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Refinery Stream
Modeling Walkthrough
Agenda
 Introduction
 Refinery stream modeling overview
 Modeling exercise
◦ Crude unit straight run naphtha 95%
 Feedback, Q&A
Our team
 40 years refinery process engineering, control,
and real time optimization experience
◦ Crude/Vac, Alky, FCC, Hydrocracking, Light Ends,
Olefins...
 Site Plans
◦ Sequence of advanced project control
◦ Benefit
◦ Additional Instrumentation requirements
 Tuning
◦ Poor regulatory tuning can reduce APC benefits by 40%-
70%
 Honeywell experience
◦ TDC, Experion, GUS, PHD, CL programming, APC
◦ Upgrades, support
Inferentials are core in refinery
advanced process control
 Distillation
 RVP
 Smoke
 Flash
 Cloud, Pour,
Viscosity
 Colour
 Octane, Cetane
 Composition
 Drivability
 Penetration, Shear
Modeling strategy
 Apply chemical engineering to select
plausible variables and equation forms
◦ Front end distillation = f(Bubble Point)
◦ Tail end distillation = f(Dewpoint)
◦ Flash  ASTM 5%
◦ Cloud  f(50%, Aromaticity)
◦ RVP
CTB
A
VP

)ln(
Crude Unit
Crude Unit
Model lab
 Straight run naptha 95%
◦ Fit model
◦ Accuracy
◦ Compare different points (90%, 95%, FBP)
Partial Pressure
 TIC-555 overhead
dewpoint at the
hydrocarbon partial
pressure
 Convert PI-551 to
absolute
◦ Calculate naptha and
steam moles to
calculate HC partial
pressure
Process Taglist
Tag Description Units
10FIC553 STRIP STEAM kg/min
10FI555 STRIP STM TO C 2 kg/h
10FI556 STRIP STM TO C 3 kg/h
10TIC555 C 1 OVHEAD TEMP deg C
10PI551 CRUDE TOWER TOP kPag
10FIC700 C 1 REFLUX FLOW m3/h
10PIC707 D3 RELIEF TO FLARE KPAG
10FIC701 D 3 NAPHTHA FLOW m3/h
10DI350 DESALTED CRUDE DENSITY KG/M3
10FI350 DESALTED CRUDE FEED MT/H
10TI551 CRUDE TOWER TRAY 23 deg C
10TI705 OVHD ACCUMULATOR NAPHTHA OUTLET deg C
10TI706 C 1 OHEAD TO D 3 deg C
Lab Data
Tag Units
STR RUN NAPHTHA, DENSITY [DENSITY] kg/m³
STR RUN NAPHTHA, SIMDIST(D2887) [IBP] °C
STR RUN NAPHTHA, SIMDIST(D2887) [5%] °C
STR RUN NAPHTHA, SIMDIST(D2887) [10%] °C
STR RUN NAPHTHA, SIMDIST(D2887) [15%] °C
STR RUN NAPHTHA, SIMDIST(D2887) [20%] °C
STR RUN NAPHTHA, SIMDIST(D2887) [25%] °C
STR RUN NAPHTHA, SIMDIST(D2887) [30%] °C
... °C
STR RUN NAPHTHA, SIMDIST(D2887) [50%] °C
... °C
STR RUN NAPHTHA, SIMDIST(D2887) [90%] °C
STR RUN NAPHTHA, SIMDIST(D2887) [95%] °C
STR RUN NAPHTHA, SIMDIST(D2887) [FBP] °C
MW Calc
Data Collection
 Frequency
◦ Lab data timestamps are usually only
approximate
 If the plant is steady the error this causes isn’t
serious
◦ If data from historian, we make sure that
compression is not excessive
◦ For analysis, we typically work with averages of
plant variables versus instantaneous readings
 This eliminates high frequency noise
 Crude unit, one hour average is usually effective
Client Dataset
Correlation sources
 API Technical Data Book
Stream MW
MW = 20.486*[exp(0.000165*Tb-
7.78712*SG+0.0011582*Tb*SG)]*Tb
1.26007*SG4.98308
where:
MW = molecular weight of the fraction
Tb = mean average boiling point of the petroleum
fraction degR
SG = specific gravity of the cut
Ref: 2B1.1 and 2B2.1
Modeling tool
 MACSEstimator modeling
◦ Offline tool
◦ Data visualization tool (PARCview)
 Explore and filter data
 Connect to your site sources and Excel
 Test models
 Fit models
 Create calculated tags
◦ Both use the same math libraries
Formulas and Calculations
 Comes with ASME steam tables
 Clients can create their own saved
libraries of formulas/functions
 Calculated tags get named and saved
 Supports external DLL libraries
 Capstone physical property library
available
 Formulas and library can be accessed by
process engineers using Excel
Using Steam Tables
What is the saturation temperature of steam at 101.325 kPa,
saturated vapour?
