Transcript Refinery Operations Planning

REFINERY OPERATIONS
PLANNING
Dunham, Luhila, Odunuga
Overview





Refinery Overview
Production Planning
Linear model with complex and simplified utilities
Results
Conclusions
Model Refinery: Bangchak Refinery
(Thailand)
FG
LPG
LN
ISO
ISOU
MTBET
LN
DCCT
NPU
CDU2
GASOLINE
POOL
OM
HN
CRU
TP
ISOG
REF
HN
SUPG
LB
SLEB
HDS
IHSD
DIESEL
POOL
PHET
HSD
Kero
MB
CDU3
Kero
KTU
JP1
FO1
Kero
FO
FG
Kero
DO
Intermediates
LPG
Naphtha
FO
Products
Crudes
FO2
FOVS
What is Refinery Operations Planning?
How much crude should be purchased?

What kind/quality of crude should be purchased?

How much does the refinery want to produce?

Consists of crude oil unloading, production planning
and distribution

Problems in Refinery Operations



Uncertainty in prices and demand
Effects of uncertainty are minimized by using
models
Historically, models have been linear
 Use
of average operating conditions
 Linear models are non-ideal

Currently
Non-linear models are ideal
 Linear Model with Complex Utilities

X
P.planning, inventory mgt, shipment
X
X
Coordination of feedstock & pdt with
markets
X
X
Uncertainty
X
X
Decomposition Strategy
Zhang et al
2001
X
Lee et al.
1996
NLP
Pongsakdi et al
2006
X
Glismann et al.
2001
Moro et al.
2004
X
Financial risk
Gathe-Lundgen et al.
2002
Shah N
1996
Crude oil distillation and blending
Features of Current Models
X
X
X
X
X
X
X
Production Planning


Production Planning
 Processing of crude oil
through different units
Decisions
 Crude oil



Purchase
Processing
Inventory management
Bangchak
Refinery
Production Planning


Routine process which guides purchasing
Departments
 Crude
oil acquisition, product sales & refinery
operations

Based on
 Market
demands and prices
 Uncertainty
Production Planning

Winter
 High
fuel oil demand
→ more fuel oil
produced

Summer
 High
demand for light
crudes → more
gasoline produced
Linear Modeling Method


Inside Unit is a black
box (inside box
doesn’t matter)
Input and output can
be related
CRU
F2
F1
Reactor
Feed
Light Ends
F3
Desulfurized
Product
Linear Modeling Method



Linear Equation
Relating Inputs and
Outputs:
F3 =α31*F1
What is α31?
It depends on the
system!
CRU
F2
F1
Reactor
Feed
Light Ends
F3
Desulfurized
Product
Finding Alpha (α)



Really, αij is the result of solving an ODE
Example: Concentration of Aromatics leaving a CRU
dCAro
 rAro  k Aro * C Aro * C H 2
dW
Thus αij will depend on
 Inlet
concentrations and flows
 Process parameters: Temperature, Pressure
Hydrotreating

Process to remove impurities in the stream
 Aromatics
Sulfur



Nitrogen
Hydrotreating for sulfur → hydrosulfurization
Reduces the aromatic content in crudes
Hydrogenation
Hydrotreating PFD
Hydrotreating Model

Operating Conditions
 Reactor
Temperatures range from 250°F – 550°F
 Main Variables
 Pressure
 Temperature
 Velocity
 H2/HC
ratio
KTU Aromatics Flow Rate
Far  f o  W * rar
ƒo = Initial Flow Rate
Arom atic_ weight
1.1E  08
W

 5.50E  5
m olecular_ weight _ oil
200
Hydrotreating Empirical Model
Aromatics:
rar  LHSV * Car * Ch
m3
LHSV  2.66
hr
Car
 P * 1 0 0 0


R *T



f Total
 P *1000 885000
Ch  
*
 R * T  fTotal
KTU Equation Comparison

Linear Equation: Far =α1*Ftotal

Actual Equation:
 1000* P 


R * T   1000* P   885000


Far  f o  W * LHSV *
*
 * 
Ftotal
 R * T   Ftotal 
Non linearity
0.45

C
h
rs  k s * 60*  Cs *

1  K H 2 S * CH 2 S


  132000
ks  4.27 10 exp

 R *T 

9
 P *1000
Cs  
 * (1242.5 * f ) * Mw / f 
 R *T 


2

CH 2 S
  P *1000  88500  
 
  
 * 
  R * T   f *100000 
  P *1000  88500  
 
Ch   
 * 
  R * T   f *100000 
K H 2 S  41770 e
2761
RT
0.45
Catalytic Reforming


Process of increasing octane number of NPU by
converting napthenes & paraffins
Outputs
 Aromatics,

light hydrocarbons (C1-C5) & hydrogen
Operating conditions
Variables
Range
Temperature °F
900 – 950
Pressure (atm)
30 – 40
Catalytic Reformer PFD
CRU -Empirical Kinetic Model
Conversion of napthenes to aromatics




