Plantwide Control for Economically
Optimal Operation of Chemical Plants
- Applications to GTL plants and CO2 capturing processes
Mehdi Panahi
PhD defense presentation
December 1st, 2011
Trondheim
M. Panahi ’Plantwide Control for Economically Optimal Operation of Chemical Plants’
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Outline
 Ch.2 Introduction
 Ch.4 Economically optimal operation of CO2
capturing process; selection of controlled variables
 Ch.5 Economically optimal operation of CO2
capturing process; design control layers
 Ch.6 Modeling and optimization of natural gas to
liquids (GTL) process
 Ch.7 Self-optimizing method for selection of
controlled variables for GTL process
 Ch.8 Conclusions and future works
M. Panahi ’Plantwide Control for Economically Optimal Operation of Chemical Plants’
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Outline
 Ch.2 Introduction
 Ch.4 Economically optimal operation of CO2
capturing process; selection of controlled variables
 Ch.5 Economically optimal operation of CO2
capturing process; design control layers
 Ch.6 Modeling and optimization of natural gas to
liquids (GTL) process
 Ch.7 Self-optimizing method for selection of
controlled variables for GTL process
 Ch.8 Conclusions and future works
M. Panahi ’Plantwide Control for Economically Optimal Operation of Chemical Plants’
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Skogestad plantwide control procedure
I Top Down
• Step 1: Identify degrees of freedom (MVs)
• Step 2: Define operational objectives (optimal operation)
– Cost function J (to be minimized)
– Operational constraints
• Step 3: Select primary controlled variables CV1s (Self-optimizing)
• Step 4: Where set the production rate? (Inventory control)
II Bottom Up
• Step 5: Regulatory / stabilizing control (PID layer)
– What more to control (CV2s; local CVs)?
– Pairing of inputs and outputs
• Step 6: Supervisory control (MPC layer)
• Step 7: Real-time optimization
M. Panahi ’Plantwide Control for Economically Optimal Operation of Chemical Plants’
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Optimal Operation
Mode I: maximize efficiency
Mode II: maximize throughput
Self-optimizing control is when we can achieve acceptable
loss with constant setpoint values for the controlled variables
without the need to reoptimize the plant when disturbances
occur
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Selection of CVs: Self-optimizing control procedure
Step 3-1: Define an objective function and constraints
Step 3-2: Degrees of freedom (DOFs)
Step 3-3: Disturbances
Step 3-4: Optimization (nominally and with disturbances)
Step 3-5: Identification of controlled variables (CVs) for
unconstrained DOFs
Step 3-6: Evaluation of loss
M. Panahi ’Plantwide Control for Economically Optimal Operation of Chemical Plants’
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Maximum gain rule for selection the best CVs
Let G denote the steady-state gain matrix from inputs u (unconstrained
degrees of freedom) to outputs z (candidate controlled variables). Scale
the outputs using S1
 1 
S1 =diag 

span(z
)

