GCC

(GENERALIZED CUTPOINT CONTROL)

Typical CDU configuration

Picture1

INFERENTIAL CONTROL OF FRACTIONATORS

Working over twenty years with crude units, Dr. Y. Zak Friedman of Petrocontrol, developed inferential modeling methodology that is based on process engineering principles. These models have been implemented on about 180 crude units and other fractionators with a high degree of success.

 

GCC works to –

  • Reconstruct crude TBP curve from unit conditions and heat balance. 
  • Estimate internal reflux profile, including overflash flow
  • Then infer product qualities as functions of boiling range and internal reflux

GCC features:

GCC makes use of heat balance for quick identification of feedstock changes.  Large fractionators my work for hours off mass balance, accumulating liquid on trays, but heat balance must always be satisfied, (or else – the column would explode).  In terms of keeping the unit under control, even difficult crude switches are accomplished within one hour, and during the switch product qualities are kept constant. Furthermore, there is no need to feed any data whatsoever before crude switches. Detection of crude characteristics is completely automatic.

 

  • Simple to calibrate.
GCC requires only a simple calibration procedure, which makes use of steady state data. The technique itself is robust enough to work without calibration, but given inaccuracies of flow, pressure and temperature measurements, precision improves after steady state calibration.

 

  • Self tuned.
Commissioning does not require elaborate tuning procedures. The model will work instantly, and it helps that the inferential responses are quick with short delay times. 

 

  • Easily understood.
The model follows standard API procedures for heat balance, temperature / pressure correction and EFV / TBP conversion.

 

  • Reliable enough to replace distillation analyzers.
Inferential precision is for example 2ºF for 90 % Naphtha distillation point, or 5 ºF for 90 % Diesel distillation point.  That said, GCC can also work with analyzers, resetting a bias in the calculation via a dead time compensator.

 

  • Able to manipulate all column cooling circuits.
Control of the cooling load distribution ensures fractionation in all sections of the column.

 

  • Multi variable dynamic capability.
The inferential calculations integrate easily with MVC (multi variable control) packages available on the market.  Indeed, the majority of our GCC models work to create inferences, whereas control action is applied by MVCs.

Crude TBP curve and cutpoints

TBPslope

Crude assay examples

Picture3

GCC Typical inferences

  • Distillation properties
    • Naphtha 90% point
    • Kerosene 90% point
    • LGO 90% point
    • HGO 90% point
  • Flash point
    • Kerosene flash point
    • LGO flash point
    • Sometimes HGO flash point

 

  • Cold properties (density analyzer on one of the sidestreams may improve cold property predictions)
    • Kero freeze point
    • LGO cloud or CFPP point
    • HGO cloud or pour point
  • Internal reflux at key trays
    • Below pumparound trays
    • Below sidestream draws
    • Overflash flow (important unmeasured constraint)

How GCC handles crude switches

Picture4

TBP slope and overflash trend

SlopeandOFtrend

Inferences versus lab trend

Picture6

Long term unbiased inferences

Picture7

Benefits of GCC

  • Crude switch time
from several hours 1 hour
  • Keep throughput high
  • Eliminate product downgrading
  • Overflash control
  • Internal reflux profile
  • Reduce number of alarms (and incidents)
  • Reduce lab support requirements
  • Information: crude TBP, other indicators

Reference literature:

  • Cross-unit APC boosts downstream performance, Asia Downstream Summit, October 2019, later published in PTQ Magazine, Q2 2020    2020_MelakaCDU-DHT_APC_PTQ
  • Total Zeeland refinery CDU APC revamp, IDTC conference, May 2018 (Prague).   2018_ZEELAND CDU APC downstream conf.  
  • Mild Hydrocracker APC at Bayernoil Neustadt refinery, IRPC conference, June 2016, later published in PTQ magazine, Q3 2017.   2017_bayernoil HCR PTQ
  • Asphalt DSR prediction and control, ARTC conference, March 2014, later published in PTQ magazine, Q4 2014.   2014_AsphaltDSRpaper_ForARTC
  • Lubes VDU product property prediction and control, ARTC conference, March 2014  2014_VDUMG3_Petronas
  • More on the Melaka delayed coker APC, ARTC conference, March 2013 2013_ARTC_coker_paper_slides
  • Total LOR CDU1 APC project, Laurent Ferrari, Sean Goodhart, Barry Rutter, Y Zak Friedman, ERTC computer conference, May 2012. 2012_LOR_GCC1_for_ERTC_final.pdf

  • Coker advanced process control at BP Gelsenkirchen refinery, Hydrocarbon Processing Journal, July 2007.BPGE_coker_July_2007.pdf

  • Implementation of APC on Repsol Poetollano CDU1, ERTC computer conference, May 2007.Puertollano_ERTC_May_2007.pdf

  • FCCU advanced control at Chevron Pembroke refinery, ERTC computer conference, May 2006.cvxERTCViennaMay2006.pdf

  • Implementation of APC on CDU 1 and CDU 3 at Sinopec Gaoqiao (Shanghai) refinery, Refining China Conference, April 2006. GaoQiao_paper_March_06.pdf

  • Coker Advanced Control and Inferential Modeling at BP Gelsenkirchen Refinery, ERTC computer conference, May 2005.2005_coker.pdf

  • The use of first-principle inference models for crude switching control, ERTC Computing Conference, May 2004.2004Petronas_ERTC.pdf

  • Multivariable Controller Implementation for a Crude Unit: A case Study, NPRA Computer Conference, October 2002, later published in O&G Journal, November 4 2002. 2002_NPRC_GCC.pdf  

  • Refinery uses column data to infer and control product properties. Oil & Gas Journal, February 19, 2001 and Refining & petrochemical property indicators for distillation, fractionation and crude switching. NPRA Computer Conference, November 2000. 2000_URC_CDU_Experience.pdf

  • Model-Based control of crude qualities: Unique advanced controls improved operation, particularly during crude switches. 1994_crude_switch.pdf

  • Control Of Crude Fractionator Predict Qualities During Feedstock Changes By Use Of Simplified Heat Balance. Paper presented at the 1985 American Control Conference, Boston, Massachusetts. 1985_GCC.pdf