Oil Refinery Heat Exchanger Network Cleaning Scheduling Strategy with Unit Cleanability Consideration

https://doi.org/10.22146/ajche.51880

Hairul Huda(1), Renanto Handogo(2*), Totok Ruki Biyanto(3), Wei Wu(4), Vincentius Surya Kurnia Adi(5)

(1) Chemical Engineering Department, Institut Teknologi Sepuluh Nopember, Surabaya, Indonesia
(2) Chemical Engineering Department, Institut Teknologi Sepuluh Nopember, Surabaya, Indonesia
(3) Engineering Physics Department, Institut Teknologi Sepuluh Nopember, Surabaya, Indonesia
(4) Chemical Engineering Department, National Cheng Kung University
(5) Chemical Engineering Department, National Chung Hsing University
(*) Corresponding Author

Abstract


Heat exchanger networks (HENs) play an important role in the chemical industries. Unfortunately, fouling is inevitable in heat exchangers operation. Therefore, the optimal cleaning procedure is required to restore heat exchangers' performance periodically. A systematic cleaning scheduling strategy for the heat exchanger network in an oil refinery is proposed in this work. There are 11 operating heat exchangers in an oil refinery to be reviewed. Different cleaning decision scenarios based on the overall heat transfer coefficient are explored for optimal cleaning schedule performance. The daily number of exchangers available to be cleaned i.e., the unit cleanability, is investigated while minimizing the energy consumption and the additional heat requirement due to the offline heat exchanger under cleaning procedure. The HEN performance and the energy-saving from the cleaning procedures are benchmarked with the uncleaned HEN. The results indicate that the cleaning procedure significantly increases the HEN performance and simultaneously reduces the heat requirement if compared to the untreated HEN benchmark. The possible conflicting situation is discussed when some heat exchangers are waiting to be cleaned due to the unit cleanability restriction, which allows the overall heat transfer coefficient to be below the allowed limit. Therefore, nonconflicting cleaning scheduling is also addressed in this work by relaxing the unit cleanability limit. Furthermore, the optimal cleaning schedule is also suggested for user reference. In this work, the optimum cleaning schedule with minimum energy consumption and maximum energy saving could be achieved when cleaning decision limit is set at 40% decrease of overall heat transfer coefficient. In the contrast, the lowest number of cleaning procedures is associated with 90% decrease in the overall heat transfer coefficient as the cleaning decision limit.