i 
L max =
span(zi )= max zi -zi,opt = max ei,opt (d)+ max ei
d,e
d
e
1
1
2 σ 2 (S1GJ -1/2
uu )
For scalar case, which usually happens in many cases, the
maximum expected loss is:
J
1
L max = uu
2 S1G 2
Maximum gain rule is useful for prescreening the sets of best controlled
variables
M. Panahi ’Plantwide Control for Economically Optimal Operation of Chemical Plants’
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Exact local method for selection the best CVs
1
max. Loss= σ(M) 2
2
1/2
uu
y-1
M=J G (FWd Wn )
F=Gy J-1uu Jud -Gdy
Δy opt.
F is optimal sensitivity of the measurements with respect to disturbances; F=
Δd
M. Panahi ’Plantwide Control for Economically Optimal Operation of Chemical Plants’
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Applications of plantwide procedure to two
important processes
1. Post-combustion CO2 capturing processes
(Chapters 3, 4 and 5)
2. Converting of natural gas to liquid hydrocarbons
(Chapters 6 and 7)
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Importance of optimal operation for CO2
capturing process
Dependency of equivalent energy in CO2
capture plant verses recycle amine flowrate
An amine absorption/stripping CO2 capturing process*
*Figure from: Toshiba (2008). Toshiba to Build Pilot Plant to Test CO2 Capture Technology.
http://www.japanfs.org/en/pages/028843.html.
M. Panahi ’Plantwide Control for Economically Optimal Operation of Chemical Plants’
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Gas commercialization options and situation of GTL processes
A simple flowsheet of a GTL process
M. Panahi ’Plantwide Control for Economically Optimal Operation of Chemical Plants’
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Outline
 Ch.2 Introduction
 Ch.4 Economically optimal operation of CO2
capturing process; selection of controlled variables
 Ch.5 Economically optimal operation of CO2
capturing process; design control layers
 Ch.6 Modeling and optimization of natural gas to
liquids (GTL) process
 Ch.7 Self-optimizing method for selection of
controlled variables for GTL process
 Ch.8 Conclusions and future works
M. Panahi ’Plantwide Control for Economically Optimal Operation of Chemical Plants’
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Economically optimal operation of CO2 capturing
Step 1. Objective function:
Cooling
Water in
min. (energy cost + cost of released CO2 to the air)
V-9
V-7
Amine
Makeup
V-3
CO2
Condenser
V-8
Stripper
Cooling
Water out
Cooler
Absorber
Step 2. 10 steady-state degrees of
freedom
Water
Make up
Pump 2
V-4
Surge Tank
Cooling
Water in
n=20
To
Stack
V-2
n=15
Cooling
Water out
V-10
Step 3. 3 main disturbances
Rich/Lean Exchanger
Step 4. Optimization
4 equality constraints and 2 inequality
Flue Gas
n=1
from Power
Plant
n=1
Pump 1
Reboiler
Steam
V-5
Condensate
2 unconstrained degrees of freedom;10-4-4=2
V-6
V-1
Steps 5&6. Exact Local method: The candidate CV set that
imposes the minimum worst case loss to the objective function
M. Panahi ’Plantwide Control for Economically Optimal Operation of Chemical Plants’
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Exact local method for selection of the best CVs
39 candidate CVs
- 15 possible tray temperature in the absorber
- 20 possible tray temperature in the stripper
- CO2 recovery in the absorber and CO2 content at the bottom of the stripper
- Recycle amine flowrate and reboiler duty
Applying a bidirectional branch and bound algorithm for
finding the best CVs
The best self-optimizing CV set in region I: CO2 recovery (95.26%) and
temperature of tray no. 16 in the stripper
These CVs are not necessarily the best when new constraints meet
M. Panahi ’Plantwide Control for Economically Optimal Operation of Chemical Plants’
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Optimal operational regions as function of feedrate
Region I. Nominal feedrate