Amount of product X1 Produced
Reaction Rate
Kinetic Reaction Constant
Equilibrium Constant
 W
 r1 
 FT

  X 1

3


P
*
P
A
H

 r1  k p1  PN 


K
p1


34750

k p1  exp 23.21 

T 

PA * PH3
46045

K p1 
 exp 46.15 

PN
T 

Reformer Temperature Modeling
Reactor 1
Mass Flow Rate (lb/hr)
-112
0
-114
Delta T (R)
-116
-118
-120
-122
-124
-126
-128
-130
5,000
10,000
15,000
20,000
25,000
30,000
35,000
Process Industry Modeling Systems
PIMS



Allows user to analyze results
graphically and to adjust
variables
Adds capabilities for global
optimization, solution ranging,
and goal programming
Requires refinery-specific
inputs to determine an
acceptable starting point
PIMS and Non-linearities

Benefits
 Identifies
the solution that maximizes global
profitability
 Validates
solution and enhances planners’ confidence
and gives an estimate on how close results are to
optimal solution
 Eliminates
solutions
need to manually search for improved
PIMS and Non-linearities




SLP is the primary non-linear modeling feature
Flexibility in the types of equations that can be
used in models
Builds derivatives which eliminates potential errors
Non-linear terms can reference existing Aspen PIMs
variables or define new variables
PIMS Modeling