Keywords


Cleaning scheduling; Furnace; Heat duty; HEN; Overall heat transfer coefficient

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References

  1. Adloor, S. D., Ismaili, R. Al, Wilson, D. I., and Vassiliadis, V. S. (2018). "Errata: Heat exchanger network cleaning scheduling: From optimal control to mixed-integer decision making," Comput. and Chem. Eng., 115, 243–245.
  2. Angsutorn, N., Siemanond, K., and Chuvaree, R. (2014). "Heat Exchanger Network Synthesis using MINLP Stage-wise Model with Pinch Analysis and Relaxation," Comput. Aided Process Eng. 33, 139-144.
  3. Biyanto, T.R., Ramasamy, M., Jameran, A. B., and Fibrianto, H. Y. (2016). "Thermal and Hydraulic Impacts Consideration in Refinery Crude Preheat Train Cleaning Scheduling Using Recent Stochastic Optimization Methods", Appl. Therm. Eng., 108, 1436–1450.
  4. Biyanto, Totok R., Khairansyah, M. D., Bayuaji, R., Firmanto, H., and Haksoro, T. (2015). "Imperialist Competitive Algorithm (ICA) for Heat Exchanger Network (HEN) Cleaning Schedule Optimization," Procedia Comput. Sci., 72, 5–12.
  5. Coletti, F., Joshi, H. M., Macchietto, S., and Hewitt, G. F. (2015). Crude Oil Fouling: Deposit Characterization, Measurements, and Modeling, In Crude Oil Fouling: Deposit Characterization, Measurements, and Modeling, Gulf Professional Publishing, London, UK.
  6. Diaby, A. L., Miklavcic, S. J., and Addai-Mensah, J. (2016). "Optimization of scheduled cleaning of fouled heat exchanger network under ageing using genetic algorithm," Chem. Eng. Res. Des., 113, 223–240
  7. Gonçalves, C. D. O., Queiroz, E. M., Pessoa, F. L. P., Liporace, F. S., Oliveira, S. G., and Costa, A. L. H. (2014). "Heuristic optimization of the cleaning schedule of crude preheat trains," Appl. Therm. Eng., 73(1), 1–12.
  8. Ishiyama, E. M., Heins, A. V., Paterson, W. R., Spinelli, L., and Wilson, D. I. (2010). "Scheduling cleaning in a crude oil preheat train subject to fouling: Incorporating desalter control," Appl. Therm. Eng., 30, 1852–1862.
  9. Ishiyama, Edward M., Paterson, W. R., and Wilson, D. I. (2009). "The Effect of Fouling on Heat Transfer, Pressure Drop, and Throughput in Refinery Preheat Trains: Optimization of Cleaning Schedules," Heat Transf. Eng., 30, 805–814.
  10. Kakaç, S., Liu, H., and Pramuanjaroenkij, A. (2012). Heat Exchangers : Selection, Rating, and Thermal Design 3rd ed. CRC Press, Taylor & Francis Group, Boca Raton, Florida, U.S.A.
  11. Lavaja, J. H., and Bagajewicz, M. J. (2004). "On a New MILP Model for the Planning of Heat-Exchanger Network Cleaning," Ind. Eng. Chem. Res., 43(21), 3924–3938.
  12. Licindo, D., Handogo, R., and Sutikno, J. P. (2015). "Optimization on Scheduling for Cleaning Heat Exchangers in The Heat Exchanger Networks," Chem. Eng. Trans., 45, 835–840.
  13. Lozano Santamaria, F., and Macchietto, S. (2018). "Integration of Optimal Cleaning Scheduling and Control of Heat Exchanger Networks Undergoing Fouling: Model and Formulation," Ind. Eng. Chem. Res., 57, 12842–12860
  14. Macchietto, S., Coletti, F., and Bejarano, E. D. (2018). "Energy Recovery in Heat Exchanger Networks in a Dynamic, Big-data World: Design, Monitoring, Diagnosis and Operation," Comput. Aided Chem. Eng,. 44, 1147-1152.
  15. Pogiatzis, T., Ishiyama, E. M., Paterson, W. R., Vassiliadis, V. S., and Wilson, D. I. (2012). "Identifying optimal cleaning cycles for heat exchangers subject to fouling and ageing," Appl. Energy, 89, 60–66.
  16. Rodriguez, C., and Smith, R. (2007). "Optimization of Operating Conditions for Mitigating Fouling in Heat Exchanger Networks," Chem. Eng. Res. Des., 85, 839–851.
  17. Rossiter, A. P., and Jones, B. P. (2015). Energy Management and Efficiency for the Process Industries 1st ed., Wiley-AIChE, Canada.
  18. Sanaye, S., and Niroomand, B. (2007). "Simulation of Heat Exchanger Network (HEN) and Planning The Optimum Cleaning Schedule," Energy Convers. and Manag., 48, 1450–1461.
  19. Smaïli, F., Vassiliadis, V. S., and Wilson, D. I. (2001). "Mitigation of Fouling in Refinery Heat Exchanger Networks by Optimal Management of Cleaning," Energy and Fuels, 15, 1038–1056.
  20. Smaïli, F., Vassiliadis, V. S., and Wilson, D. I. (2002a). "Optimization of cleaning schedules in heat exchanger networks subject to fouling," Chem. Eng. Commun., 189, 1517–1549.
  21. Smaïli, F., Vassiliadis, V. S., and Wilson, D. I. (2002b). "Long-Term Scheduling Of Cleaning Of Heat Exchanger Networks Comparison Of Outer Approximation-Based Solutions with a Backtracking Threshold Accepting Algorithm," Chem. Eng. Res. Des., 80, 561–578..
  22. Varbanov, P. S., Walmsley, T. G., Walmsley, M., Klemeš, J. J., and Kravanja, Z. (2018). "Numerical Representation for Heat Exchanger Networks Binding Topology and Thermodynamics," Comput. Aided Chem. Eng., 43, 1457-1462.
  23. Wang, Y., Zhan, S., and Feng, X. (2015). "Optimization of Velocity for Energy Saving and Mitigating Fouling in a Crude Oil Preheat Train with Fixed Network Structure," Energy, 93, 1478–1488.
  24. Wilson, D. I. (2005). "Challenges in cleaning: Recent developments and future prospects," Heat Trans. Eng., 26, 51–59.



DOI: https://doi.org/10.22146/ajche.51880

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ASEAN Journal of Chemical Engineering  (print ISSN 1655-4418; online ISSN 2655-5409) is published by Chemical Engineering Department, Faculty of Engineering, Universitas Gadjah Mada.