Region II. Feedrate >+20%: Max. Heat constraint
Region III. Feedrate >+51%: Min. CO2 recovery constraint
M. Panahi ’Plantwide Control for Economically Optimal Operation of Chemical Plants’
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Proposed control structure with given flue gas flowrate (region I)
M. Panahi ’Plantwide Control for Economically Optimal Operation of Chemical Plants’
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Region II: in presence of large flowrates of flue gas (+30%)
Flowrateof
flue gas
(kmol/hr)
Pumps
duty
(kW)
Optimal nominal
point
219.3
+5% feedrate
Self-optimizing CVs in region I
Cooler
Duty
(kW)
Reboiler
duty
(kW)
Objective
function
(USD/ton)
CO2 recovery
%
Temperature
of
tray no. 16
°C
3.85
95.26
106.9
321.90
1161
2.49
230.3
4.24
95.26
106.9
347.3
1222
2.49
+10% feedrate
241.2
4.22
95.26
106.9
371.0
1279
2.49
+15% feedrate
252.2
4.64
95.26
106.9
473.3
1339
2.49
+19.38% feedrate,
reboiler duty
saturates
261.8
4.56
(+18.44%)
95.26
106.9
419.4
(+30.29%)
1393
(+20%)
2.50
+30% feedrate
(reoptimized)
285.1
4.61
91.60
103.3
359.3
1393
2.65
Saturation of reboiler duty (new operations region, region II); one
unconstrained degree of freedom left
Maximum gain rule for finding the best CV: 37 candidates
Temp. of tray no. 13 in the stripper: the largest scaled gain
M. Panahi ’Plantwide Control for Economically Optimal Operation of Chemical Plants’
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Proposed control structure with given flue gas flowrate (region I)
M. Panahi ’Plantwide Control for Economically Optimal Operation of Chemical Plants’
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Proposed control structure with given flue gas flowrate (region II)
Reboiler duty at the
maximum
M. Panahi ’Plantwide Control for Economically Optimal Operation of Chemical Plants’
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Region III: reaching the minimum allowable CO2 recovery
Flowrate
of
flue gas
(kmol/hr)
Pumps
Duty
(kW)
CO2
recovery
%
Self-optimizing
CV
in region II
Cooler
Duty
(kW)
Reboiler
Duty
(kW)
Objective
function
(USD/ton)
Temperature
of tray 13
°C
Optimal nominal case
in +30%
feedrate
285.1
4.61
91.60
109
359.3
1393
2.65
+40% feedrate
307.02
4.58
86.46
109
315.5
1393
2.97
+50% feedrate
328.95
4.55
81.31
109
290.3
1393
3.31
+52.78% feedrate,
reach to minimum
CO2 recovery
335.1
4.54
80
109
284.6
1393
3.39
A controller needed to set the flue gas flowrate
M. Panahi ’Plantwide Control for Economically Optimal Operation of Chemical Plants’
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Outline
 Ch.2 Introduction
 Ch.4 Economically optimal operation of CO2
capturing process; selection of controlled variables
 Ch.5 Economically optimal operation of CO2
capturing process; design control layers
 Ch.6 Modeling and optimization of natural gas to
liquids (GTL) process
 Ch.7 Self-optimizing method for selection of
controlled variables for GTL process
 Ch.8 Conclusions and future works
M. Panahi ’Plantwide Control for Economically Optimal Operation of Chemical Plants’
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Design of the control layers
Regulatory layer: Control of secondary (stabilizing) CVs (CV2s), PID loops
• Absorber bottom level,
• Stripper (distillation column) temperature,
• Stripper bottom level,
• Stripper top level,
• Stripper pressure,
• Recycle surge tank: inventories of water and amine,
• Absorber liquid feed temperature.
Supervisory (economic) control layer: Control of the primary (economic) CVs
(CV1s), MPC
• CO2 recovery in the absorber,
• Temperature at tray 16 in the stripper,
• Condenser temperature.
M. Panahi ’Plantwide Control for Economically Optimal Operation of Chemical Plants’
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RGA analysis for selection of pairings
1. Dynamic RGA
duty
-0.76s  0.038 
2400s 2 +107s+1

