Optimization

OPTIMIZATION OF CATALYTIC REFORMERSOPTIMIZATION OF CATALYTIC REFORMERS

Introduction

Types of Process Variables

Effect of Operating Conditions

Reformer Optimization

Case Studies

INTRODUCTIONINTRODUCTION

Catalyst Reformer is used to produce high-octane gasoline and aromatics

from naphtha.

It is a major refinery unit

1. worldwide capacity 8.7 MBBLD (1990) is close to that of FCC

2. Reformate contributes upto 30% in the gasoline pool and is the most

important octane boosting stream.

3. Major source of BTX (32% of world’s benezene)

Designing/Revamping/Operating this unit in optimum manners can have a

significant impact on refinery margin

Catalytic reformers are designed to operate under flexible operating conditions

subject to various constraints. Optimization of operating conditions can boost the unit’s economy

significantly (upto ~110%)

TYPES OF PROCESS VARIABLESTYPES OF PROCESS VARIABLES

What to optimize? (output variables)

1. Daily/Annual operating profit

2. Yield/Production Rate of

a) Reformate

b) BTX (Benzene, Toluene & Xylenes) in reformate

c) H2

3. Reformate quality

a) RON0/MON0 (unleaded research/motor octane no.)

b) RVP (Reid vapor pressure)

c) Benzene/Aromatic content

4. Residual cycle length or catalyst activity


What can be manipulated? (input variables)

1. Feed rate

3. Reactor inlet temperatures

4. Reactor / Separator pressure

5. H2/HC (hydrogen-to-hydrocarbon) ratio or recycle rate

6. Amount of cracked naphtha (that can be mixed with virgin naphtha)

7. Cl2/H2O (chlorine/moisture) dosing rate

Hardware / Equipment constraints.

1. Reactor configuration - SR/CYCLIC/CCR (semi-regenerative / cyclic /

continuous catalyst circulation)

2. Catalyst type, loading and distribution

3. No. of reactors, feed/effluent heat exchanger type or area

4. Maximum RGC (recycle gas compressor) power

5. Maximum CHE/IHE (charge/inter heater) duties


Inputs constraints.

1. Feed rate

2. Recycle rate (or, H2/HC ratio)

3. Separator/Reactor pressure

4. Reactor inlet temperatures

Outputs constraints.

1. Minimum RON0

2. Minimum cycle length

Causes of process upsets or change in operating conditions.

1. Change in naphtha quality

a) IBP & FBP, or hydrocarbon compositions ( e.g., N+2A)

2. Change in operating objectives


Daily Operating Margin (Rs/day) = (product –feed) value – operating cost

Product value = (hydrogen + fuel gas + LPG) value

+ (benzene-toluene-xylene / reformate value)

Operating cost = (compressors’ power + charge and inter heater duty) cost

+ cycle length penalty

Octane No. (RON0 / MON0) -

Resistance to knocking (rumbling sound of uncontrolled ignition) that reduces

fuel efficiency.

RON0 is measured as percent of i-octane in n-heptane that has same knocking as

the unleaded fuel under standard experimental conditions.

MON0 is same as RON0 but measured under higher compression ratio.

amount

quality

specification

TYPES OF PROCESS VARIABLESTYPES OF PROCESS VARIABLESReformate Quality Specifications

RON0 – Current gasoline RON0 specification is 87-91.

It will be raised to 91-95 beyond 2005.

Since reformate has highest RON0 in gasoline pool, its RON0 should be much

higher than specified.

RVP – Vapor pressure measured under standard condition.

Specification for gasoline is 35-100 Kpa.

Reformate RVP should be lower than this to allow blending of lighter

streams (e.g., light naphtha) into the gasoline pool.

Benzene – Carcinogenic and toxic.

Content Gasoline specification of 3-5 lv% (1-2 beyond 2005).

Aromatic – Toxic and produces smog.

Content Gasoline specification 40-45 lv% (<35 beyond 2005).

TYPES OF PROCESS VARIABLESTYPES OF PROCESS VARIABLESFeedstock quality

1. N+2A (naphthenic plus twice aromatics LV%) measured via PONA analysis.

2. Feed Composition measured in terms of carbon no. (e.g., C6, C7, C8, C9+) for

each major groups of hydrocarbons (e.g., paraffin, naphthene and aromatic)

via Gas Chromatograph (GC) or ASTM/TBP curve.

3. IBP / FBP (initial / final boiling point).

4. Mixing with cracked naphtha from FCC / Coker units.

5. presence of catalyst poisons.

