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A Plantwide Control Procedure Applied to the HDA Process

A Plantwide Control Procedure Applied to the HDA Process. Antonio Araújo and Sigurd Skogestad Department of Chemical Engineering Norwegian University of Science and Technology (NTNU) Trondheim, Norway November, 2006. Outline. General procedure plantwide control HDA process

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A Plantwide Control Procedure Applied to the HDA Process

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  1. A Plantwide Control Procedure Applied to the HDA Process Antonio Araújo and Sigurd Skogestad Department of Chemical Engineering Norwegian University of Science and Technology (NTNU) Trondheim, Norway November, 2006

  2. Outline • General procedure plantwide control • HDA process • Active constraints • Self-optimizing variables • Maximum throughput mode • Regulatory control • Dynamic simulations • comparison with Luyben

  3. u (valves) General procedure plantwide control Part I. “Top-down” steady-state approach - identify active constraints and primary controlled variables (y1) • Self-optimizing control Part II. Bottom-up identification of control structure – starting with regulatory (“stabilizing”) control layer. • Identify secondary controlled variables (y2) RTO. min J (economics). MV = y1s y1s Control of primary variables (MPC) y2s “Stabilizing” control: p, levels, T (PID) • Skogestad, S. (2004), “Control structure design for complete chemical plants”, • Computers and Chemical Engineering, 28, 219-234.

  4. Part I. Top-down steady-state approach Step 1. IDENTIFY DEGREES OF FREEDOM Need later to choose a CV (y1) for each Step 2. OPERATIONAL OBJECTIVES Optimal operation: Minimize cost J J = cost feeds – value products – cost energy subject to satisfying constraints Step 3. WHAT TO CONTROL? (primary CV’s c=y1) What should we control (y1)? • Active constraints • “Self-optimizing” variables These are “magic” variables which when kept at constant setpoints give indirect optimal operation by controlling some “magic” variables at • Maximum gain rule: Look for “sensitive” variables with a large scaled steady-state gain Step 4. PRODUCTION RATE y1s

  5. u (valves) Part II. Bottom-up control structure design Step 5. REGULATORY CONTROL LAYER (PID) • Main objectives • “Stabilize” = Avoid “drift” • Control on fast time scale • Identify secondary controlled variables (y2) • flow, pressures, levels, selected temperatures • and pair with inputs (u2) Step 6. SUPERVISORY CONTROL LAYER • Decentralization or MPC? Step 7. OPTIMIZATION LAYER (RTO) • Can we do without it? y2 = ?

  6. Two main modes of optimal operation for chemical plants Depending on marked conditions: Mode I: Given throughput When: Given feed or product rate Optimal operation: Max. efficiency Mode II: Maximum throughput (feed available). When: High product prices and available feed Optimal operation: max. flow in bottleneck 1. Desired: Same or similar control structure in both cases 2. Operation/control: Traditionally: Focus on mode I But: Mode II is where the company may make extra money!

  7. Purge (CH4 + H2) Compressor H2 + CH4 Quench Toluene Mixer FEHE Furnace PFR Separator Cooler CH4 Toluene Benzene Toluene Column Stabilizer Benzene Column Diphenyl HDA process Toluene + H2 = Benzenje + CH4 2 Benzene = Diphenyl + H2 • References for HDA: • McKetta (1977) ; • Douglas (1988) • Wolff (1994) • Luyben (2005) • ++....

  8. 5 Purge (H2 + CH4) 3 Compressor 1 Furnace H2 + CH4 Quencher Toluene Mixer FEHE Reactor 6 4 2 Cooler 7 12 10 8 Separator Benzene CH4 Toluene Toluene Column Benzene Column Stabilizer Diphenyl 13 11 9 Step 1 - Steady-state degrees of freedom NEED TO FIND 13 CONTROLLED VARIABLES (y1)

  9. Step 2 - Definition of optimal operation • The following profit is to be maximized: -J = pbenDben + Σ(pv,iFv,i) – ptolFtol – pgasFgas – pfuelQfuel – pcwQcw – ppowerWpower - psteamQsteam • Constraints during operation: • Production rate: Dben≥ 265 lbmol/h. • Hydrogen excess in reactor inlet: Fhyd / (Fben + Ftol + Fdiph) ≥ 5. • Reactor inlet pressure: Preactor,in ≤ 500 psia. • Reactor inlet temperature: Treactor,in ≥ 1150 °F. • Reactor outlet temperature: Treactor,out ≤ 1300 °F. • Quencher outlet temperature: Tquencher,out ≤ 1150 °F. • Product purity: xDben ≥ 0.9997. • Separator inlet temperature: 95 °F ≤ Tseparator ≤ 105 °F. • Compressor power: WS ≤ 545 hp • Furnace heat duty: Qfur ≤ 24 MBtu • Cooler heat duty: Qcool ≤ 33 MBtu • + Distillation heat duties (condensers and reboilers).