0.45s+0.0754 
205s 2 +18.8s+1 
stripper
0.77 0.23
RGAdyn. (0)= 

 0.23 0.77 
3.5
3
sum
 6.85s+1.74
 19.7s 2 +11.4s+1
G dyn. (s)= 
 (-9.51s-1.02)e-2s
 218s 2 +17.3s+1
Temp. no.16 in the
CO2 recovery
Off-diagonal pairing alt.2
4
||RGA - I||
Recycle
amine
4.5
Reboiler
2.5
2
1.5
1
Diagonal pairing alt.1
0.5
0
-3
10
-2
10
-1
0
10
10
Frequency [rad/min]
1
10
2
10
2. Steady-State RGA
0.5232 1.48 
GSS  10  

 8.47 5.17 
2
 0.27 1.27 
RGA SS = 

 1.27 0.27 
M. Panahi ’Plantwide Control for Economically Optimal Operation of Chemical Plants’
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”Break through” of CO2 at the top of the absorber (UniSim simulation)
Liquid mole fraction of CO2 in trays of the Absorber
tray 15
0,055
0,05
tray 14
tray 13
0,045
tray 12
tray 11
0,04
tray 10
tray 9
mole fraction
tray 1
0,035
tray 8
tray 7
tray 6
tray 15
0,03
0,025
tray 5
tray 4
0,02
tray 3
tray 2
0,015
0
50
100
150
200
250
300
350
400
450
tray 1
Time (min)
M. Panahi ’Plantwide Control for Economically Optimal Operation of Chemical Plants’
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Proposed control structure with given flue gas flowrate,
Alternative 1
M. Panahi ’Plantwide Control for Economically Optimal Operation of Chemical Plants’
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Proposed control structure with given flue gas flowrate,
Alternative 2 (reverse pairing)
M. Panahi ’Plantwide Control for Economically Optimal Operation of Chemical Plants’
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Proposed control structure in region II,
Alternative 3
M. Panahi ’Plantwide Control for Economically Optimal Operation of Chemical Plants’
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Modified alternative 2
Modified Alternative 2: Alternative 4
M. Panahi ’Plantwide Control for Economically Optimal Operation of Chemical Plants’
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Control of self-optimizing CVs using a multivariable controller
M. Panahi ’Plantwide Control for Economically Optimal Operation of Chemical Plants’
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Performance of the proposed control structure, Alternative 1
M. Panahi ’Plantwide Control for Economically Optimal Operation of Chemical Plants’
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Performance of the proposed control structure, Alternative 3
M. Panahi ’Plantwide Control for Economically Optimal Operation of Chemical Plants’
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Performance of the proposed control structure, Alternative 4
M. Panahi ’Plantwide Control for Economically Optimal Operation of Chemical Plants’
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Performance of the proposed control structure, MPC
M. Panahi ’Plantwide Control for Economically Optimal Operation of Chemical Plants’
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Comparison of different alternatives
• Alternative 1 is optimal in region I, but fails in region II
• Alternative 2 handles regions I (optimal) and II (close to optimal), but more
interactions in region I compare to Alternative 1. No need for switching
• Alternative 3 is optimal in region II. Need for switching
• Alternative 4 is modified Alternative 2 ,results in less interactions. No need
for switching
• MPC, similar performance to Alternatives 2 & 4