Empirical charts are often used to determine the necessary operating conditions.

Model based simulation and optimization can provide the best answer.


Feedstock quality (Empirical Charts)

70

75

80

85

90

95

90 91 92 93 94 95 96 97 98 99 100

RON0

C5

+ R

efo

rma

te Y

ield

(v

ol.%

)

N+2A = 40

N+2A = 60

N+2A = 80

EFFECT OF OPERATING CONDITIONSEFFECT OF OPERATING CONDITIONS

Reforming – 1. Naphthene dehydrogenation: NH A + nH2

Reactions 2. Isomerization: n-P i-P, NP-CH3 NH

3. Hydrocracking: P7 P4 + P3, P7 P6 + CH4

4. Dehydrocyclization: P A + nH2

(P = Paraffin, NP = Cyclopentanes, NH = Cyclohexanes, A = Aromatic)

Reaction Relative Rate

of Reaction

Heat of Reaction,

cal/mole

Naphthene

Dehydrogenation

100+ > 50000

Isomerization 12 -1000 to –4000

Hydrocracking 4 -12000 to –15000

Dehydrocyclization 1 49000 to 64000

EFFECT OF FEED RATEEFFECT OF FEED RATE

For a particular feed, product yields and qualities depend on the ratio of feed rate to catalyst loading.

LHSV is the volumetric ratio of feed rate (at 60oF & 1 atm) to catalyst loading.

- Not a true residence time.

- Varies between 1-2 hr.-1

WHSV is the mass ratio of feed rate to catalyst loading.

Lower LHSV/WHSV Greater severity Greater reaction conversions including hydrocracking of paraffins and

coking (and vice versa).

EFFECT OF FEED RATEEFFECT OF FEED RATE

90

94

98R

ON

0 WAIT = 518oC

-17

-13

-9

-5

-1

101214161820

LHSV (hr.-1) * 10

WA

IT (o

C) RON0 = 95

Base WAIT = 512oC

EFFECT OF REACTOR TEMPERATUREEFFECT OF REACTOR TEMPERATURE Reaction temperature must be kept high enough (> 460oC, normally 480oC) to

allow high equilibrium conversion of naphthenes and paraffins to aromatics, the

reactions being highly endothermic in nature . Differential (gradually increasing) catalyst loading and inter-heaters.

However, reaction temperature must not be too high (< 525oC, normally 510oC) so

that elevated kinetic rates of hydrocracking and coke formation sharply reduces the

reformate yield and catalyst activity.

Fine control of reactors’ inlet temperature profile is essential to compensate for

changes in feedstock quality and catalyst activity.

WAIT, WABT = Average inlet and bed temperature respectively, averaged w.r.t.

reactor-wise catalyst distribution.

Higher WAIT/WABT Greater severity Greater reaction conversions including hydrocracking of paraffins and coking

(and vice versa).

EFFECT OF REACTOR TEMPERATUREEFFECT OF REACTOR TEMPERATURE

85

90

95

100

485 490 495 500 505 510 515 520

WAIT (oC)

RO

N0

EFFECT OF SEVERITYEFFECT OF SEVERITY

RON0

93

99

C5+ Yield

85

78

RON0

92

100

H2, SCFB

630

790

RON0

92

100

Reformate RVP, psi

3.4

4.2

RON0

92

100

Reformate Benzene, LV%

2.1

2.8

RON0

90

100

Relative Cycle Length (21.4 atm)

1.0

0.2

Effects of Change in Reactor Severity (LHSV or WAIT)

EFFECT OF REACTOR PRESSUREEFFECT OF REACTOR PRESSURE Lowering of pressure increases equilibrium conversions in dehydrogenation and

dehydrocyclization reactions that involves a net increase in total moles .

Lowering of pressure also reduces H2 partial pressure and this in turn decreases the

hydrocracking of paraffins.

Lowering of pressure, however, increases coking (i.e., catalyst deactivation).

The reported reactor pressures (e.g., 15-22 & 4-7 atm for SR & CCR respectively)

are average values taking into account the pressure drops (e.g., 0.14-0.27 or 0.34-0.68

atm for each of the radial or axial reactors with fresh catalyst).

Lower reactor pressure Greater RON0 Greater C5+ yield Greater H2 production Lower benzene conc. Lower RVP Greater coking (decreasing catalyst activity)

(and vice versa).

