysis reactor, cracked-gas compressor inlet pressure and demethanizer column pressure. Their values are calculated, solving a Nonlinear Programming subproblem where the modeling equations of the utility system and the ethylene plant are considered. A rigorous simulation of the utility system is carried out using a water property prediction package. There is a strong integration between the ethylene plant and the utility system due to the generation of high steam pressure in the pyrolysis reactor or the use of residual gas as fuel gas in the boilers. The sensitivity of the profit function with respect to the ethylene and utility plant optimization variables is shown for different ethylene prices optimal solutions. KEYWORDS: Utility Syste_, Ethylene Plant, Opti_ization.
INTRODUCTION The utility system provides power to drive the process units, high, medium and low pressure steam, treated and cooling water for the ethylene plant. The main units, as shown in Fig. I, are high, medium and low pressure headers, boilers, turbines, heat exchangers, flash drums, deaerator, let down stations, vents and other units associated with steam systems.In a previous work, Petracci et al. (1991) developed a Mixed Integer Nonlinear Programming (MINLP) algorithm to select the drivers configuration (electrical motors or steam turbines) simultaneously with some continuous optimization variables such as the deaerator pressure and flow rates. The solution procedure to solve the MINLP problems alternates between Nonlinear Programming (NLP) and Mixed Integer Linear Programming subproblems. They solve the NLP subproblem by successive linearizations. The ethylene plant and the headers conditions were kept constant. The main purpose of this work is to include the temperature and pressure of the steam headers as continuous optimization variables. They can be optimized for fixed operating conditions of the ethylene plant or both plants can be optimized simultaneously in the NLP subproblem. The NLP subproblem is solved by a Successive Quadratic Programming approach due to the fact that the system including the continuous optimization variables of the utility and ethylene plants is highly non linear. 5147
SI48
European Symposium on Computer Aided Process Engineering-2
ETHYLENE PLANT OPTIMIZATION
The optimization studies are carried out for a 250000 Tons/year ethylene plant using ethane-propane mixtures as feedstocks. The optimization package (Diaz et al. (1992» is supported by a tailor made plant simulator based on realistic reduced plant models. More than 400 equipment, economic and process parameters can be studied in the simulator, that computes more than 3000 process and economic variables. This package is used to study the effect of utility variables on the process economic sensitivity. In Fig.! the main features of the utility system are shown. Three steam pressures are available: high, medium and low. There are three main turbines: cracked gas compressor (XC1) ,ethylene (XC2) and propylene (XC3) refrigeration compressors. The ethylene compressor also drives the ethylene splitter heat pump system. The ethylene plant is a complex, interacting and very integrated plant, where about 50 X of the high pressure steam (HP) is generated in the pyrolysis furnaces. The XC! is a condensation turbine, however XC2 and XC3 are back pressure turbines that work between medium and low pressure and high and medium pressure respectively. The sensitivity studies of the utility system is based on a rigorous simulation of this sector. There are two alternative objective functions: maximum gross benefit or maximum ethylene production. The continuos variables related to the utility systems are: temperature (HPST) and pressure (HPSP) of the high pressure steam, medium steam pressure (MPSP) I low pressure steam (LPSP) and dearetor pressure.
r-"~~
'JlB9' MBIO san
'!'y
I I.
y
I
1I
r.--. f
<
!
I ~=r==r===F=~~~ Waste ~ i"----Heat ~ . I SOiler , - !
!
.
!
I
X
i t! I _._._._.~._.~.L._._._._
!
ii
"l
0/
~=====~=!====r===~==~~=~~==~~='J
L.P.
i
Header
~
i
~
f
Deaerated Water I
~
i
?Y
~
VacuulI Condenser
I
l.....-._•••__ . ..:J._.~ ......J
i
ii
BFW Pump
'-------l
~~~~=:~T:'-'-'----'-'--HMB'--~--::,--J -
Cooling Water
XB XC
!I
I
Water ._j Make-up '--- reateH--- - Water
Motor Pumps Turbine Pumps Turbine Compressors
Fig.1 Utility Systea
The process optimization variables of the ethylene-plant are: ethane conversion (CONV) and steam dilution rate (DR) of the pyrolisis reactor, cracked gas compressor inlet pressure (IP) and demethanizer column pressure. Economic and
SI49
European Symposium on Computer Aided Process Engineering-2
process data required for the economic evaluations are shown in Table 1. Table 1.Costs, prices and feed data Ethane 111.85 Fuel gas 0.095 Electricity 0.072 Makeup water 0.387 Cooling water 0.01 Ethylene 340. Subproducts 140.
u$s/Ton u$s/Nm3 u$s/Kr u$s/m u$s/m~
u$s/Ton u$s/Ton
Feed flow rate (Kg/h)
36375.