Alternative 4 is recommended for implementation in practice
M. Panahi ’Plantwide Control for Economically Optimal Operation of Chemical Plants’
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Outline
 Ch.2 Introduction
 Ch.4 Economically optimal operation of CO2
capturing process; selection of controlled variables
 Ch.5 Economically optimal operation of CO2
capturing process; design control layers
 Ch.6 Modeling and optimization of natural gas to
liquids (GTL) process
 Ch.7 Self-optimizing method for selection of
controlled variables for GTL process
 Ch.8 Conclusions and future works
M. Panahi ’Plantwide Control for Economically Optimal Operation of Chemical Plants’
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A simple flowsheet of GTL process
CO+H2+CH4
CO2
CH4
CO+H2
(CH2)n
(CH2)n
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Pre-reformer reactions
Converting higher hydrocarbons
m
)H 2 +nCO
2
than methane, For n  2
Cn Hm +nH2O  (n 
Methanation
CO+3H 2  CH 4 +H 2O
Shift Reaction
CO+H 2O  CO2 +H 2
Auto-thermal reformer (ATR) reactions
Steam reforming of methane:
3
CH4  O2  CO  2H 2O
2
CH 4  H 2O  CO  3H 2
Shift Reaction:
CO  H 2O  CO2  H 2
Oxidation of methane:
Fischer-Tropsch (FT) reactions
nCO  2nH 2  (-CH 2 -) n  nH 2O
M. Panahi ’Plantwide Control for Economically Optimal Operation of Chemical Plants’
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Fischer-Tropsch (FT) reactor
Simulation of a slurry bubble column reactor (SBCR)
Reactions: nCO  2nH 2  (-CH 2 -)n  nH 2O
Kinetics (the model developed by Iglesia et al):
rCH 4 
rCO 
1.08 108 PH 2 PCO 0.05
1  3.3 105 PCO
(
1.96 108 PH 2 0.6 PCO 0.65
5
1  3.3 10 PCO
molCH 4
g-atom surface metal. s
(
)
molCO
)
g-atom surface metal. s
2 n 1
FT products distribution (ASF model): wn  n(1   ) 
41 reactions: 21 reactions for CnH2n+2 and 20 reactions for CnH2n
FT products: C1, C2, C3-C4 (LPG), C5-C11 (Naphtha, Gasoline), C12-C20 (Diesel), C21+ (wax)
M. Panahi ’Plantwide Control for Economically Optimal Operation of Chemical Plants’
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Detailed flowsheet of GTL process (UniSim)
Tail Gas
2937 kmol/hr
3000 kPa
Natural Gas
12673 kmol/hr
8195 kmol/hr
3000 kPa, 40 °C
CH4: 0.3587
CO: 0.1454
H2: 0.2142
N2: 0.1173
CO2: 0.0838
H2O: 0.0024
Other: 0.0782
Compressor
CH4:0.955
C2H6:0.030
C3H8:0.005
n-C4H10:0.004
N2:0.006
Pure Oxygen
(from ASU)
CO2
Water
9736 kmol/hr
936 kmol/hr
5236 kmol/hr
CO2
Removal
FT
Reactor Vapor
200 °C
Steam
675 °C
210°C
210°C
2000 kPa
Heater
Light
Ends
MP Steam
392 kmol/hr
Water
MP Steam
Pre-Reformer
1030 °C
Autothermal
Reformer
(ATR)
MP Saturated
Steam
Syngas
35100 kmol/hr
Liquid
3-Phase
Separator To Upgrading Unit
721 kmol/hr, 30°C
Separator
Natural Gas
(fuel)
Fired
Heater
Purge to fired
heater (as fuel)
(141.4 m3/hr)
vol. mole fraction
LPG: 0.0468
Naphtha/Gasoline: 0.3839
Diesel: 0.3216
Wax: 0.2242
Other: 0.0235
Water
48887 kmol/hr
252 °C, 4000 kPa
38°C
4743 koml/hr
Water
8589 kmol/hr
Extra
Steam
27020 kmol/hr
To fired heater (not shown)
to produce superheat steam
5204 kmol/hr
455 °C, 3000 kPa
16663 kmol/hr
400 °C, 4000 kPa
Superheated
Steam
ASU
Turbines
10 kPa
M. Panahi ’Plantwide Control for Economically Optimal Operation of Chemical Plants’
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Different methods for calculation of α
1) α1
rCH 4
rCO
 0.55
PH0.42
0.6
CO
P

