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Mehdi Panahi PhD defense presentation December 1 st , 2011 Trondheim

Plantwide Control for Economically Optimal Operation of Chemical Plants - Applications to GTL plants and CO 2 capturing processes. Mehdi Panahi PhD defense presentation December 1 st , 2011 Trondheim. Outline. Ch.2 Introduction

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Mehdi Panahi PhD defense presentation December 1 st , 2011 Trondheim

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  1. 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

  2. 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

  3. 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

  4. 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

  5. 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

  6. 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

  7. 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 For scalar case, which usually happens in many cases, the maximum expected loss is: Maximum gain rule is useful for prescreening the sets of best controlled variables

  8. Exact local method for selection the best CVs F is optimal sensitivity of the measurements with respect to disturbances;

  9. Applications of plantwide procedure to two important processes • Post-combustion CO2 capturing processes (Chapters 3, 4 and 5) • 2. Converting of natural gas to liquid hydrocarbons (Chapters 6 and 7)

  10. 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.

  11. Gas commercialization options and situation of GTL processes A simple flowsheet of a GTL process

  12. 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

  13. Economically optimal operation of CO2 capturing Step 1. Objective function: min. (energy cost + cost of released CO2 to the air) Step 2. 10 steady-state degrees of freedom Step 3. 3 main disturbances Step 4. Optimization 4 equality constraints and 2 inequality 2 unconstrained degrees of freedom;10-4-4=2 Steps 5&6. Exact Local method: The candidate CV set that imposes the minimum worst case loss to the objective function

  14. 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

  15. 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

  16. Proposed control structure with given flue gas flowrate (region I)

  17. Region II: in presence of large flowrates of flue gas (+30%) Saturation of reboiler duty (new operations region, region II); one unconstrained degree of freedom left Maximumgainrule for findingthe best CV: 37 candidates Temp. of tray no. 13 in the stripper: the largest scaled gain

  18. Proposed control structure with given flue gas flowrate (region I)

  19. Proposed control structure with given flue gas flowrate (region II) Reboiler duty at the maximum

  20. Region III: reaching the minimum allowable CO2 recovery A controller needed to set the flue gas flowrate

  21. 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

  22. 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.

  23. RGA analysis for selection of pairings 1. Dynamic RGA Reboiler duty Recycle amine CO2 recovery Temp. no.16 in the stripper 2. Steady-State RGA

  24. ”Break through” of CO2 at the top of the absorber (UniSim simulation) tray 15

  25. Proposed control structure with given flue gas flowrate, Alternative 1

  26. Proposed control structure with given flue gas flowrate,Alternative 2 (reverse pairing)

  27. Proposed control structure in region II,Alternative 3

  28. Modified alternative 2 Modified Alternative 2: Alternative 4

  29. Control of self-optimizing CVs using a multivariable controller

  30. Performance of the proposed control structure, Alternative 1

  31. Performance of the proposed control structure, Alternative 3

  32. Performance of the proposed control structure, Alternative 4

  33. Performance of the proposed control structure, MPC

  34. 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

  35. 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

  36. A simple flowsheet of GTL process CO+H2+CH4 CO2 (CH2)n (CH2)n CH4 CO+H2

  37. Pre-reformer reactions Converting higher hydrocarbons than methane, For Methanation Shift Reaction Auto-thermal reformer (ATR) reactions Oxidation of methane: Steam reforming of methane: Shift Reaction: Fischer-Tropsch (FT) reactions

  38. Fischer-Tropsch (FT) reactor Simulation of a slurry bubble column reactor (SBCR) Reactions: Kinetics (the model developed by Iglesia et al): FT products distribution (ASF model): 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)

  39. Detailed flowsheet of GTL process (UniSim)

  40. Differentmethods for calculationofα 1) α1 Real roots α as a function of the selectivity (1.2 ≤ H2/CO ≤ 2.15) 2) α2 3) Constant α = 0.9 (α3)

  41. FT reactor performance (single pass) at H2/CO=2 feed for α1, α2 and α3

  42. FT Products distribution when α1 is used

  43. FT Products distribution when α2 is used

  44. FT Products distribution when α3 is used

  45. Dependency of differentαcalculationmethods vs. feed H2/CO

  46. Optimization formulation Objective function Variable income (P): sales revenue – variable costs • Steady-state degrees of freedom • H2O/C (fresh + recycled hydrocarbons to pre-reformer) • O2/C (hydrocarbons into ATR) • 3. Fired heater duty • 4. CO2 recovery percentage • 5. Purge ratio • 6. Recycle ratio to FT reactor • Operational constraints • Molar ratio H2O/C ≥ 0.3 • ATR exit temperature ≤ 1030ºC, active at the max. • 3. Inlet temperature to ATR ≤ 675ºC, active at the max. • The purge ratio is optimally around 2%, it is bounded at a higher value, active at the min.

  47. Optimality of objective function (α2model) with respect to decision variables and active constraints, wax price= 0.63 USD/kg

  48. 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

  49. Optimal Operation of GTL process • - Mode I: Natural gas is given • Mode II: Natural gas is also a degree of freedom (maximum throughput)

  50. Process flowsheet of GTL process with data for optimal nominal point (mode I)

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