Feed composition (molar fraction %) Methane 1.4 94.3 Ethane Propane 4.3
SENSITIVITY ANALYSIS The non linear programming subproblem has been solved using the Successive Quadratic Programming code OPT implemented by Biegler et al . (1985) • The variations in operating conditions allowed in the real plant are included in the NLP subproblem as lower and upper bounds on the optimization variables (Table 2). Case I corresponds to the normal operating conditions of the ethylene and utili ty plants and is the initial point used for the optimization. The relative contribution of the ethylene and utility system to the variation of the objective function from an initial conditionis studied by computing the incremental benefits obtained by optimizing both sectors independently. The results shown in Table 2 and 3 indicate that at the ethylene price of 340 u$s/Ton the main contribution to the benefit objective function lies in t.he utility sector. However when the initial demethanizer column pressure is increased to 32 bar the contribution of both sectors is of the same order (Table 4). The reason for this is that the demethanizer pressure in Case I is very close to the optimum value. The last column of Tables 2 and 3 give the benefit and operating conditions for the optimum point. A comparison between the utility demands at Case I and for the optimal solution are given in Table 3. It is interesting to study the effect of ethylene price variations on the ethylene plant and utility system optimization. For an ethylene price of 450 uts/Ton the optimal solution for the utility system is the same as before (Table 5) but there is a significant decrease in the optimum value of the cracked gas compressor inlet pressure
(IP)
and an in crease o f
the dilution
ratio.
Both
variables increase the ethylene yield at the expense of higher operating costs. These changes are justified at the higher ethylene price condition.
Table 5. Opti.al point (ethylene price: 450 u$s/Ton) Benefit U$S/h 8036.
CONY
DR
IP
58 0.4 0.45
DP HPST
HPSP
MPSP
29 450
52
22
LPSP
DEAP
3
0.1
The benefit variation with respect to conversion, dilution ratio, inlet pressure, demethanizer pressure and high pressure steam temperature is shown in Figures 3 to 7. The sensitivities were obtained at the optimal solution point for twc ethylene prices. CACE 17 Suppl- K
5150
European Symposium on Computer Aided Process Engineering-2
Table 2. Optiaization for an ethylene price of 340 u$sITon.
Variable/ unit CONV/% DR IP/(Kg/cm 2) r DP " HPSP " MPSP " LPSP " DEAP " HPST oC. BENEFIT ETHYLENE
Lower Bound
Upper Case I Bound
58.00 67.00 60.50 0.20 0.40 0.26 0.20 0.60 0.41 29.00 33.00 29.65 48.00 52.00 50.30 18.00 22.00 19.20 3.00 5.00 3.55 0.10 1. 50 0.37 370.00 450.00 386.00
u$s/h kg/h
Table 3.
4629.5 28595.
Process Utility Overall Optimum Opt Inua Optimum 58.42 0.22 0.37 29.00 50.30 19.20 3.55 0.37 386.00
60.50 0.26 0.41 29.65 52.00 22.00 3.00 0.10 450.00
58.28 0 .30 0.55 29.00 52.00 22.00 3.00 0.10 450.00
4643.5 28652.
4793.6 28595.
4818.2 28866.
Main Deaands for Case I and Optiaal Solution
Cracked gas eomp. Ethylene compo Propylene camp. Boiler steam Furnace steam Cooling water Natural gas
Units
Case I
Opt. Point
HP HP HP
17210. 10556. 6158.
16911. 10823. 6197.
kg/hr kg/hr tn/hr kg/hr
93816. 98861. 7688. 9284.
74392. 98251. 7220. 8357.
Table 4. Benefit variation with different Deaethanizer Coluan Pressure DP
Profit
mrr. with Proe.Opt.
Diff. with UtiLOpt.