w1  2000

w1
1 1
 1
1 1
 1
16  [  2w2 (

)  ...  25w25 (

)]
16
1   30 1   28
1   352 1   350
(1   )2  2000
16  [
(1   ) 2
1 1
 1
1 1
 1
 2(2 (1   )2 )(

)  ...  25(1  2  3 2  ...20 19 )(1   ) 2 (

)]
16
1   30 1   28
1   352 1   350
1.6
1.5
Value of real roots
1.4
1.3
1.2
1.1
1
0.9
0.8
0.7
0.02
0.03
0.04
0.05
Left hand side value in 6.12
0.06
0.07
Real roots α as a function of the selectivity (1.2 ≤ H2/CO ≤ 2.15)
2) α2
  (0.2332
yCO
 0.633)[1  0.0039(T  533)]
yCO  yH 2
3) Constant α = 0.9 (α3)
M. Panahi ’Plantwide Control for Economically Optimal Operation of Chemical Plants’
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FT reactor performance (single pass) at H2/CO=2 feed for
α1, α2 and α3
α1
α2
α3
CO conversion, %
83.56
86.52
86.97
H2 conversion, %
90.98
91.82
91.97
CH4 formation (kg/kgcat.hr)
0.0106
0.011
0.011
Other hydrocarbons formation
(kg/kgcat.hr)
0.1877
0.1924
0.1924
parameter
M. Panahi ’Plantwide Control for Economically Optimal Operation of Chemical Plants’
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FT Products distribution when α1 is used
M. Panahi ’Plantwide Control for Economically Optimal Operation of Chemical Plants’
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FT Products distribution when α2 is used
M. Panahi ’Plantwide Control for Economically Optimal Operation of Chemical Plants’
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FT Products distribution when α3 is used
M. Panahi ’Plantwide Control for Economically Optimal Operation of Chemical Plants’
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Dependency of different α calculation
methods vs. feed H2/CO
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Optimization formulation
Objective function
Variable income (P): sales revenue – variable costs
Steady-state degrees of freedom
1.
H2O/C (fresh + recycled hydrocarbons to pre-reformer)
2.
O2/C (hydrocarbons into ATR)
3.
Fired heater duty
4.
CO2 recovery percentage
5.
Purge ratio
6.
Recycle ratio to FT reactor
Operational constraints
1.
Molar ratio H2O/C ≥ 0.3
2.
ATR exit temperature ≤ 1030ºC, active at the max.
3.
Inlet temperature to ATR ≤ 675ºC, active at the max.
4.
The purge ratio is optimally around 2%, it is bounded at a higher value, active at the min.
M. Panahi ’Plantwide Control for Economically Optimal Operation of Chemical Plants’
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Optimality of objective function (α2 model) with respect to decision
variables and active constraints, wax price= 0.63 USD/kg
M. Panahi ’Plantwide Control for Economically Optimal Operation of Chemical Plants’
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Outline
 Ch.2 Introduction
 Ch.4 Economically optimal operation of CO2
capturing process; selection of controlled variables
 Ch.5 Economically optimal operation of CO2
capturing process; design control layers
 Ch.6 Modeling and optimization of natural gas to
liquids (GTL) process
 Ch.7 Self-optimizing method for selection of
controlled variables for GTL process
 Ch.8 Conclusions and future works
M. Panahi ’Plantwide Control for Economically Optimal Operation of Chemical Plants’
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Optimal Operation of GTL process
- Mode I: Natural gas is given
- Mode II: Natural gas is also a degree of freedom
(maximum throughput)
M. Panahi ’Plantwide Control for Economically Optimal Operation of Chemical Plants’
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Process flowsheet of GTL process with data for optimal
nominal point (mode I)
3000kPa
2500kPa
Tail Gas
10846 kmol/hr
Compressor I
0.47 MW
CO2
906 kmol/hr
Natural Gas
Compressor II Recycle Tail
0.55 MW
5190 kmol/hr
CO2
Removal
455°C
200°C
675°C
3000 kPa
2700 kPa
V-1
∆P=f(Q)
Water
Natural Gas
(fuel)
1030°C
Autothermal
Reformer
(ATR)
210°C
Vapor
210°C
2500 kPa
MP
Steam
FT
Reactor
Water
Heater
Steam Drum
Liquid
Fired
Heater
Syngas
34627 kmol/hr
HP Saturatied
Steam
Light
Ends
Purge to fired
heater (as fuel)
325 kmol/hr
3-Phase
Separator Liquid fuels to
upgrading unit: 751 kmol/hr
Separator
Pre-Reformer
Steam
gas to FT
7762 kmol/hr
2700 kPa
Oxygen(from ASU)
8195 kmol/hr
CH4:0.955
C2H6:0.030
C3H8:0.005
n-C4H10:0.004
N2:0.006
(144 m3/hr)
vol. mole fractions:
LPG: 0.0525
Naphtha/Gasoline: 0.3759
Diesel: 0.3156
Wax: 0.2257
Water
Water
8560 kmol/hr
906 kmol/hr
Extra
Steam
To fired heater (not shown)
to produce superheat steam
4896 kmol/hr
455°C, 3000 kPa
Superheated Steam
ASU
Turbines
M. Panahi ’Plantwide Control for Economically Optimal Operation of Chemical Plants’
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Mode I: Natural gas flowrate is given
Step 1: Define the objective function and constraints
Variables income
Inequality Constraints
Three inequality constraints + capacity constraints on the variable units; fired heater
(duty +40% compared to nominal), CO2 recovery unit (+20% feedrate), oxygen
plant (+20% oxygen flowrate).
Equality Constraints (Specs:9)
Step 2: Identify degrees of freedom (DOFs) for optimization
15 degrees of freedom
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Step 3: Identification of important disturbances
Natural gas flowrate,
Natural gas composition,
Natural gas price,
FT reactions kinetic parameter,
Change in active constraints value.
M. Panahi ’Plantwide Control for Economically Optimal Operation of Chemical Plants’
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Step 4: Optimization
MIXED method: combines the advantage of global optimization of BOX and
efficiency of SQP method
15 degrees of freedom, 9 equality constraints and 3 active constraints:
unconstrained degrees of freedom: 15 – 9 – 3 = 3, which may be viewed as:
H2O/C, CO2 recovery, tail gas recycle ratio to FT reactor
Step 5. Identification of candidate controlled variables
18 candidate measurements including the three unconstrained degrees of freedom
18  18!
 816
 
3
3!15!
 