PIMS finds
maximum by
calculating
objective function
gradient
Maximum found
by PIMS depends
on initial condition
100
90
80
70
60
50
40
30
20
10
0
Objective…
Max 2
X
Max 1
X
x
x
0
20
Start 1
40
Start 2
60
Alternative Method
Linear Model with Utilities
Model Super tables
Product flow of Paraffins
Product flow of Paraffins
(psi)
Pressure
(F)
Temp.
Concentration Flow Rate
0.31
15500
0.31
16000
0.31
16500
0.31
17000
0.31
17500
0.31
18000
0.31
18500
0.31
19000
0.31
19500
0.31
20000
400
800
400
820
400
840
2547.928
2630.119
2712.31
2794.502
2876.693
2958.884
3041.075
3123.266
3205.458
3287.649
2547.928
2630.119
2712.31
2794.502
2876.693
2958.884
3041.075
3123.266
3205.458
3287.649
2547.928
2630.119
2712.31
2794.502
2876.693
2958.884
3041.075
3123.266
3205.458
3287.649
X=f(C,T,P,F)
Conc = 0.31
Temp = 800 F
Pressure = 400 psi
Flowrate = 16000 m3/day
X= 2630 bbl/hr
Model Super tables
Product flow of Paraffins
(psi)
Pressure
400
400
400
400
400
400
400
400
400
400
450
450
450
450
450
450
450
450
450
450
500
500
500
500
(F)
Temp.
800
820
840
860
880
900
920
940
960
980
800
820
840
860
880
900
920
940
960
980
800
820
840
860
Concentration Flow Rate
0.31
15500 2571.22 2596.69 2647.74 2747.85 2940.15 3302.30 3971.58 5186.33 7353.35 11155.62 2577.40 2609.65 2674.26 2800.97 3044.36 3502.73 4349.85 5887.40
8630.25 13442.95 2584.32 2624.13 2703.90 2860.34
0.31
16000 2653.41 2678.88 2729.93 2830.04 3022.34 3384.49 4053.77 5268.52 7435.54 11237.81 2659.59 2691.84 2756.45 2883.16 3126.55 3584.92 4432.04 5969.59
8712.44 13525.14 2666.51 2706.32 2786.09 2942.53
0.31
16500 2735.60 2761.07 2812.13 2912.24 3104.53 3466.68 4135.96 5350.72 7517.73 11320.01 2741.79 2774.03 2838.65 2965.35 3208.74 3667.12 4514.24 6051.78
8794.64 13607.33 2748.70 2788.51 2868.28 3024.72
0.31
17000 2817.79 2843.27 2894.32 2994.43 3186.72 3548.87 4218.15 5432.91 7599.92 11402.20 2823.98 2856.22 2920.84 3047.54 3290.93 3749.31 4596.43 6133.97
8876.83 13689.52 2830.89 2870.70 2950.48 3106.91
0.31
17500 2899.98 2925.46 2976.51 3076.62 3268.91 3631.06 4300.34 5515.10 7682.11 11484.39 2906.17 2938.41 3003.03 3129.74 3373.12 3831.50 4678.62 6216.16
8959.02 13771.71 2913.08 2952.89 3032.67 3189.10
0.31
18000 2982.17 3007.65 3058.70 3158.81 3351.10 3713.25 4382.53 5597.29 7764.30 11566.58 2988.36 3020.60 3085.22 3211.93 3455.31 3913.69 4760.81 6298.35
9041.21 13853.90 2995.27 3035.08 3114.86 3271.29
0.31
18500 3064.36 3089.84 3140.89 3241.00 3433.30 3795.44 4464.73 5679.48 7846.49 11648.77 3070.55 3102.80 3167.41 3294.12 3537.51 3995.88 4843.00 6380.54
9123.40 13936.09 3077.46 3117.27 3197.05 3353.48
0.31
19000 3146.55 3172.03 3223.08 3323.19 3515.49 3877.64 4546.92 5761.67 7928.69 11730.96 3152.74 3184.99 3249.60 3376.31 3619.70 4078.07 4925.19 6462.74
9205.59 14018.29 3159.66 3199.47 3279.24 3435.68
0.31
19500 3228.75 3254.22 3305.27 3405.38 3597.68 3959.83 4629.11 5843.86 8010.88 11813.15 3234.93 3267.18 3331.79 3458.50 3701.89 4160.26 5007.38 6544.93
9287.78 14100.48 3241.85 3281.66 3361.43 3517.87
0.31
20000 3310.94 3336.41 3387.46 3487.57 3679.87 4042.02 4711.30 5926.05 8093.07 11895.34 3317.12 3349.37 3413.98 3540.69 3784.08 4242.45 5089.57 6627.12
9369.97 14182.67 3324.04 3363.85 3443.62 3600.06
0.31
20500 3393.13 3418.60 3469.66 3569.77 3762.06 4124.21 4793.49 6008.25 8175.26 11977.54 3399.31 3431.56 3496.17 3622.88 3866.27 4324.65 5171.77 6709.31
9452.17 14264.86 3406.23 3446.04 3525.81 3682.25
0.33
15500 2735.60 2761.07 2812.13 2912.24 3104.53 3466.68 4135.96 5350.72 7517.73 11320.01 2741.79 2774.03 2838.65 2965.35 3208.74 3667.12 4514.24 6051.78
8794.64 13607.33 2748.70 2788.51 2868.28 3024.72
0.33
16000 2823.09 2848.57 2899.62 2999.73 3192.02 3554.17 4223.45 5438.21 7605.22 11407.50 2829.28 2861.52 2926.14 3052.85 3296.23 3754.61 4601.73 6139.27
8882.13 13694.82 2836.19 2876.00 2955.78 3112.21
0.33
16500 2910.59 2936.06 2987.11 3087.22 3279.52 3641.67 4310.95 5525.70 7692.72 11494.99 2916.77 2949.02 3013.63 3140.34 3383.73 3842.10 4689.22 6226.77
