Refinery Energy Losses Due to Fouling in Heat Exchangers


Figure 6: Network Retrofit Case Study19 C1


Kerosine GO Crude E-01 E-02 E-03 Desalter E-04 E-05 E-06 E-07 Residue C2 Kerosine GO Crude E-01 E-02 C3 E-03 Desalter E-04 E-05 Kerosine GO Crude E-01 E-02 E-03 Desalter


Upper P/A


Lower P/A


E-07x E-04 E-05 E-06 E-07 Fired heater E-06


Upper P/A


Lower P/A


HGO E-07x E-07 Residue HGO B


10 15 20


C4 Kerosine GO Crude E-01 E-02 E-03 Desalter


Upper P/A


Lower P/A


E-07x E-04 E-05 E-06 E-07 Residue Fired heater HGO


0 5


-5 0 C3 C1 C4 C2 Fired heater Fired heater


Upper P/A


Lower P/A


A HGO


280


210 220 230 240 250 260 270


200 0 C3 C1 C2 C4


100


200


300 Time (days)


400


500


600


100


200


300 Time (days)


exists between maximum energy recovery and fouling behaviour as it can be seen in Figure 6B which shows the cumulative additional energy recovered for C2, C3 and C4 over the original configuration C1. The difference in energy recovery for the three different retrofit solutions proposed can be large and using traditional energy recovery rules (e.g. pinch technology) can lead to poor network performance over time. Considering fouling dynamics in PHT network design and retrofit is thus of paramount importance.


Conclusion


Given the large quantity of energy and the costs involved, mitigation of crude oil fouling in atmospheric distillation unit PHTs, plays a major role in


unlocking energy efficiency of oil refineries. Taking into account the slow dynamics caused by fouling is important for control, operation and design optimisation. To effectively achieve fouling mitigation, fundamental knowledge accrued over years of research has been exploited in the novel, first principle thermo-hydraulic model presented here that captures the dynamic behaviour of refinery PHTs under fouling. Validation of the model using data from four individual units from two refineries and operators, spanning a wide range of operating conditions, gives good confidence in its predictive accuracy. Such a model can be used for control studies, but also to help decide cleaning schedules, evaluate retrofit options for individual exchangers20


or configure/retrofit new network structures that minimise fouling,19 based on economic impact. n


400


500


600


1.


Taborek J, Assessment of Fouling Research on the Design of Heat Exchangers. In: Panchal CB (Ed.), Fouling Mitigation of Industrial Heat-Exchange Equipment, Begell House, Inc., San Luis Obispo, California, 1997;27–39.


2. Watkinson P, Critical Review of Organic Fluid Fouling: Final Report, Argonne National Laboratory, 1988.


3.


Van Nostrand WL, Leach SH, Haluska JL, Economic Penalties Associated with the Fouling of Refinery Heat Transfer Equipment. In: Somerscales EFC, Knudsen JG (Eds), Fouling of Heat Transfer Equipment, Hemisphere: Troy, New York, 1981;619–43.


4. 5. 6. 7.


ESDU Heat exchanger fouling in the pre-heat train of a crude oil distillation unit, ESDU Data Item 00016; ESDU International plc, London, 2000.


Müller-Steinhagen H, Malayeri MR, Watkinson AP, Heat Exchanger Fouling: Environmental Impacts, Heat Tran Eng, 2009;30:773–6.


DOE Energy Bandwidth for Petroleum Refining Processes U.S. Department of Energy Office of Energy Efficiency and Renewable Energy Industrial Technologies Program 2006.


Yeap BL, Wilson DI, Polley GT, Pugh SJ, Mitigation of crude oil refinery heat exchanger fouling through retrofits based on thermo-hydraulic fouling models, Chem Eng Res Des, 2004;82A:53–71.


24


8. 9.


Macchietto S, Hewitt GF, Coletti BD, et al., Fouling in Crude Oil Preheat Trains: a Systematic Solution to an Old Problem, Heat Transfer Eng, 2010;32(3&4):197–215.


Ebert WA, Panchal CB, Analysis of Exxon crude-oil-slip stream coking data. In: Panchal CB, Bott TR, Somerscales EFC, Toyama S (Eds), Fouling Mitigation of Industrial Heat- Exchange Equipment, Begell House Inc., San Luis Obispo, California, 1997;451–60.


10. Butterworth D, Process heat transfer 2010, Appl Therm Eng, 2004;24:1395–1407.


11. Polley GT, Wilson DI, Yeap BL, Pugh SJ, Use of crude oil fouling threshold data in heat exchanger design, Appl Therm Eng, 2002;22:763–76.


12. Butterworth D, Design of shell-and-tube heat exchangers when the fouling depends on local temperature and velocity, Appl Therm Eng, 2002;22:789–801.


13. Bories M, Patureaux T, Preheat Train Crude Distillation Fouling Propensity Evaluation by the Ebert and Panchal Model. In: Watkinson P, Müller-Steinhagen H, Malayeri MR (Eds), ECI Conference on Heat Exchanger Fouling and Cleaning: Fundamentals and Applications, The Berkeley Electronic Press: Santa Fe, 2003;200–10.


14. Ishiyama EM, Paterson WR, Wilson DI, The Effect of Fouling on Heat Transfer, Pressure Drop, and Throughput in Refinery


Preheat Trains: Optimization of Cleaning Schedules, Heat Tran Eng, 2009;30:805–14.


15. Smaili F, Vassiliadis VS, Wilson DI, Mitigation of fouling in refinery heat exchanger networks by optimal management of cleaning, Energ Fuel, 2001;15:1038–56.


16. Lavaja JH, Bagajewicz MJ, On a New MILP Model for the Planning of Heat-Exchanger Network Cleaning. Part III: Multiperiod Cleaning under Uncertainty with Financial Risk Management, Ind Eng Chem Res, 2005;44:8136–46.


17. Coletti F, Macchietto S, A dynamic, distributed model of shell-and-tube heat exchangers undergoing crude oil fouling, Ind Eng Chem Res, 2011;50(8):4515–33.


18. Coletti F, Macchietto S, Refinery pre-heat train network simulation: assessment of energy efficiency and carbon emissions, Heat Transfer Eng, 2010;32(3&4):228–36.


19. Coletti F, Macchietto S,Polley GT, Effects of fouling on performance of retrofitted heat exchanger networks; a thermo-hydraulic based analysis, Comput Chem Eng, 2011;35(5):907–17.


20. Coletti F, A heat exchanger model to increase energy efficiency in refinery pre-heat trains. In: Jezowski J, Thullie J (Eds), European Symposium on Computer Aided Process Engineering (ESCAPE) 19, Elsevier: Cracow, Poland, 2009;1245–50.


HYDROCARBON WORLD – VOLUME 6 ISSUE 1


Energy recovery increase (%)


Coil inlet temperature (°C)


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