EFFECT OF REACTOR PRESSUREEFFECT OF REACTOR PRESSURE

76

78

80

82

84

86

88

90

90 92 94 96 98 100 102

RON0

C5

+ Y

ield

21.4 atm

14.6 atm

7.8 atm

EFFECT OF REACTOR PRESSUREEFFECT OF REACTOR PRESSURE

Pressure, atm

4.4

14.8

21.4

H2 Production, SCFB

1700

900

750

Pressure, atm

4.4

21.4

Reformate Benzene conc., LV%

0.4

1.2

Pressure, atm

4.4

21.4

Reformate RVP, atm

2.3

3.8

Pressure, atm

11.2

21.4

Relative cycle length (RON0 = 90)

0.4

1.0

Effects of Change in Reactor Pressure

EFFECT OF H2/HC RATIOEFFECT OF H2/HC RATIO

Defined as moles of H2 in recycle to the total HC (hydrocarbon) moles in reactor

charge (excludes ~20% HC in recycle), normal ranges being 2 to 5.

Lower H2/HC Lower recycle rate Lower energy cost Favors dehydrogenation reactions Increases Coking (decreasing catalyst activity)

(and vice versa).

REFORMER OPTIMIZATIONREFORMER OPTIMIZATION

Best Operating Conditions ?

Feedstock’s Quality Operating Objective

Reformer Input / Output

Constraints

Hardware

Limits

Disturbances Changes


Maximizing the daily operating margin out of reformer unit.

Coping with fluctuating demands of products, like, BTX and gasoline.

Meeting stringent product quality specifications like RON0, benzene/aromatic

content and RVP of reformate.

Minimize catalyst deactivation and hence increase the cycle length.

Any combination of above objectives.

Objectives of Reformer Optimization

Why We Want to Optimize Reformer Operation?

Finding an operating point that will more closely meet the objective of

reformer operation than the current operating point.


Profit may be defined in terms of multiple output variables (e.g., throughputs,

product qualities).

There are multiple input variable, each of which influences all the output variables

although not to the same extent.

There are hardware/equipment bounds, physical limits of input variables,

tolerable range of output variables.

Constrained, Multi-Variable & Nonlinear Optimization

Issues in Reformer Optimization


PID Type Controllers

(Feed Flow Control, Fuel Gas Flow Control,

Recycle Gas Pressure/Flow Control, etc.)

Advanced Process Controllers

(Production Maximization, Octane Control,

H2/HC Control, etc.)

On-Line Optimization

Off-Line Optimization

Frequency

Each 8-24 hr.

(major changes and

disturbances)

Each 8-12 hr.

(major changes and

disturbances)

Each 1-5 min.

(larger disturbances)

Each 1-20 sec.

(random disturbances)

Typical Benefits

}10% more

$0.6-1.0 / m3

____


Off-Line / On-Line

Optimizer

Process Model / Constraints

Data Reconciliation

Data Filtering

Model Updating

Reformer Plant

Parameters

Inputs &

Parameters

Inputs &

Parameters

Outputs

I/O Data

Constraints


Use Data when it appears that the process has reached a steady state

Standard deviations of feed and product flowrates should be below a limit.

Eliminate outliers in all data

Data values to be restricted within the maximum expected standard deviation.

Average out all data over a fixed period (usually, 2 hr.)

Eliminate small random fluctuations in the data.

Examine the crucial data like recycle gas compositions, feed and reformate

compositions based on their expected ranges Amount of components in the recycle gas should fall exponentially with

increase in carbon number. Benzene / Toluene yields are normally more than higher aromatics. Component wise yield values should be within their expected range.

Data Filtering


Eliminate data with gross error (instrument biases and process faults) using a

rigorous statistical methods like GLR (Generalized Likelihood Ratio) method.

Data Reconciliation

Reconcile or adjust data to satisfy material balances (like, total and

carbon / hydrogen balances).

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Data-driven model: Pre-defined model structure Can be fitted very quickly, provided necessary data are available Require huge amount of data, including feed/product component distributions

(i.e., not just on-line sensor data) collected at various times Existing plant data base in refineries may cover very narrow operating range Collecting more useful data by plant perturbations may not be allowed Collecting more useful data through pilot plant is costly Need to be updated continuously.

Fundamental model: Can be fitted very quickly with just 2/3 data sets collected at various times Need update, but less frequently Arriving at the proper model structure is difficult.

Data-Driven vs. Fundamental Models


Rigorous dynamic model is difficult to solve, steady state model is normally used.

