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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). What is Refinery Operations Planning?.

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Refinery Operations Planning

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  1. Refinery Operations Planning Dunham, Luhila, Odunuga

  2. Overview • Refinery Overview • Production Planning • Linear model with complex and simplified utilities • Results • Conclusions

  3. Model Refinery: Bangchak Refinery (Thailand)

  4. 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

  5. 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

  6. Production Planning • Production Planning • Processing of crude oil through different units • Decisions • Crude oil • Purchase • Processing • Inventory management Bangchak Refinery

  7. Production Planning • Routine process which guides purchasing • Departments • Crude oil acquisition, product sales & refinery operations • Based on • Market demands and prices • Uncertainty

  8. Production Planning • Winter • High fuel oil demand → more fuel oil produced • Summer • High demand for light crudes → more gasoline produced

  9. Linear Modeling Method CRU F2 F1 Light Ends Reactor Feed F3 Desulfurized Product Inside Unit is a black box (inside box doesn’t matter) Input and output can be related

  10. Linear Modeling Method CRU F2 F1 Light Ends Reactor Feed F3 Desulfurized Product Linear Equation Relating Inputs and Outputs: F3 =α31*F1 What is α31? It depends on the system!

  11. Finding Alpha(α) • Really, αij is the result of solving an ODE • Example: Concentration of Aromatics leaving a CRU • Thus αij will depend on • Inlet concentrations and flows • Process parameters: Temperature, Pressure

  12. Hydrotreating • Process to remove impurities in the stream • Aromatics • Hydrotreating for sulfur → hydrosulfurization • Reduces the aromatic content in crudes • Hydrogenation Nitrogen Sulfur

  13. Hydrotreating PFD

  14. Hydrotreating Model • Operating Conditions • Reactor Temperatures range from 250°F – 550°F • Main Variables • Pressure • Temperature • Velocity • H2/HC ratio

  15. KTU Aromatics Flow Rate ƒo = Initial Flow Rate

  16. Hydrotreating Empirical Model Aromatics:

  17. KTU Equation Comparison • Linear Equation: Far =α1*Ftotal • Actual Equation:

  18. Non linearity

  19. Catalytic Reforming • Process of increasing octane number of NPU by converting napthenes & paraffins • Outputs • Aromatics, light hydrocarbons (C1-C5) & hydrogen • Operating conditions

  20. Catalytic Reformer PFD

  21. CRU -Empirical Kinetic Model Conversion of napthenes to aromatics • Amount of product X1 Produced • Reaction Rate • Kinetic Reaction Constant • Equilibrium Constant

  22. Reformer Temperature Modeling

  23. 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

  24. 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 need to manually search for improved solutions

  25. 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

  26. PIMS Modeling • PIMS finds maximum by calculating objective function gradient • Maximum found by PIMS depends on initial condition Max 2 X Max 1 X x x Start 1 Start 2

  27. Alternative Method Linear Model with Utilities

  28. Model Super tables Product flow of Paraffins X=f(C,T,P,F) Conc = 0.31 Temp = 800 F Pressure = 400 psi Flowrate = 16000 m3/day X= 2630 bbl/hr

  29. Model Super tables

  30. Linear Model with Utilities • Our model finds the maximum by testing many discrete points • Optimum value will be close to the global optimum

  31. GAMS Software • Algebraic modeling interface capable of solving linear and mixed integer models • Non-linear equations cause problems

  32. Comparison Linear Model (in GAMS) PIMS • Linear or Mixed Integer Programming • Discretizes continuous values • Always finds best test point (near global maximum) • Successive Linear Programming • Uses gradient of objective function • May find local maximum (depends on starting point)

  33. 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

  34. Utility Table Equations • Water Cost (Heat exchangers) • Unit Fuel Gas Consumption (Heaters)

  35. Utility Equations in GAMS

  36. Results

  37. Linear Model Development

  38. 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

  39. Results - Gross Refinery Margin

  40. Results - Total Utility Cost

  41. Purchasing Recommendations

  42. Unit Operating Conditions

  43. DiscussionCatalytic Reforming Unit Isothermal Model Varying Temperature Model • Each reactor operates at a different temperature • Temperature changes in each reactor • Produces more Hydrogen • Produces almost 50% more Reformate Reactors are isothermal All reactor temperatures are the same Produces more Fuel Gas

  44. 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

  45. 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

  46. Questions?

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