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Optimization and comparative analysis of LNG regasification processes

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  • Fahmy, M.F.M.
  • Nabih, H.I.
  • El-Rasoul, T.A.

Abstract

LNG (liquefied natural gas) receiving terminals are responsible for assuring that regasified LNG meets pipeline specifications and accordingly, certain compositional modifications of the received LNG are anticipated by the industry. Meeting pipeline specifications of lower heating value range of natural gas through extraction of heavy components; C2+ can yield additional revenue. The objective of this study is to investigate LNG regasification systems in an attempt to achieve the requirements of maximum C2+ recovery and utmost gains from products sales while meeting pipeline specifications with respect to the heating value range of the natural gas. Different LNG regasification process configurations are analyzed through examining their respective operating variables and conditions that influence these regasification systems. A computer simulation is conducted and the investigated parameters are de-methanizer feed temperature, de-methanizer column pressure, number of de-methanizer column trays, mole percent of methane in bottom product from de-methanizer, outlet compressor pressure, refrigeration recovery exchanger outlet temperature, outlet air cooler temperature, split fraction of LNG from LNG pumps and residue gas heater temperature. The operating parameters of each process configuration are optimized and results reveal the optimum configuration providing the maximum amount of C2+ recovery and allowing maximum net gain.

Suggested Citation

  • Fahmy, M.F.M. & Nabih, H.I. & El-Rasoul, T.A., 2015. "Optimization and comparative analysis of LNG regasification processes," Energy, Elsevier, vol. 91(C), pages 371-385.
  • Handle: RePEc:eee:energy:v:91:y:2015:i:c:p:371-385
    DOI: 10.1016/j.energy.2015.08.035
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    2. Ghorbani, Bahram & Shirmohammadi, Reza & Mehrpooya, Mehdi & Hamedi, Mohammad-Hossein, 2018. "Structural, operational and economic optimization of cryogenic natural gas plant using NSGAII two-objective genetic algorithm," Energy, Elsevier, vol. 159(C), pages 410-428.
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    5. Davide Borelli & Francesco Devia & Corrado Schenone & Federico Silenzi & Luca A. Tagliafico, 2021. "Dynamic Modelling of LNG Powered Combined Energy Systems in Port Areas," Energies, MDPI, vol. 14(12), pages 1-18, June.

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