implementation of coordinator mpc on a large-scale gas plant
DESCRIPTION
Implementation of Coordinator MPC on a Large-Scale Gas Plant. Elvira Marie B. Aske* & , Stig Strand & and Sigurd Skogestad * * Department of Chemical Engineering Norwegian University of Science and Technology (NTNU) Trondheim, Norway & StatoilHydro R&D, Process Control, Trondheim, Norway. - PowerPoint PPT PresentationTRANSCRIPT
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Implementation of Coordinator MPC on a Large-Scale Gas Plant
Elvira Marie B. Aske*&, Stig Strand& and Sigurd Skogestad*
*Department of Chemical Engineering
Norwegian University of Science and Technology (NTNU)
Trondheim, Norway&StatoilHydro R&D, Process Control, Trondheim, Norway
ADCHEM 2009, Istanbul, Turkey, July 12-15
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Outline• Introduction and motivation
– The Kårstø gas plant
• Maximum throughput as optimal operation• Approach: Coordinator MPC*:
– Maximize flow through linear network– Estimate feasible remaining capacity (R) in units using local MPCs
• Application to Kårstø Gas Plant– Previous work*: Works well on simulations– Here: Actual implementation
• Design• Tuning (plant runs)• Experiences
• Conclusion
*Aske, E.M.B., S. Strand and S. Skogestad (2008). Coordinator MPC for maximizing plant throughput. Comput. Chem. Eng. 32(1-2), 195–204.
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Gas processingareaControl
room
Kårstø plant
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Nyhamna
Europipe II
Europipe I
Norpipe
Emden
ÅTS
Norne
Åsgard
Haltenpipe
Heidrun
Franpipe
Zeebrugge
Zeepipe I
St Fergus
Vesterled
Frigg
Statfjord
Kårstø
Kollsnes
Melkøya
Snøhvit
Ormen Lange
Easington
Langeled
Ekofisk
Sleipner
Troll
Dunkerque
Kristin
Tjeldbergodden
North Sea gas network
• Kårstø plant: Receives gas from more than 30 offshore fields
• Limited capacity at Kårstø may limit offshore production (both oil and gas)
Norwegiancontinental shelf
Oslo
UK
GERMANY
TRONDHEIM
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5 Kårstø plant – 20 years of development
1985
2005
20001993
2003
How manipulate feeds and crossovers?
Europipe IIsales gas
Statpipesales gas
Propane
N-butane
I-butane
Naphtha
Ethane
Condensate
Sleipnercondensate
Tampen rich gas
Halten/Nordland rich gas
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Maximum throughput• Often: Economic optimal operation = maximum throughput
– Operate with max feasible flow through bottlenecks
– No remaining unconstrained DOFs (RTO not needed)
“Coordinator MPC”:• Manipulate TPMs (feed valves and crossovers) presently
used by operators• Throughput determined at plant-wide level (not by one
single unit) coordination required• Frequent changes dynamic model for optimization
TPM = Throughput Manipulator
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Approach
• Objective: Max throughput, subject to feasible operation:• Approach: Use Coordinator MPC to optimally adjust TPMs:
– Throughput manipulators (TPMs): Feeds and crossovers
– Remaining capacity (R) = Rs = 0 in bottleneck units
• Decompose the problem (decentralized).• Assume Local MPCs closed when running Coordinator MPC
– Need flow network model (No need for a detailed model of the entire plant)• Decoupling: Treat TPMs as DVs in Local MPCs• Use local MPCs to estimate feasible remaining capacity (R) in each unit
?
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8”Coordinator MPC”: Coordinates network flows, not MPCs
(remaining capacity)
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• Feasible remaining feed capacity for unit k:
• Obtained by solving “extra” steady-state LP problem in each local MPC:
subject to present state, models and constraints in the local MPC
• Use end predictions for the variables• Recalculated at every sample (updated measurements)• Very little extra effort!