Step 6. Selection of CVs
Exact local method for selection of the best CVs
M. Panahi ’Plantwide Control for Economically Optimal Operation of Chemical Plants’
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Individual measurements (mode I)
worst-case loss for the best 5 individual measurement sets
no.
Sets
Loss (USD/hr)
1
y3:CO2 recovery
y9: CO mole
fraction
in fresh syngas
y12: CO mole
fraction
in tail gas
1393
2
y3:CO2 recovery
y2: H2O/C
y6: H2/CO
in tail gas
1457
3
y3:CO2 recovery
y2: H2O/C
y5: H2/CO
in fresh syngas
1698
4
y3:CO2 recovery
y6: H2/CO
in tail gas
y5: H2/CO
in fresh syngas
2594
5
y10:CH4 mole
fraction
in fresh syngas
y6: H2/CO
in tail gas
y5: H2/CO
in fresh syngas
2643
M. Panahi ’Plantwide Control for Economically Optimal Operation of Chemical Plants’
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Control structure for mode I of operation with proposed CVs
and possible pairings with MVs (red lines are by-pass streams)
Self-optimizing CV3
PC
RC
SP=30 bar
SP (splitter ratio)
CC
SP (CO%)=12.96
Tail Gas
Compressor I
Autothermal
Reformer
(ATR)
Natural Gas
TC
Self-optimizing CV2
CO2
SP=27bar
SP (CO2 recovery%)=
75.73
PC
Compressor
II Tail
Recycle
gas to FT
CC
SP=455°C
Oxygen(from ASU)
SP=12.5bar
Vapor
RC
PC
SP=200°C
CO2
Removal
TC
SP=38°C
TC
SP=1030°C
Water
Fired
Heater
Pre-Reformer
Steam
SP=675°C
Natural Gas (fuel)
TC
Syngas
Self-optimizing CV1
CC
SP (H2O/C)
CC
SP (CO%)=25.67
HP Saturated
Steam
SP=455°C
TC
Heater
Water
TC
Steam Drum
SP=210°C
Liquid
Light Purge to fired
Ends heater (as fuel)
Liquid fuels to
upgrading unit
3-Phase
Separator
Separator
TC
MP Steam
FT
Reactor
V-1
∆P=f(Q)
SP=3% purge
SP=30°C
TC
Water
Water
Extra
Steam
To fired heater (not shown)
to produce superheat steam
Superheated
Steam
ASU
Turbines
M. Panahi ’Plantwide Control for Economically Optimal Operation of Chemical Plants’
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Mode II: Natural gas feedrate is also a degree of freedom
Point A: oxygen flowrate saturates
1 extra DOF, 1 new active constraint
M. Panahi ’Plantwide Control for Economically Optimal Operation of Chemical Plants’
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Optimal values in: nominal point, saturation of oxygen flowrate and
maximum throughput
Recycle
ratio
to FT
Purge
of
tail
gas
H2/CO
fresh
H2/CO
into
FT
H2O/C
O2/C
CO2
recovery
opt.
nominal
0.6010
0.523
75.73%
73.79%
3%
2.1
max.
oxygen
0.5357
0.516
76.80%
90%
3%
max.
through
put
0.4084
0.504
76.04%
97.13%
3%
CO conversion %
H2 conversion %

