Optimal Model-Based Production Planning for Refinery …

[Pages:12]Optimal Model-Based Production Planning for Refinery Operation

Abdulrahman Alattas Advisor: Ignacio E. Grossmann

Chemical Engineering Department Carnegie Mellon University

1

Presentation Outline

Introduction Problem Statement LP-Based Planning Model Process Unit Models Aggregate Model Conclusion

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1

Motivation

Taxes,

20%

Refining Operation and crude cost

variable cost of production

Largest product price components

Crude,

Key to refinery profit and economics 53%

Dist. & Marketin

g, 9%

Refinery production planning models

Refining,

Operation optimization

18.10%

2005 Retail Gasoline Price Components

Crude selection

(Grant et al, 2006)

maximizing profit; minimizing cost

LP-based, linear process unit equations

comprise accuracy for robustness and simplicity

3

Motivation

Issues

Improvement to current models

Upgrade LP models to NLP Integrate scheduling into planning model

Current Project

collaboration with BP Goal: develop a refinery planning model with

nonlinear process unit equations, and integrated scheduling elements

4

2

Problem Statement

butane

crude1

SR Fuel gas SR Naphtha

SR Gasoline

Cat Ref

Typical Refinery Configuration (Adapted from Aronofsky, 1978)

Fuel gas

Premium Gasoline blending Reg.

CDU SR Distillate

crude2

SR GO SR Residuum

Cat Crack Hydrotreatment

Distillate Distillate blending

Gas oil GO blending

5

Treated Residuum

Problem Statement

Information Given

Refinery configuration: Process units Feedstock: crude oils & others Final Product: Specs & demand

Economics

Feedstock & operating cost Final product prices

Objective

Select crude oils and quantities to process

Maximizing profit 6

single period time horizon

3

LP-Based Planning Model (1)

Planning model

Typical elements

Process Units

yield equation

F = a F outlet

unit , feed ,outlet

feed

Base model: fixed yield for all units

Capacity check F feed ,unit Capunit

Separators:

feed

F = i,sep-in

Fi ', sep -out

i'

Mixers:

F = F i,mix-in

i ', mix -out

i

Product blending:

Fi, p = Fp

i

Product Specifications

Prp =

i

Pri Fi, p

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// Prp ( or )Spec pr, p Fp

LP-Based Planning Model (2)

Economics

Feedstock Cost

C * F feedstock feedstock

Operating cost

C * F unit

unit , feed

Income: product sales

C * F product

product

Objective function:

Profit

profit =

C prodcut * Fproduct -

C * F - feedstock

feedstock

C * F unit unit, feed

Cost

cost = C * F + feedstock feedstock Cunit * Funit, feed - C * F prodcut product

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4

Process Unit Models

Overview

Predicts products quantities and properties

SR Fuel gas

Function of feed and operating conditions

SR Naphtha

Inherently nonlinear

crude1

Process Models in Refinery Planning Model

SR Gasoline

Linear yield calculation assumption: LP requirement

CDU SR Distillate

Tradeoff: accuracy vs. robustness & simplicity

Area for nonlinear upgrade

Initial Focus on CDU

Front end of the every refinery

crude2

SR GO

Dictates final products and their quality Affects downstream units

SR Residuum

Typical Crude Distillation 9 Unit (CDU)

CDU Fixed Yield Model (1)

Fixed yield approach

Linear equation, for LP-based models Similar approach in other units Simple & robust Issues

Linear model No parameters for operating conditions or cuts

property calculations Single operating mode

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5

CDU Fixed Yield Model (2)

1200

Foutlet = aunit , feed * F feed

1000

TBP (?F)

Residuum Bottom

Heavy Distillate Light Distillate

Naphtha Fuel Gas

800

600

400

200

0

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

Crude Volume %

Crude true boiling point (TBP) curve showing crude cuts

11

(adapted from Watkins 1979)

CDU Swing Cut Model (1)

Swing cut approach

Upgrade from fixed yield Similar to fixed yield, with optimized cuts

Suitable for existing LP-based models Reflects operating modes Limitation

Linear model No parameters for operating conditions or cuts property

calculations

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6

CDU Swing Cut Model (2)

F = a * F + b + b outlet

CDU , feed

feed

CDU ,outlet , front

CDU ,outlet ,back

1200

SwingCut * Ffeed = bCDU ,outlet _ cut, front + bCDU ,outlet _ cut+1,back

1000

TBP (?F)

Residuum Bottom

Heavy Distillate Light Distillate

Naphtha Fuel Gas

800

600

400

200

0

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

Crude Volume %

Crude TBP curve showing crude cuts and swing cuts

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(adapted from Watkins 1979)

Complex Refinery Example -

Configuration for Heavy Crude Processing

Ref. Fuel

Gasoline

Reformer

Isomerization

Jet Fuel

CDU

Cracker

Desulfurization

Gas Oil

Fuel Oil

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Complex Refinery Configuration (Favennec, 2001)

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Complex Refinery Example - Data

Final Products Demand

Unit Capacity and Crude Availability

Final Products LPG Light naphtha Premium Gasoline (98 mogas) Regular Gasoline (95 mogas) Jet Fuel Gas Oil Fuel Oil Fuel Oil (Refinery use)

Demand (kt)

11 6

20 80 70 160 148 15.2

kt Crude Distillation Unit Reforming Capacity

95 severity Total Total Cracking Capacity Desulfurization Capacity Crude 1 (lighter) Crude 2 (heavier)

Min

Max

700

2 60

135 150 400 260

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Complex Refinery Example - Results

Crude Feedstock Other Feedstock

Refinery Production

Crude1 (lighter) Crude2 (heavier) Heavy Naphtha Fuel Gas LPG Light Naphtha Premium Gasoline Reg. Gasoline Gas Oil Fuel Oil Net Cost

Fixed yield Swing cut

142

0

289

469

13

9

13

17

18

20

6

6

20

20

80

92

163

170

148

160

89663

85714

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