  10. Disturbances • Typical disturbances : • Feeds • Utilities • Constraints • Caused by: implementation error or change

  11. Step 3: What to control? • 13 steady-state degrees of freedom • 70 Candidate controlled variables • pressures, temperatures, compositions, flow rates, heat duties, etc.. • Number of different sets of controlled variables: • Cannot evaluate all ! • OPTIMAL OPERATION: • Control active constraints! • Find from steady-state optimization (step 3.1) • Remaining unconstrained DOFs: • Look for “self-optimizing” variables (step 3.2)

  12. Operation with given feedMode I

  13. Step 3.1 – Optimization distillation • Distillation train: • Optimized separately using detailed models • Generally: Most valuable product at its constraint • Other compositions: Trade-off between recovery and energy • Results:

  14. Step 3.1 – Optimization entire process • Reactor-recycle part • With simplified distillation section (constant compositions) Distillation compositions

  15. Purge (H2 + CH4) Compressor 5 Furnace 4 H2 + CH4 Quencher Toluene Mixer FEHE Reactor 2 1 Cooler 3 8 6 10 Separator 4 Benzene CH4 Toluene Toluene Column Benzene Column Stabilizer Diphenyl Step 3.1 – Optimization: Active Constraints • Max. Toluene feed rate • Min. H2/aromatics ratio • Min. Separator temperature • Min. quencher temperature • Max. Reactor pressure • Max. impurity product • + 5 distillation purities 11 9 7

  16. Step 3.2: What more to control? • So far: Control 6 active constraints + 5 compositions (“self-optimizing”) • What should we do with the 2 remaining degrees of freedom? • Self-optimizing control: Control variables that give small economic loss when kept constant • But still many alternative sets • Prescreening: Use “maximum gain rule” (local analysis) for prescreening • Maximize σ(S1·G2x2·Juu-1/2). • Optimal variation and implementation error enters in S1

  17. Step 3.2 – “Maximum gain rule” • Linear model • All measurements: σ(S1Gfull·Juu-1/2) = 6.34·10-3 • Best set of two measurements involves two compositions: c1 c2

  18. Step 3 - Final selection in mode I Purge (H2 + CH4) Compressor c2 c1 5 Furnace 4 H2 + CH4 Quencher Toluene Mixer FEHE Reactor 2 1 Cooler 3 8 6 10 Separator 4 Benzene CH4 Toluene Toluene Column Benzene Column Stabilizer Diphenyl 11 9 7

  19. Step 3: What to control in Mode II ?Available feed and good product pricesMaximum throughput

  20. Optimization in mode II: Maximum throughput • 14 steady-state degrees of freedom (one extra) • Reoptimize operation with feedrate Ftol as parameter: • Find same active constraints as in Mode I. • At Ftol = 380 lbmol/h: Compressor power constraint active. • At Ftol = 390 lbmol/h: Furnace heat duty constraint active. • Further increase in Ftol infeasible: Furnace is BOTTLENECK!

  21. Step 3 - Controlled variable mode II c1 • 8 active constraints (including WS and Qfur ) • + 5 distillation compositions • One unconstrained degree of freedom: • To reduce the need for reconfiguration we control x-methane • Average loss 68.74 k$/year

  22. Step 4 – Throughput manipulator c1 • Mode I: Toluene feedrate (given) • Mode II: Optimal throughput manipulator is furnace duty (bottleneck) • Minimizes back-off • But furnace duty is used to stabilize reactor • So use toluene feedrate also in mode II

  23. Part II: Bottom-up designstarting with regulatory layer

  24. Step 5: Regulatory layer - Stabilization • Control reactor temperature and liquid levels in separator and distillation columns (LV configuration). TC01 LC01 LC22 LC12 LC32 LC31 LC21 LC11

  25. Regulatory layer - Avoiding drift I: Pressure control PC01 TC01 LC01 PC33 PC22 PC11 LC22 LC12 LC32 LC31 LC21 LC11

  26. Regulatory layer - Avoiding drift II: Temperature control TC03 PC01 TC02 TC01 LC01 PC33 PC22 PC11 TC11 #3 #5 LC22 LC12 LC32 TC33 TC22 #20 LC31 LC21 LC11

  27. Regulatory layer - Avoiding drift III: Flow control FC02 TC03 PC01 TC02 TC01 FC01 LC01 PC33 PC22 PC11 TC11 #3 #5 LC22 LC12 LC32 TC33 TC22 #20 LC31 LC21 LC11

  28. Step 6: Supervisory layer – Mode I Decentralized control (PID-loops) seems sufficient FC02 CC01 TC03 PC01 RC01 CC02 TC02 TC01 FC01 LC01 CC22 CC12 PC33 PC22 PC11 TC11 #3 #5 LC22 LC12 LC32 TC33 TC22 #20 CC32 LC31 LC21 LC11 CC11 CC31 CC21

  29. Step 6: Supervisory layer – Mode II Decentralized control (PID-loops) seems sufficient Fixed FC02 CC01 TC03 PC01 RC01 TC02 TC01 SETPOINT= Max.fuel-backoff LC01 CC22 CC12 PC33 PC22 PC11 TC11 #3 #5 LC22 LC12 LC32 TC33 TC22 #20 CC32 LC31 LC21 LC11 CC11 CC31 CC21

  30. Dynamic simulations – Mode I Disturbance D1: +15 lbmol/h (+5%) increase in Ftol . Ours Luyben’s

  31. Dynamic simulations – Mode I Disturbance D2: -15 lbmol/h (-5%) increase in Ftol . Ours Luyben’s

  32. Dynamic simulations – Mode I Disturbance D3: +0.05 increase in xmet. Ours Luyben’s

  33. Dynamic simulations – Mode I Disturbance D4: +20 psi increase in Prin. Ours Luyben’s

  34. Conclusion Procedure plantwide control: I. Top-down analysis to identify degrees of freedom and primary controlled variables (look for self-optimizing variables) II. Bottom-up analysis to determine secondary controlled variables and structure of control system (pairing).

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