8969.62 13782.32 2923.69 2963.50 3043.27 3199.71
0.33
17000 2998.08 3023.56 3074.61 3174.72 3367.01 3729.16 4398.44 5613.20 7780.21 11582.49 3004.27 3036.51 3101.13 3227.83 3471.22 3929.60 4776.72 6314.26
9057.12 13869.81 3011.18 3050.99 3130.77 3287.20
0.33
17500 3085.57 3111.05 3162.10 3262.21 3454.51 3816.65 4485.94 5700.69 7867.70 11669.98 3091.76 3124.01 3188.62 3315.33 3558.72 4017.09 4864.21 6401.75
9144.61 13957.31 3098.68 3138.49 3218.26 3374.70
0.33
18000 3173.07 3198.54 3249.60 3349.70 3542.00 3904.15 4573.43 5788.19 7955.20 11757.48 3179.25 3211.50 3276.11 3402.82 3646.21 4104.58 4951.70 6489.25
9232.11 14044.80 3186.17 3225.98 3305.75 3462.19
0.33
18500 3260.56 3286.04 3337.09 3437.20 3629.49 3991.64 4660.92 5875.68 8042.69 11844.97 3266.75 3298.99 3363.61 3490.32 3733.70 4192.08 5039.20 6576.74
9319.60 14132.29 3273.66 3313.47 3393.25 3549.68
0.33
19000 3348.06 3373.53 3424.58 3524.69 3716.99 4079.14 4748.42 5963.17 8130.19 11932.46 3354.24 3386.49 3451.10 3577.81 3821.20 4279.57 5126.69 6664.24
9407.09 14219.79 3361.16 3400.97 3480.74 3637.18
0.33
19500 3435.55 3461.03 3512.08 3612.19 3804.48 4166.63 4835.91 6050.67 8217.68 12019.96 3441.74 3473.98 3538.60 3665.30 3908.69 4367.07 5214.19 6751.73
9494.59 14307.28 3448.65 3488.46 3568.24 3724.67
0.33
20000 3523.04 3548.52 3599.57 3699.68 3891.98 4254.12 4923.41 6138.16 8305.17 12107.45 3529.23 3561.48 3626.09 3752.80 3996.19 4454.56 5301.68 6839.22
9582.08 14394.77 3536.14 3575.95 3655.73 3812.16
0.33
20500 3610.54 3636.01 3687.06 3787.17 3979.47 4341.62 5010.90 6225.65 8392.67 12194.94 3616.72 3648.97 3713.58 3840.29 4083.68 4542.05 5389.17 6926.72
9669.57 14482.27 3623.64 3663.45 3743.22 3899.66
0.35
15500 2899.98 2925.46 2976.51 3076.62 3268.91 3631.06 4300.34 5515.10 7682.11 11484.39 2906.17 2938.41 3003.03 3129.74 3373.12 3831.50 4678.62 6216.16
8959.02 13771.71 2913.08 2952.89 3032.67 3189.10
0.35
16000 2992.78 3018.25 3069.30 3169.41 3361.71 3723.86 4393.14 5607.89 7774.91 11577.18 2998.96 3031.21 3095.82 3222.53 3465.92 3924.29 4771.41 6308.96
9051.81 13864.51 3005.88 3045.69 3125.46 3281.90
0.35
16500 3085.57 3111.05 3162.10 3262.21 3454.51 3816.65 4485.94 5700.69 7867.70 11669.98 3091.76 3124.01 3188.62 3315.33 3558.72 4017.09 4864.21 6401.75
9144.61 13957.31 3098.68 3138.49 3218.26 3374.70
0.35
17000 3178.37 3203.85 3254.90 3355.01 3547.30 3909.45 4578.73 5793.49 7960.50 11762.78 3184.56 3216.80 3281.42 3408.13 3651.51 4109.89 4957.01 6494.55
9237.41 14050.10 3191.47 3231.28 3311.06 3467.49
0.35
17500 3271.17 3296.64 3347.69 3447.80 3640.10 4002.25 4671.53 5886.28 8053.30 11855.57 3277.35 3309.60 3374.21 3500.92 3744.31 4202.68 5049.80 6587.35
9330.20 14142.90 3284.27 3324.08 3403.85 3560.29
0.35
18000 3363.96 3389.44 3440.49 3540.60 3732.90 4095.04 4764.33 5979.08 8146.09 11948.37 3370.15 3402.40 3467.01 3593.72 3837.11 4295.48 5142.60 6680.14
9423.00 14235.70 3377.07 3416.88 3496.65 3653.09
0.35
18500 3456.76 3482.24 3533.29 3633.40 3825.69 4187.84 4857.12 6071.88 8238.89 12041.17 3462.95 3495.19 3559.81 3686.51 3929.90 4388.28 5235.40 6772.94
9515.80 14328.49 3469.86 3509.67 3589.45 3745.88
0.35
19000 3549.56 3575.03 3626.08 3726.19 3918.49 4280.64 4949.92 6164.67 8331.69 12133.96 3555.74 3587.99 3652.60 3779.31 4022.70 4481.07 5328.19 6865.74
9608.59 14421.29 3562.66 3602.47 3682.24 3838.68
0.35
19500 3642.35 3667.83 3718.88 3818.99 4011.28 4373.43 5042.72 6257.47 8424.48 12226.76 3648.54 3680.78 3745.40 3872.11 4115.50 4573.87 5420.99 6958.53
9701.39 14514.08 3655.45 3695.26 3775.04 3931.47
0.35
20000 3735.15 3760.63 3811.68 3911.79 4104.08 4466.23 5135.51 6350.27 8517.28 12319.56 3741.34 3773.58 3838.20 3964.90 4208.29 4666.67 5513.79 7051.33
9794.19 14606.88 3748.25 3788.06 3867.84 4024.27
0.35
20500 3827.95 3853.42 3904.47 4004.58 4196.88 4559.03 5228.31 6443.06 8610.08 12412.35 3834.13 3866.38 3930.99 4057.70 4301.09 4759.46 5606.58 7144.13
9886.98 14699.68 3841.05 3880.86 3960.63 4117.07
Linear Model with Utilities

