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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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    1. Szargut, Jan & Szczygiel, Ireneusz, 2009. "Utilization of the cryogenic exergy of liquid natural gas (LNG) for the production of electricity," Energy, Elsevier, vol. 34(7), pages 827-837.
    2. Khan, Mohd Shariq & Lee, Moonyong, 2013. "Design optimization of single mixed refrigerant natural gas liquefaction process using the particle swarm paradigm with nonlinear constraints," Energy, Elsevier, vol. 49(C), pages 146-155.
    3. Lee, Ung & Kim, Kyeongsu & Han, Chonghun, 2014. "Design and optimization of multi-component organic rankine cycle using liquefied natural gas cryogenic exergy," Energy, Elsevier, vol. 77(C), pages 520-532.
    4. Mokarizadeh Haghighi Shirazi, M. & Mowla, D., 2010. "Energy optimization for liquefaction process of natural gas in peak shaving plant," Energy, Elsevier, vol. 35(7), pages 2878-2885.
    5. Liu, Yanni & Guo, Kaihua, 2011. "A novel cryogenic power cycle for LNG cold energy recovery," Energy, Elsevier, vol. 36(5), pages 2828-2833.
    6. Sun, Heng & Zhu, Hongmei & Liu, Feng & Ding, He, 2014. "Simulation and optimization of a novel Rankine power cycle for recovering cold energy from liquefied natural gas using a mixed working fluid," Energy, Elsevier, vol. 70(C), pages 317-324.
    7. Tan, Hongbo & Li, Yanzhong & Tuo, Hanfei & Zhou, Man & Tian, Baocong, 2010. "Experimental study on liquid/solid phase change for cold energy storage of Liquefied Natural Gas (LNG) refrigerated vehicle," Energy, Elsevier, vol. 35(5), pages 1927-1935.
    8. Khan, Mohd Shariq & Lee, Sanggyu & Rangaiah, G.P. & Lee, Moonyong, 2013. "Knowledge based decision making method for the selection of mixed refrigerant systems for energy efficient LNG processes," Applied Energy, Elsevier, vol. 111(C), pages 1018-1031.
    9. NESTEROV, Yurii, 2012. "Efficiency of coordinate descent methods on huge-scale optimization problems," LIDAM Reprints CORE 2511, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    10. Gómez, Manuel Romero & Garcia, Ramón Ferreiro & Gómez, Javier Romero & Carril, José Carbia, 2014. "Thermodynamic analysis of a Brayton cycle and Rankine cycle arranged in series exploiting the cold exergy of LNG (liquefied natural gas)," Energy, Elsevier, vol. 66(C), pages 927-937.
    11. Remeljej, C.W. & Hoadley, A.F.A., 2006. "An exergy analysis of small-scale liquefied natural gas (LNG) liquefaction processes," Energy, Elsevier, vol. 31(12), pages 2005-2019.
    12. Choi, In-Hwan & Lee, Sangick & Seo, Yutaek & Chang, Daejun, 2013. "Analysis and optimization of cascade Rankine cycle for liquefied natural gas cold energy recovery," Energy, Elsevier, vol. 61(C), pages 179-195.
    13. Xia, Guanghui & Sun, Qingxuan & Cao, Xu & Wang, Jiangfeng & Yu, Yizhao & Wang, Laisheng, 2014. "Thermodynamic analysis and optimization of a solar-powered transcritical CO2 (carbon dioxide) power cycle for reverse osmosis desalination based on the recovery of cryogenic energy of LNG (liquefied n," Energy, Elsevier, vol. 66(C), pages 643-653.
    14. He, Tianbiao & Ju, Yonglin, 2014. "A novel conceptual design of parallel nitrogen expansion liquefaction process for small-scale LNG (liquefied natural gas) plant in skid-mount packages," Energy, Elsevier, vol. 75(C), pages 349-359.
    15. Xu, Xiongwen & Liu, Jinping & Cao, Le & Pang, Weiqiang, 2014. "Automatically varying the composition of a mixed refrigerant solution for single mixed refrigerant LNG (liquefied natural gas) process at changing working conditions," Energy, Elsevier, vol. 64(C), pages 931-941.
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    2. 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).
    3. 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.
    4. 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.
    5. 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).
    6. Oh, Jin-Sik & Binns, Michael & Park, Sangmin & Kim, Jin-Kuk, 2016. "Improving the energy efficiency of industrial refrigeration systems," Energy, Elsevier, vol. 112(C), pages 826-835.
    7. Ali Rehman & Muhammad Abdul Qyyum & Ashfaq Ahmad & Saad Nawaz & Moonyong Lee & Li Wang, 2020. "Performance Enhancement of Nitrogen Dual Expander and Single Mixed Refrigerant LNG Processes Using Jaya Optimization Approach," Energies, MDPI, vol. 13(12), pages 1-27, June.
    8. 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).
    9. 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.

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