Remaining capacity (using local MPCs)
current feed to unit kmax feed to unit k within feasible operation
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Local MPC applications
• Kårstø: Most local MPC applications are on two-product distillation columns: – CVs: Distillate- and bottom products quality (estimated)
+ differential pressure and other constraints
– MVs: Temperature setpoint (boilup) and reflux flow
– DV (disturbance): Feed flow
• New: Local MPCs estimate their feasible remaining capacity (R) using feed flow (DV) as degree of freedom
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Coordinator MPC: Design
Objective: Maximize plant throughput, subject to achieving feasible operation
• MVs: TPMs (feeds and crossovers that affect several units)• CVs: total plant feed + constraints:
– Constraints (R > backoff > 0, etc.) at highest priority level
– Objective function: Total plant feed as CV with high, unreachable set point with lower priority
• DVs: feed composition changes, disturbance flows• Model: step-response models obtained from
– Calculated steady-state gains (from feed composition)– Plant tests (dynamic)
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MV
CV
Half of the plant included:
6 MVs22 CVs7 DVs
Rich gas
Rich gas
Condensate
Export gas
Export gas
CV CV CV CV
CV CV
CV
CV
CV
CV CV
CV
CV
CV
CV
CV
CV
MV
MV
MV
MV
MV
KÅRSTØ MPC COORDINATOR IMPLEMENTATION (2008)
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13Step response models in coodinator MPC
+ more…
Remaining capacity (R) goes down when feed increases…
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Coordinator MPC in closed loop
• Test runs January and February 2008
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MV
CV3
Rich gas
Rich gas
Condensate
Export gas
Export gas
CV CV CV CV2
CV CV
CV
CV1
CV
CV CV
CV
CV
CV
CV
CV
CV
MV1
MV
MV2
MV
MV
DV
TEST 07 FEB 2008
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16 TEST 07 FEB 2008
MV1
DVMV2
CV1
CV2
CV3
t = 0 min: Turn ont = 250 - 320 min: Change model gains (tuning)t = 500 min: Adjust back-off for R in demethanizert = 580 – 600 min: Feed composition change (DV)
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Experiences• Using local MPCs to estimate feasible remaining capacity leads
to a plant-wide application with “reasonable” size• The estimated remaining capacity relies on
– accuracy of the steady-state models– correct and reasonable CV and MV constraints– use of gain scheduling to cope with larger nonlinearities
→ Crucial to inspect the models and tuning of the local applications in a systematic manner
• Requires follow-up work and extensive training of operators and operator managers
– “New way of thinking”
– New operator handle instead of feedrate: Rs (back-off)
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Conclusions
• Frequent changes in feed composition, pipeline pressures and other disturbances require a dynamic model for optimization
• Coordinator MPC is promising tool for implementing maximum throughput at the Kårstø gas plant.
• More focus among operator personnel on– capacity of each unit
– Plant-wide perspective to decide the plant- and crossover flows
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Acknowledgements• StatoilHydro and Gassco
• Kjetil Meyer, Roar Sørensen
• Operating managers and personnel at the Statpipe and Sleipner trains.
References• General approach: Aske, E.M.B., S. Strand and S. Skogestad (2008).
Coordinator MPC for maximizing plant throughput. Comput. Chem. Eng. 32(1-2), 195–204.
• Full paper application: E.M.B. Aske, Ph.D. thesis, NTNU, Trondheim, Norway, 2009 (Chapter 6). Available from the home page of S. Skogestad:http://www.nt.ntnu.no/users/skoge/publications/thesis/2009_aske/
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COORDINATORIN CLOSED LOOPDATE=05 Feb 2008
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MV
CV
Rich gas
Rich gas
Condensate
Export gas
Export gas
CV CV CV CV
CV CV
CV
CV
CV
CV CV
CV
CV
CV
CV
CV
CV
MV
MV
MV
MV
MV
DATE=07 Feb 2008
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9 hrs 6 hrs
CV: Pipeline pressure MV: Feed
CV: Remaining capacityMV: Crossover
Increasebackoff
New constraintfrom pipelinenetwork operators
DATE=07 Feb 2008
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COORDINATORIN CLOSED LOOP07 FEB 2008
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CV: Pipeline pressure MV: Feed
CV: Remainingcapacity
MV: Crossover
9 hrs 6 hrs
DV: Feed composition
Model adjustment
Compositiondisturbance
07 FEB 2008