Our model finds
the maximum by
testing many
discrete points
100
Objective Function
90
80
70
60
50
40
30
20

Optimum value
will be close to
the global
optimum
10
0
0
10
20
30
40
50
60
GAMS Software


Algebraic modeling
interface capable of
solving linear and
mixed integer models
Non-linear equations
cause problems
Comparison
Linear Model (in GAMS)



Linear or Mixed
Integer Programming
Discretizes continuous
values
Always finds best test
point (near global
maximum)
PIMS



Successive Linear
Programming
Uses gradient of
objective function
May find local
maximum (depends on
starting point)
Utility Calculations



Steam and Power are produced within the refinery
Steam is produced by fired steam boilers, which
burn refinery fuel gas and fuel oils to create steam
Electricity is produced by running high pressure
steam through a turbine
Utility Table Equations

Water Cost (Heat exchangers)


$
 
lb
coolers 
 m p  Cp p  Tp
TW  Cpw

$
 
lb
condensers  
Unit Fuel Gas Consumption (Heaters)

 p  Cp p  T
m
H fg

m  vap
Tw  Cpw
Utility Equations in GAMS
Results
Linear Model Development
LP Model
(Individual
Units)
CRU Reactor
Temperature
Isothermal
NonIsothermal
Utilities
No Utilities
Simplified
Utilities
Complex
Utilities
Utility Models
Linear Model with Complex Utilities:
 Uses tables to coordinate output values with
functions of Temperature, Pressure, and Flow rate
Linear Model with Simplified Utilities:
 Assumes Temperature and Pressure to be the
average of operating conditions
Linear Model without Utilities:
 Does not calculate utility cost
Results - Gross Refinery Margin
Model
GRM
Linear Model with Complex Utilities
$34,103,151
Linear Model with Simplified Utilities
$31,168,455
Results - Total Utility Cost
Model
Utility Cost
Linear Model with Complex Utilities
$2,980,761
Linear Model with Simplified Utilities
$3,411,319
Purchasing Recommendations
Linear Model with Simplified Utilities
Linear Model with Complex Utilities
Crude Purchasing Recommendations
(m3/day)
Crude Purchasing Recommendations
(m3/day)
Month
Month
1
2
1
3
2
3
OM
244486 262303 267899
OM
250361
265445
267700
TP
32853
41126
47392
TP
35313
42245
43073
LB
0
0
9041
LB
0
0
12997
SLEB
95392
95392
95392
SLEB
95392
95392
95392
PHET
57235
57235
57235
PHET
57235
57235
57235
MB
95392
95392
95392
MB
95392
95392
95392
Unit Operating Conditions
No Utility Model
Month:
1
2
3
Complex Utility Model
1
NPU2
Temperature
Pressure
600
600
600
600
700
600
600
600
600
600
700
680
N/A
N/A
700
680
700
680
275
1.9
980
850
275
1.9
275
2
980
500
700
680
700
680
275
2.1
275
2.1
980
850
980
400
980
600
980
750
CRU2
980
850
980
800
980
850
CRU3
Temperature
Pressure
600
600
ISOU
CRU2
Temperature
Pressure
600
600
NPU3
ISOU
Temperature
Pressure
3
NPU2
NPU3
Temperature
Pressure
2
CRU3
980
800
980
550
980
400
Discussion
Catalytic Reforming Unit
Isothermal Model



Reactors are
isothermal
All reactor
temperatures are the
same
Produces more Fuel
Gas
Varying Temperature Model




Each reactor operates
at a different
temperature
Temperature changes
in each reactor
Produces more
Hydrogen
Produces almost 50%
more Reformate
Hydrogen and Refinery Fuel Gas



Both utility models calculated a net production of
Hydrogen and Refinery Fuel Gas
Assume these are usable and can be transported
around the refinery where make-up is needed
Since excess is produced, no Hydrogen or RFG is
purchased
Conclusions
The Linear Model with Complex Utilities processes
more crude and gives a larger GRM than a model
with Simplified Utilities and a model with no utility
cost calculation
The Non-isothermal CRU model produces more
reformate and increases overall GRM
Linear models in GAMS always find a value close to
the global optimum, where PIMS may find only a
local optimum depending on starting point
Questions?