1 modelling, operation and control of an lng plant jens strandberg & sigurd skogestad department...
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Modelling, Operation and Control of an LNG Plant
Jens Strandberg
&
Sigurd Skogestad
Department of Chemical Engineering,
Norwegian University of Science and Technology
Trondheim, Norway
2
Outline
• Statoil's Snøhvit LNG Project
• Optimal Operation of LNG Plant
• Contollability Analysis
• Identifying the Model
• Results
• Conclusions and Further Work
3
Statoil's SnøhvitLNG Project
• Natural gas liquefaction plant situated at Melkøya island outside Hammerfest, northern Norway.
• Receiving natural gas from the Snøhvit, Albatross and Askeladd fields in the Barents Sea
• Liquefied Natural Gas (LNG) to be shipped by carriers to markets in Europe and the USA.
• Plant to go on-line in 2006
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The Mixed Fluid Cascade (MFC) Process
• Developed by Linde-Statoil Technology Alliance.
• Consists of– Precooling section
– Liquefaction section
– Subcooling section
• Heat exchangers are plate-fin types and spiral wound heat exchangers.
• Refrigerants are mixtures of methane, ethane, propane, nitrogen and others
• LNG product is cooled to -160ºC
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Optimal Operation of LNG plant
• Different from Optimal Design
• What to control?
• Optimization criteria (Economics)
• Degrees of Freedom:– 4 compressors
– 4 expansion valves
– NG flow
– refrigerant compositions (not considered here)
– Total: 9
• Controllability
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Optimal Operation of LNG plant
Case 1. Given feed rate. Keep final NG temperature at setpoint.
• Remaining DOF's = 7.
• Objective function for optimization:
• However, optimization studies indicate that keeping all the intermediate NG outlet temperatures constant is the best self-optimizing control structure.
• In this case, the remaining DOF's are 4.
J min u iW i ,comp W turbine
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Optimal Operation of LNG plant
Case 2. Keep final NG temperature at setpoint & Maximize LNG production.
• NG feed now “free”
• Compressors optimally at max, remaining DOF's = 4
• Keeping intermediate temperatures constant. DOF = 1
• So far: only steady-state considerations...
J max um LNG
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Controllability
• What is the controllability of the plant?
• Check:– Speed of response to reject disturbances
– Speed of response to track reference changes
– Input constraints arising from disturbances
– Effective time delay
• Consider one heat exchanger NG Shell
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Linear Models
• Controllability analysis -Need linear model of the plant.
• Starting point: tried to linearize a dynamic model of a spiral wound heat exchanger.
• Model developed by Sintef Trondheim for Statoil and is a pure simulation model.
• To derive a linear model by doing perturbations directly on the model equations proved infeasible.
• Instead, black-box model identification techniques were applied.
• Matlab's System Identification Toolbox has been used to create low order SISO models for the heat exchanger.
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Model identification
• Method applied to the liquefaction heat exchanger.
• 4 streams– 4 input temperatures
– 4 input pressures
– 4 input mass flows
• Simulations made with PRBS-type perturbations. One input at a time.
• Matlab routines used:– n4sid, pem, bj, oe.
NG Shell
y u
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Comparing model outputs
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Resulting models and Controllability
• Controllability– speed of responses OK
– input constraints OK
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Conclusions and Further Work
• Illustrated systematic approach for control system design:
– what to control
– economics
– controllability
• Usually large difference between optimal design and optimal operation
• Illustrated use of model identification techniques to derive linear models
• Detailed economic optimization
• Linearization of model equations directly
• MIMO identification
• Further contollability studies
• Controller designs
• Startup optimizations
Conclusions Further Work
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Acknowledgements
• Thanks to Sintef and Statoil for use of Dcoil simulation model
• Supporters:– Norwegian Research Fund
(NFR)
– Natural Gas Research Center, NTNU