Carbon
efficiency
Objective
function
(USD/hr)
per
pass
overall
per
pass
overall
2.03
85.74
95.50
89.93
96.92
0.87
74.59%
49293
2.092
1.91
67.08
94.14
74.705
95.88
0.86
74.30%
59246
2.095
1.80
51.25
94.79
60.69
96.39
0.87
74.31%
59634
FT reactor volume is
the bottleneck
M. Panahi ’Plantwide Control for Economically Optimal Operation of Chemical Plants’
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Individual measurements (mode II)
worst-case loss for the best 5 individual measurement sets
no.
Loss
(USD/hr)
Sets
1
y3:CO2
recovery
y2: H2O/C
y7: H2/CO
into FT reactor
3022
2
y3:CO2
recovery
y2: H2O/C
y6: H2/CO
in tail gas
3316
3
y3:CO2
recovery
y2: H2O/C
y5: H2/CO
in fresh syngas
3495
4
y3:CO2
recovery
y2: H2O/C
y17: tail gas
flowrate to
syngas unit
4179
5
y3:CO2
recovery
y9: CO mole
fraction
in fresh syngas
y15: CO mole
fraction
into FT reactor
4419
M. Panahi ’Plantwide Control for Economically Optimal Operation of Chemical Plants’
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Control structure for mode II of operation with proposed CVs
and possible pairings with MVs (red lines are by-pass streams)
PC
RC
SP=30 bar
SP (splitter ratio)
Tail Gas
Compressor I
TC
SP=455°C
TC
SP=200°C
CO2
Removal
Natural Gas
Autothermal
CO2
Self-optimizing CV2
Reformer
SP (CO2 recovery%)=
76.04
(ATR)
CC
Oxygen(from ASU)
flowrate is at max.
SP=38°C
Fired
Heater
Pre-Reformer
Steam
Natural Gas (fuel)
SP=675°C
TC
Water
SP=12.5bar
HP Saturated
Steam
RC
PC
MP Steam
FT
Reactor
V-1
∆P=f(Q)
Heater
SP=3% purge
Vapor
Water
TC
Steam Drum
SP=210°C
Syngas
TC
Compressor II
Recycle Tail
gas to FT
TC
SP (H2O/C=0.4084)
SP=455°C
PC
SP (H2/CO)=1.8
SP=1030°C
Self-optimizing CV1
CC
CC
SP=27bar
Liquid
Light Purge to fired
Ends heater (as fuel)
Liquid fuels
to upgrading
unit
3-Phase
Separator
Separator
TC
Self-optimizing CV3
SP=30°C
TC
Water
Water
Extra
Steam
To fired heater (not shown)
to produce superheat steam
Superheated
Steam
ASU
Turbines
M. Panahi ’Plantwide Control for Economically Optimal Operation of Chemical Plants’
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Concluding remarks of self-optimizing application for
GTL process
• Self-optimizing method was applied for selection of the CVs for GTL
• There are 3 unconstrained DOFs in both modes of operation
• One common set in the list of the best individual measurements in two
modes:
CO2 recovery
H2/CO in fresh syngas
H2O/C setpoint reduces from 0.6 to o.4
• Operation in Snowballing region should be avoided
• Saturation point of oxygen plant capacity is recommended for operation in
practice
M. Panahi ’Plantwide Control for Economically Optimal Operation of Chemical Plants’
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Outline
 Ch.2 Introduction
 Ch.4 Economically optimal operation of CO2
capturing process; selection of controlled variables
 Ch.5 Economically optimal operation of CO2
capturing process; design control layers
 Ch.6 Modeling and optimization of natural gas to
liquids (GTL) process
 Ch.7 Self-optimizing method for selection of
controlled variables for GTL process
 Ch.8 Conclusions and future works
M. Panahi ’Plantwide Control for Economically Optimal Operation of Chemical Plants’
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Conclusions and future works
Systematic plantwide procedure of Skogestad was applied for a post-combustion
CO2 capturing process; a simple control configuration was achieved, which works
close to optimum in the entire throughput range without the need for switching the
control loops or re-optimization of the process
A GTL process model suitable for optimal operation studies was modeled and
optimized. This model describes properly dependencies of important parameters
in this process
Self-optimizing method was applied to select the right measurements for the GTL
process in two modes of operation
UniSim/Hysys linked with MATLAB showed to be a very good tool for optimal
operation studies
M. Panahi ’Plantwide Control for Economically Optimal Operation of Chemical Plants’
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Conclusions and future works
Implementation of the final control structure for CO2 capture plant is recommended
for implementation in practice
Dynamic simulation of the GTL process should be done to validate the proposed
control structures
The application of plantwide control procedure is strongly recommended for other
newer energy-intensive processes
Developing a systematic method for arriving at a simple/single control structure,
which works close to optimum in all operational regions can be a good topic for
future work
Thank you for your attention!
M. Panahi ’Plantwide Control for Economically Optimal Operation of Chemical Plants’
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