Answer: 99.96429585 °C, or 211.9496461°F
Physical Property Library
468 Compounds in library
Pure properties or
thermodynamic properties
such as Cp, Enthalpy, …
Going Online
 Components
 Data Flow
MACSEstimator
Evaluate
Inadequate Refine
Good Control
A simple online calculation is not
enough of a solution
Business objectives
Gather Data
Clean/Filter
Model
Go Online
Evaluate
24
The life cycle of a model
PARCmodel is an ideal tool in your plant analytics tool box
PARCmodel results can be used in any number of ways
 Monitored on-line for determining when a process shift has occurred
 Export for use with Capstone’s MACSestimator real-time soft sensor
 Advanced control with MACSsuite utilizing MACSestimator based soft
sensors
PARCview PARCmodel MACSestimator MACSsuiteProcess
Information
Capstone’s suite of process tools will significantly shorten the cycle time from
project conception, to project implementation
Calculation in DCS blocks
 Cons
◦ Challenging to debug, maintain and support
◦ Very rare that model is so good that lab
feedback not required
◦ Handling lab timestamps
MACSestimator
 Features
◦ Runs models in real time
◦ Handles filtering of data
◦ Validity checking
◦ Diagnostics
◦ Lab feedback
◦ Add calculations or new models on the fly
◦ Seamless integration with MACS controller
 Interlock/shed control
 Operator reset capability
MACSEstimatorArchitecture
Security
Database Client Data
Sources
TDCMACS Server
LIMS
OSI
PI/PHD/IP21.
.
.
MACS Server Components
 MACS
 MACSEstimator calculation engine
 MSSQL engine (server 2005 or greater)
◦ Security database and site data source connection
information
 Alarm Engine
◦ Monitors tags for alarm conditions
◦ Optional notification via email, OPCDA
 Health Engine
◦ Monitors server and application health (disk space,
memory, loss of data)
29

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Refinery stream modeling walkthrough

  • 2. Agenda  Introduction  Refinery stream modeling overview  Modeling exercise ◦ Crude unit straight run naphtha 95%  Feedback, Q&A
  • 3. Our team  40 years refinery process engineering, control, and real time optimization experience ◦ Crude/Vac, Alky, FCC, Hydrocracking, Light Ends, Olefins...  Site Plans ◦ Sequence of advanced project control ◦ Benefit ◦ Additional Instrumentation requirements  Tuning ◦ Poor regulatory tuning can reduce APC benefits by 40%- 70%  Honeywell experience ◦ TDC, Experion, GUS, PHD, CL programming, APC ◦ Upgrades, support
  • 4. Inferentials are core in refinery advanced process control  Distillation  RVP  Smoke  Flash  Cloud, Pour, Viscosity  Colour  Octane, Cetane  Composition  Drivability  Penetration, Shear
  • 5. Modeling strategy  Apply chemical engineering to select plausible variables and equation forms ◦ Front end distillation = f(Bubble Point) ◦ Tail end distillation = f(Dewpoint) ◦ Flash  ASTM 5% ◦ Cloud  f(50%, Aromaticity) ◦ RVP CTB A VP  )ln(
  • 8. Model lab  Straight run naptha 95% ◦ Fit model ◦ Accuracy ◦ Compare different points (90%, 95%, FBP)
  • 9.
  • 10. Partial Pressure  TIC-555 overhead dewpoint at the hydrocarbon partial pressure  Convert PI-551 to absolute ◦ Calculate naptha and steam moles to calculate HC partial pressure
  • 11.
