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Get More from your Process
using Modelling and Simulation
Andy Clegg
Industrial Systems and Control Ltd.
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ISC Background
Founded in 1987
Control Engineering Consultancy
Marine, Metals, Process and Automotive Industries
Specific Problem Solving
What-If ? Analysis
Applied Control Technology Consortium
Established 1990
Technology Transfer and Training
Through Dynamic Modelling
and Simulation
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Presentation
What is Modelling and Simulation ?
Examples:
Offshore Oil Platform Export Pump
pH Control in a Paper Mill
Water Pumping Station Modelling
Distillation Column Re-tuning
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What is a dynamic model?
“A parameterised set of algebraic and differential
equations that together define the static and dynamic
behaviour of a system”
Dynamic Modelling
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Dynamic Modelling
Why?
de-risk the plant design process
safe exploration of the plant operating envelope
investigate the causes of problems
evaluate control designs and process changes
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Static Modelling:
Used in plant design Component selection (to achieve plant specn) Energy balance calculations
Dynamic Modelling:
Used to design/evaluate plant for dynamic behaviourInduced by set point changesInduced by disturbancesStart-up/shutdown
Static v. Dynamic Modelling
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Build mathmodel
Port to simulation
environment
Validate model (static/dynamic
behaviour)
Fine tune model
Establish plant physical
structure/data
Pump & valve characteristics
Dimension of vessels & pipes
P & I drawing information
Intuitive knowledge plus
available plant data
Validated Model
Physical Dynamic Modelling
How?
Start simple
and enhance
as required
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Modelling – The Main Challenges
Define the objectives and level of detail
Defining the model boundaries and assumptions
Obtaining:
Plant component characteristics
Relationships between variables
Measured plant data
Validation:
Matching the behaviour of the model to that of the plant
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Linear Process Example
A Simple Tank: Simple analysis gives relationship:
time
qin
h
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Nonlinear Process Example
A Non-Simple Tank:Analysis is much more complex
Gives a nonlinear relationship
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Simulation
What is Simulation?
“Simulation is the numerical solution of a
mathematical system model by a computer”
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Provide
Integration algorithms (to solve nonlinear differential equations)
Static behaviour representation
Simplify model building process:
Hide much of maths
GUI Function block programming interface
Hierarchical structure
Libraries of common components
System/control analysis tools
Dynamic Simulation Tools
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Dynamic Simulation Tools
Matlab/Simulink
HYSYS Dynamics
LabVIEW
ACSL
VisSim
Easy5
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Dynamic Simulation Tool Comparison
Modelling Tool
Modelling
Tool Features
VisSim LabView MATLAB MATRIXx Easy5 HYSYSDynamic
ACSL
Block Structure Programming
Hierarchical Structure
Industrial Component Libraries
Continuous & Discrete Events
Basic Level Programming
Precision Validation Capability
Model Compiler
System/Control Analysis
Hydrocarbon phase tables
Widely Applied
Price Indicator Low Low Med. N/A High High High
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Problem
MOL export pump speed oscillations
High maintenance - costs and time
… which Impact on oil production
Repeated attempts to tune controllers – none really solved problem
Consultancy Approach
Represent process behaviour using Hysys Dynamics
Use to understand problem
Evaluate (change) solution options
Example 1: Offshore Oil Platform
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Hysys Dynamic model environment
Front–end of oil/gas/water separation process
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Identifying the Source of the Problem
Level controllers on surge vessels
two controllers had been “altered” to error-squared
DCS constraints gave pure integral action instability !!
inappropriate controller gains
Solution:
Re-tune and reconfigure controllers
Possible improvements through DCS upgrade
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Simulated Results
MOL Pump Dynamic Flow Behaviour
MOL pump recycle flow
- First 7 hrs. - current control
- Last 7 hrs. – re-designed control
MOL pump flow control
- First 7 hrs. - current control
- Last 7 hrs. – re-designed control
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Simulated Results
LP separator inflow & outflow
- First 7 hrs. - current control
- Last 7 hrs. – re-designed control
LP separator level
- First 7 hrs. - current control
- Last 7 hrs. – re-designed control
LP Vessel Dynamic Behaviour
Currently being implemented offshore
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Example 2: pH control in a Paper Mill
Feed Tank Level
pH
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pH Control Evaluation
Original ‘on-off’ controller
Trial PID controller
Modelled Controller Features
• Ideal PID Controller Structure
• Anti-windup
• Logic to inhibit controller during RT empty cycle
• Logic to switch between PID & ‘bang-bang’ controllers
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Validation of Model pH Dynamic Data
Plant data over a 9 hour period Model data over a 9 hour period
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pH Control Comparison
Current ‘On-Off’ Control
pH ‘Trigger’ points at - 4.7 (H2SO4 on)
- 4.6 (H2SO4 off)
Peak to peak pH amplitude 0.38 pH units
PID Control Alternative
pH set point at - 4.53
Peak to peak pH amplitude 0.03 pH units
Reduced by >90%
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pH response following recommendations 28/09/04
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Example 3: Water Pumping Station
“Water Industry Toolbox” icon added to Simulink
Library Browser
“Water Industry Toolbox” Blocks
Simulink Browser
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Building a Pumping Station Model
Create ‘new model’ by clicking on ‘new model’ icon
Click and drag blocks required
into the ‘new model’ window
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Constructed Model
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Actual Validation Results
Model Tank Level Trend Actual Tank Level Trend
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Modelling Exercise Findings
Predicted Lift Efficiency:
Original on-off strategy – 24.7%
Single VSD pump – 33.3%
Dual VSD pumps – 69.4%
Moving to Dual VSD pump would reduce energy
consumption by 64.5% !!
due to lower pumping speeds
Now implemented. Actual energy savings 65.1%
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Example 4: Level Analysis & Tuning
Step tests for level response:
Flow Valve
Level
Modelled using: integrator
deadtime
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Cascaded Level/Flow Loops
Simulink Model:
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Real Life Modelling Examples
Cascaded Level/Flow Analysis & Tuning
Level Controller Response:
Re-tuned
gains:
Matched plant response !!
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Summary
Hopefully demonstrated benefits of modelling
It can be difficult – but tools can make it easier
Thanks for listening, any questions ?
Andy Clegg, Industrial Systems and Control Ltd.
50 George St., Glasgow, G1 1QE
0141 553 1111
http://www.isc-ltd.com