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Sequential coordinate random search for optimal operation of LNG (liquefied natural gas) plant

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  • Khan, Mohd Shariq
  • I.A. Karimi,
  • Bahadori, Alireza
  • Lee, Moonyong

Abstract

This study exploits the sequential coordinate randomization search method for optimizing LNG (liquefied natural gas) process plants. The coordinate search is based on the idea of minimizing the multivariable function considering one variable at a time. The random element is incorporated in the coordinated search for an exhaustive exploration of decision variable space. A simple implementation with few operating parameters makes the proposed approach suitable for the optimization of highly non-linear LNG process plants. The efficacy of the proposed methodology was tested on the well-known SMR (single mixed refrigerant) and propane pre-cooled mixed refrigerant (C3MR) process of NG liquefaction. The main decision variables in SMR and C3MR process plants were identified and optimized in terms of the compression energy. The results were compared with the heuristic results, which revealed the superiority, simplicity and suitability of the proposed sequential coordinate random search algorithm for LNG process plants.

Suggested Citation

  • Khan, Mohd Shariq & I.A. Karimi, & Bahadori, Alireza & Lee, Moonyong, 2015. "Sequential coordinate random search for optimal operation of LNG (liquefied natural gas) plant," Energy, Elsevier, vol. 89(C), pages 757-767.
    • Handle: RePEc:eee:energy:v:89:y:2015:i:c:p:757-767
    DOI: 10.1016/j.energy.2015.06.021
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    References listed on IDEAS

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    3. Zhang, Shouxin & Zou, Zimo & Klemeš, Jiří Jaromír & Varbanov, Petar Sabev & Shahzad, Khurram & Ali, Arshid Mahmood & Wang, Bo-Hong, 2023. "A new strategy for mixed refrigerant composition optimisation in the propane precooled mixed refrigerant natural gas liquefaction process," Energy, Elsevier, vol. 274(C).
    4. He, Ting & Lin, Wensheng, 2020. "A novel propane pre-cooled mixed refrigerant process for coproduction of LNG and high purity ethane," Energy, Elsevier, vol. 202(C).
    5. Santos, Lucas F. & Costa, Caliane B.B. & Caballero, José A. & Ravagnani, Mauro A.S.S., 2022. "Framework for embedding black-box simulation into mathematical programming via kriging surrogate model applied to natural gas liquefaction process optimization," Applied Energy, Elsevier, vol. 310(C).
    6. Qyyum, Muhammad Abdul & Lee, Moonyong, 2018. "Hydrofluoroolefin-based novel mixed refrigerant for energy efficient and ecological LNG production," Energy, Elsevier, vol. 157(C), pages 483-492.
    7. Na, Jonggeol & Lim, Youngsub & Han, Chonghun, 2017. "A modified DIRECT algorithm for hidden constraints in an LNG process optimization," Energy, Elsevier, vol. 126(C), pages 488-500.
    8. Muhammad Abdul Qyyum & Muhammad Yasin & Alam Nawaz & Tianbiao He & Wahid Ali & Junaid Haider & Kinza Qadeer & Abdul-Sattar Nizami & Konstantinos Moustakas & Moonyong Lee, 2020. "Single-Solution-Based Vortex Search Strategy for Optimal Design of Offshore and Onshore Natural Gas Liquefaction Processes," Energies, MDPI, vol. 13(7), pages 1-22, April.
    9. Santos, Lucas F. & Costa, Caliane B.B. & Caballero, José A. & Ravagnani, Mauro A.S.S., 2023. "Multi-objective simulation–optimization via kriging surrogate models applied to natural gas liquefaction process design," Energy, Elsevier, vol. 262(PB).

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