Major reforming reactions are Naphthene Dehydrogenation, Isomerization,

Hydrocracking, Dehydrocyclization (details were shown in a previous slide)

Apart from the usual frequency factor and activation energy, kinetic rate

expression may also include:

- Equilibrium constant to express reversibility of reactions

- Acid/Metal adsorption terms

- Catalyst activity rigorously calculated via a deactivation model

Model equations include mass and energy balances for reactor, F/E exchanger and

product separation system.

Calculation of recycle gas KW, reformate qualities, residual cycle length, daily

operating profit, etc.

Fundamental Models


Needed if model predictions differ from plant data.

Fundamental model parameters remain same as originally fitted.

Only a few lumped parameters are tuned to primarily match: Reactor-wise dehydrogenation and cracking rates Equilibrium constants used in VLE calculations.

Model Update

I/O Data and Process Constraints

Types of input / output data, hardware bounds, input limits and output constraints

were already discussed in a previous slide.


SLP (successive linear programming) and SQP (successive quadratic

programming) are normally used.

SQP is more efficient and faster in locating the optima anywhere in the feasible

region.

In SQP, coefficients of a QP objective is recalculated at each new iteration.

Optimizer

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REFORMER OPTIMIZATION CASE STUDIESREFORMER OPTIMIZATION CASE STUDIES

Optimization of a Commercial SR using CRESOP(a software licensed by EIL & IIP)

Base Case SimulationFeed Flow = 900 MT/day

Recycle Gas flow = 436.4 MT/day

No. of Reactors = 3

Catalyst Type = Bimetallic

Inlet Temperature of Successive Reactors = 498, 498, 498 oC

Pressure of Separator Drum = 17 bar

RGP HP = 2119.4 KW

CHT duty = 6.4 MMKcal/hr

1st IHT duty = 4.4 MMKcal/hr

2nd IHT duty = 2.0 MMKcal/hr

RON0 = 83.6

Cycle length = 8262.2 hr

Operating Margin = 2.50755425 x 106 Rs/day


Opr. Margin BTX Tonnage Maximization (X=920)

Maxm. Minm. Maximization Case A Case B (Y=3000)

Feed (MT/day) 900 (X) 850 900 904.7 (+4.7) 900

Recycle ( ” ) 440 400 440 (+3.6) 440 (+3.6) 440 (+3.6)

Sep. Press. (bar) 17 16 17 17 16.0 (-1.0)

1st Reac. in. oC 505 495 495 (-3) 495 (-3) 496.4 (-1.6)

2nd Reac. in. oC 505 495 495 (-3) 495 (-3) 495.8 (-2.2)

3rd Reac. in. oC 510 495 505 (+7) 504.4 (+6.4) 510 (+12)

RGP HP (KW) 2500 - 2105 (-94.4) 2122.3 (-77.1) 2146.7 (-52.7)

CHT MMKcal/hr 7 - 6.3 (-0.1) 6.3 (-0.1) 5.9 (-0.5)

1st IHT ” 5 - 4.3 (-0.1) 4.3 (-0.1) 4.3 (-0.1)

2nd IHT ” 3 - 2.7 (+0.7) 2.7 (+0.7) 3.0 (+1.0)

RON0 - 82 85.2 (+1.6) 85.2 (+1.6) 86.9 (+3.3)

Run Length (hr) 12000 8000 (Y) 8000 (-262.2) 8000 (-262.2) 6607.8 (-1654.4)

Margin (Rs/day) ___ ___ +3.32% +3.5% +4.7%

BTX (MT/day) ___ ___ ___ +3.1% +5.4%


Operating Margin Maximization:

Minm. Run length is the most important active constraint resulting in: highest separator pressure (to reduce catalyst deactivation) lowest inlet temperatures for the 1st two reactors (to reduce catalyst deactivation).

BTX Tonnage Maximization (Case A):

Minm. Run length is again the most important active constraint resulting in: highest separator pressure (to reduce catalyst deactivation) lowest inlet temperatures in the 1st two reactors (to reduce catalyst deactivation).

BTX Tonnage Maximization (Case B):

Lowering minm. run length has satisfied the following thermodynamic requirements: lowest separator pressure (to increase BTX formation) highest inlet temperatures in the 3rd reactor (to increase endothermic BTX

formation).