DifL with Global Op
Case I
29.65
-t629.5
14
164
188.7
Case II
32.00
4514.4
129
195
308.8
5151
European Symposium on Computer Aided Process Engineering-2
lIOOO
4950 4900
---.c...
4850
(i}
4800
..
4700
..... ~
'0 a.
4150
4650 4600
~
. ... __•.---a 310
380
.----
390
COO
410
420
<130
440
450
4850
8OIlO 7950 7900
4600
'C'
.c
-e-,
-..
~
lIOOO
;;--.........
~<=::~
4750· 4700
.-:
4050
7800
4600
780Il
7750
4550
7750
7700
4500
0
31
30
29
-...
~ 4800 ;;:::
0
a.
4150
-----.....------. ~
-------
4650
4800
8050
4950 - -- --
eooo
4900
1950
-
7700
eoso
'C'
-.. ...__·_··_ ----.---a ~
7900
7850
1650
7800
a.
1800
0
4100
4650
7750
02 -
-
o-"':.3:--:-0.35---~-.l7700
-025
0.4
Dilution Ratio
Fig.6
Fig .5
4950 -
- - -
-~
'C' 4850
.c
4800 4150
6050
- - - ----
4900
• -' .
.-- -..
8OIlO 7950
- - - . - .~
1llOO 7850
4'00
1800
4600
7750
4800
0.2
03
71150
;;::: 4150
7900
Conversion (%)
a::
-
.c:
o,58-O:-6--0 12::--- ""0.64~----~--l 7700 0.66 0.68
~ ~ a
3J
Fig.4
------------
4100
32
7850
Demethanizer Col. Pressure (kg/cm2 r)
4950
s: -.
1900
a.
Fig .3
'C' 4850
1950
7850
HPS Temperature (oC)
4900
8OIlO
0.4
0.45
0.5
0.55
Inlet Pressure (kg/cm2 r)
Fi g. 7
0.6
1700
S152
European Symposium on Computer Aided Process Engineering-2
Table 6. Sensitivity of opti.ization variables CONV
.1x
10.
DR
IP
DP HPST
HPSP MPSP
0.2
0.4
4.
80.
4
4
2.
LPSP DEAP 1.4
ABenefits (340 u$s/Ton)
72
24 38 -272
182
14
66
-27
-10
6Benefits (450 u$s/Ton)
140
99 32 -151
185
5
63
-32
-11
A sensitivity study of the optimization variables in the near optimum region was carried out for the two ethylene prices considered. The results obtained are given in Table 6 in which the variations in optimization variables and their effect on the plant benefits are shown. These results indicate that for both price levels the utility variables playa significant role in the plant optimal operation. High pressure steam temperature (HPST) and medium pressure steam pressure (MPSP) are the most sensitive among the utility variables. All the process optimization variables have a significant effect on the objetive function, however at the higher ethylene price the sensitivity of the benefits with respect to the ethylene conversion and ethane dilution ratio are greater than for the 340 u$s/Ton case. The sensitivity of the utility variables does not change with ethylene price because they influence the costs term of the objetive function.
CONCLUSIONS Significant benefits can be achieved by optimization of continuous variables of the utility system. The high pressure steam temperature is the more sensitive utility variable, followed by the medium steam pressure. The optimal control of both variables leads to important savings in operating costs. For low ethylene price conditions, an increase in cracked gas compressor inlet pressure and a decrease in demethanizer pressure from normal operating conditions are clearly justified. The sensitivity with respect to conversion and dilution ratio increases with the ethylene price. These results show the economic potential of overall optimization of ethylene plants process and utility systems.
REFERENCES Biegler, L.T. and J. E.Cuthrell (1985). Improved Unfeasible Path Optimization for sequential Modular Simulators II: The Optimization Algorithm. Comp.and Chern. Engn., 9 (3), 257. Diaz M.S., J.A.Bandoni, N.Petracci, L.Aparicio and E.A.Brignole (1992). Estructural and Parameter Optimization of an Ethylene Plant, ESCAPE I, Helsingor, Denmark. Petracci. N.• E.A.Brignole and A.M.Eliceche (1991). Utility System Optimal Operation. Computer-Oriented Process Engineering (L.Puigjaner and A.Espunia ed.). p 387, Elsevier.