  • 12. Process Taglist Tag Description Units 10FIC553 STRIP STEAM kg/min 10FI555 STRIP STM TO C 2 kg/h 10FI556 STRIP STM TO C 3 kg/h 10TIC555 C 1 OVHEAD TEMP deg C 10PI551 CRUDE TOWER TOP kPag 10FIC700 C 1 REFLUX FLOW m3/h 10PIC707 D3 RELIEF TO FLARE KPAG 10FIC701 D 3 NAPHTHA FLOW m3/h 10DI350 DESALTED CRUDE DENSITY KG/M3 10FI350 DESALTED CRUDE FEED MT/H 10TI551 CRUDE TOWER TRAY 23 deg C 10TI705 OVHD ACCUMULATOR NAPHTHA OUTLET deg C 10TI706 C 1 OHEAD TO D 3 deg C
  • 13. Lab Data Tag Units STR RUN NAPHTHA, DENSITY [DENSITY] kg/m³ STR RUN NAPHTHA, SIMDIST(D2887) [IBP] °C STR RUN NAPHTHA, SIMDIST(D2887) [5%] °C STR RUN NAPHTHA, SIMDIST(D2887) [10%] °C STR RUN NAPHTHA, SIMDIST(D2887) [15%] °C STR RUN NAPHTHA, SIMDIST(D2887) [20%] °C STR RUN NAPHTHA, SIMDIST(D2887) [25%] °C STR RUN NAPHTHA, SIMDIST(D2887) [30%] °C ... °C STR RUN NAPHTHA, SIMDIST(D2887) [50%] °C ... °C STR RUN NAPHTHA, SIMDIST(D2887) [90%] °C STR RUN NAPHTHA, SIMDIST(D2887) [95%] °C STR RUN NAPHTHA, SIMDIST(D2887) [FBP] °C MW Calc
  • 14. Data Collection  Frequency ◦ Lab data timestamps are usually only approximate  If the plant is steady the error this causes isn’t serious ◦ If data from historian, we make sure that compression is not excessive ◦ For analysis, we typically work with averages of plant variables versus instantaneous readings  This eliminates high frequency noise  Crude unit, one hour average is usually effective
  • 16. Correlation sources  API Technical Data Book
  • 17. Stream MW MW = 20.486*[exp(0.000165*Tb- 7.78712*SG+0.0011582*Tb*SG)]*Tb 1.26007*SG4.98308 where: MW = molecular weight of the fraction Tb = mean average boiling point of the petroleum fraction degR SG = specific gravity of the cut Ref: 2B1.1 and 2B2.1
  • 18. Modeling tool  MACSEstimator modeling ◦ Offline tool ◦ Data visualization tool (PARCview)  Explore and filter data  Connect to your site sources and Excel  Test models  Fit models  Create calculated tags ◦ Both use the same math libraries
  • 19. Formulas and Calculations  Comes with ASME steam tables  Clients can create their own saved libraries of formulas/functions  Calculated tags get named and saved  Supports external DLL libraries  Capstone physical property library available  Formulas and library can be accessed by process engineers using Excel
  • 20. Using Steam Tables What is the saturation temperature of steam at 101.325 kPa, saturated vapour? Answer: 99.96429585 °C, or 211.9496461°F
  • 21. Physical Property Library 468 Compounds in library Pure properties or thermodynamic properties such as Cp, Enthalpy, …
  • 24. Evaluate Inadequate Refine Good Control A simple online calculation is not enough of a solution Business objectives Gather Data Clean/Filter Model Go Online Evaluate 24 The life cycle of a model
  • 25. PARCmodel is an ideal tool in your plant analytics tool box PARCmodel results can be used in any number of ways  Monitored on-line for determining when a process shift has occurred  Export for use with Capstone’s MACSestimator real-time soft sensor  Advanced control with MACSsuite utilizing MACSestimator based soft sensors PARCview PARCmodel MACSestimator MACSsuiteProcess Information Capstone’s suite of process tools will significantly shorten the cycle time from project conception, to project implementation
  • 26. Calculation in DCS blocks  Cons ◦ Challenging to debug, maintain and support ◦ Very rare that model is so good that lab feedback not required ◦ Handling lab timestamps
  • 27. MACSestimator  Features ◦ Runs models in real time ◦ Handles filtering of data ◦ Validity checking ◦ Diagnostics ◦ Lab feedback ◦ Add calculations or new models on the fly ◦ Seamless integration with MACS controller  Interlock/shed control  Operator reset capability
  • 29. MACS Server Components  MACS  MACSEstimator calculation engine  MSSQL engine (server 2005 or greater) ◦ Security database and site data source connection information  Alarm Engine ◦ Monitors tags for alarm conditions ◦ Optional notification via email, OPCDA  Health Engine ◦ Monitors server and application health (disk space, memory, loss of data) 29