Optimization of a CCR

Base Case SimulationFeed Flow = 1411 MT/day

Recycle Gas flow = 186 MT/day

Catalyst Flow = 0 Kg/hr

Inlet Temperature of Successive Reactors = 507, 507, 507 oC

Temperature & Pressure of Separator Drum = 37 oC & 3.3 Kg/Cm2

Temperature & Pressure of Recontacting Drum = 27 oC & 6.1 Kg/Cm2

Temperature & Pressure of LPG Absorber Drum = 26 oC & 13.3 Kg/Cm2

RGP HP = 2057 KW

CHT duty = 6.7 MMKcal/hr

1st IHT duty = 6.5 MMKcal/hr

2nd IHT duty = 3.6 MMKcal/hr

RON0 = 98.6

SR Cycle length = 58 hr

Operating Margin = 4.41856 x 106 Rs/day


Opr. Margin Maximization

Maxm. Minm. Case A Case B (X=1450)

Feed (MT/day) 1500(X) 1300 1500 (+89) 1450 (+39)

Recycle ( ” ) 220 150 205 (+19) 194 (+8)

Sep. Press. (bar) 5 3 3.3 (0) 3.7 (+0.4)

1st Reac. in. oC 510 495 498 (-9) 495 (-12)

2nd Reac. in. oC 510 495 505 (-2) 508 (+1)

3rd Reac. in. oC 510 495 510 (+3) 510 (+3)

RGP HP (KW) 3000 - 2245 (+188) 1980 (-77)

CHT MMKcal/hr 8 - 8.0 (+1.3) 7.0 (+0.3)

1st IHT ” 7 - 7.0 (+0.5) 7.0 (+0.5)

2nd IHT ” 5 - 4.1 (+0.5) 4.0 (+0.4)

RON0 - 98.5 98.5 (-0.1) 98.5 (-0.1)

Run Length (hr) - 24 60 (+2) 67 (+9)

Margin (Rs/day) ___ ___ +6.7% +3.7%


Operating Margin Maximization (Case A):

Maxm. feed rate, maxm. charge-heater duty, maxm. 1st inter-heater duty and minm.

octane no. are the most important active constraints resulting in: highest possible reformate production lower inlet temperatures in the 1st two reactors and highest inlet temperature in

the last reactor minimizing hydrocracking in the first two reactors (reformate is much more

valuable than light gases) completing conversion of naphthene to aromatics in the last reactor (minm.

octane no. must be achieved).

Operating Margin Maximization (Case B):

Lowering maxm. feed rate has the following effects: highest possible reformate production (lower than Case A) Better profile of reactor inlet temperatures is achieved (profit margin increases by

0.095% as compared to only 0.075% in Case A, for each MT increase in feed rate).

REFERENCESREFERENCES

1. G. J. Antos, A. M. Aitani and J. M. Parera, "Catalytic Naphtha Reforming - Science &

Technology", Mercel Dekker, New York, 1995.

2. A. K. Datta, H. Singh, P. K. Sen, A. K. Saxena, G. Das, V. K. Kapoor, M. O. Garg, "Benzene

Management in Gasoline Using CRESOP", 11th Refinery Tech. Meeting, Hyderabad (India), 2000.

3. L. T. Biegler and J. E. Cuthrell, "Improved Infeasible Path Optimization for Sequential Modular

Simulators - II: The Optimization Algorithm", Comp. Chem. Engg., vol. 9, p.257, 1985.

4. N. L. Gilsdorf and R. H. Rachford, "Platforming in the Reformulated Gasoline Era", NPRA

annual meeting, Lousiana (USA), 1992.

5. M. J. Liebman, T. F. Edgar and L. S. Lasdon, “Efficient Data Reconciliation and Estimation for

Dynamic Process using NLP Techniques”, Comp. Chem. Engg., vol. 16, no. 10/11, p.963, 1992.

8. D. M. Little, “Catalytic Reforming”, PennWell, Tulsa (USA), 1985.

9. D. R. Mudt, T. W. Hoffman and S. R. Hendon, "The Closed-Loop Optimization of a

Semi-Regenerative Catalytic Reforming Process”, AIChE Meeting, March, Houston, 1995.

10. S. Narashimhan and R. S. H. Mah, "Generalized Likelihood Ratio Method for Gross Error

Detection", AIChE J., vol. 33, no. 9, p. 1514, 1987.

11. A. K. Saxena, G. Das and Harendra Singh, "Optimization of Semi-Regenerative Reformer - A

Case Study", Eighth Refinery Tech. Meeting, Chennai (India), 1995.

12. U. Taskar and J. B. Riggs, "Modeling and Optimization of a Semi-Regenerative Catalytic

Reformer", AIChE J., vol. 43, no. 3, p. 740, 1997.

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