IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v150y2018icp860-876.html
   My bibliography  Save this article

Optimization of single mixed-refrigerant natural gas liquefaction processes described by nondifferentiable models

Author

Listed:
  • Watson, Harry A.J.
  • Vikse, Matias
  • Gundersen, Truls
  • Barton, Paul I.

Abstract

A new strategy for the optimization of natural gas liquefaction processes is presented, in which flowsheets formulated using nondifferentiable process models are efficiently and robustly optimized using an interior-point algorithm. The constraints in the optimization formulation lead to solutions that ensure optimal usage of the area of multistream heat exchangers in the processes in order to minimize irreversibilities. The process optimization problems are solved reliably without the need for a complex initialization procedure even when highly accurate descriptions of the process stream cooling curves are required. In addition to the well-studied PRICO liquefaction process, two significantly more complex single mixed-refrigerant processes are successfully optimized and results are reported for each process subject to constraints imposed by several different operating scenarios.

Suggested Citation

  • Watson, Harry A.J. & Vikse, Matias & Gundersen, Truls & Barton, Paul I., 2018. "Optimization of single mixed-refrigerant natural gas liquefaction processes described by nondifferentiable models," Energy, Elsevier, vol. 150(C), pages 860-876.
  • Handle: RePEc:eee:energy:v:150:y:2018:i:c:p:860-876
    DOI: 10.1016/j.energy.2018.03.013
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544218304110
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.energy.2018.03.013?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Arne Stolbjerg Drud, 1994. "CONOPT—A Large-Scale GRG Code," INFORMS Journal on Computing, INFORMS, vol. 6(2), pages 207-216, May.
    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. NESTEROV, Yu., 2005. "Lexicographic differentiation of nonsmooth functions," LIDAM Reprints CORE 1817, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    4. Kamil A. Khan & Harry A. J. Watson & Paul I. Barton, 2017. "Differentiable McCormick relaxations," Journal of Global Optimization, Springer, vol. 67(4), pages 687-729, April.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Vikse, Matias & Watson, Harry A.J. & Kim, Donghoi & Barton, Paul I. & Gundersen, Truls, 2020. "Optimization of a dual mixed refrigerant process using a nonsmooth approach," Energy, Elsevier, vol. 196(C).
    2. Katebah, Mary A. & Hussein, Mohamed M. & Al-musleh, Easa I. & Almomani, Fares, 2023. "A systematic optimization approach of an actual LNG plant: Power savings and enhanced process economy," Energy, Elsevier, vol. 269(C).
    3. Tak, Kyungjae & Park, Jaedeuk & Moon, Il & Lee, Ung, 2023. "Comparison of mixed refrigerant cycles for natural gas liquefaction: From single mixed refrigerant to mixed fluid cascade processes," Energy, Elsevier, vol. 272(C).
    4. Matthew E. Wilhelm & Matthew D. Stuber, 2023. "Improved Convex and Concave Relaxations of Composite Bilinear Forms," Journal of Optimization Theory and Applications, Springer, vol. 197(1), pages 174-204, April.
    5. Subramanian, Avinash S.R. & Gundersen, Truls & Adams, Thomas A., 2020. "Technoeconomic analysis of a waste tire to liquefied synthetic natural gas (SNG) energy system," Energy, Elsevier, vol. 205(C).
    6. 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).
    7. Qyyum, Muhammad Abdul & Haider, Junaid & Qadeer, Kinza & Valentina, Valentina & Khan, Amin & Yasin, Muhammad & Aslam, Muhammad & De Guido, Giorgia & Pellegrini, Laura A. & Lee, Moonyong, 2020. "Biogas to liquefied biomethane: Assessment of 3P's–Production, processing, and prospects," Renewable and Sustainable Energy Reviews, Elsevier, vol. 119(C).
    8. Subramanian, Avinash S.R. & Gundersen, Truls & Adams, Thomas A., 2021. "Optimal design and operation of a waste tire feedstock polygeneration system," Energy, Elsevier, vol. 223(C).
    9. Bian, Jiang & Cao, Xuewen & Teng, Lin & Sun, Yuan & Gao, Song, 2019. "Effects of inlet parameters on the supersonic condensation and swirling characteristics of binary natural gas mixture," Energy, Elsevier, vol. 188(C).
    10. Tak, Kyungjae & Choi, Jiwon & Ryu, Jun-Hyung & Moon, Il, 2020. "Sensitivity analysis of effects of design parameters and decision variables on optimization of natural gas liquefaction process," Energy, Elsevier, vol. 206(C).
    11. 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).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Huiyi Cao & Kamil A. Khan, 2023. "General convex relaxations of implicit functions and inverse functions," Journal of Global Optimization, Springer, vol. 86(3), pages 545-572, July.
    2. Artur M. Schweidtmann & Alexander Mitsos, 2019. "Deterministic Global Optimization with Artificial Neural Networks Embedded," Journal of Optimization Theory and Applications, Springer, vol. 180(3), pages 925-948, March.
    3. 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).
    4. Dominik Bongartz & Alexander Mitsos, 2017. "Deterministic global optimization of process flowsheets in a reduced space using McCormick relaxations," Journal of Global Optimization, Springer, vol. 69(4), pages 761-796, December.
    5. Klaus Mittenzwei & Wolfgang Britz, 2018. "Analysing Farm‐specific Payments for Norway using the Agrispace Model," Journal of Agricultural Economics, Wiley Blackwell, vol. 69(3), pages 777-793, September.
    6. Ni, Yuanming & Steinshamn, Stein I. & Kvamsdal, Sturla F., 2022. "Negative shocks in an age-structured bioeconomic model and how to deal with them," Economic Analysis and Policy, Elsevier, vol. 76(C), pages 15-30.
    7. Duarte, Belmiro P.M. & Sagnol, Guillaume & Wong, Weng Kee, 2018. "An algorithm based on semidefinite programming for finding minimax optimal designs," Computational Statistics & Data Analysis, Elsevier, vol. 119(C), pages 99-117.
    8. Conrado Borraz-Sánchez & Russell Bent & Scott Backhaus & Hassan Hijazi & Pascal Van Hentenryck, 2016. "Convex Relaxations for Gas Expansion Planning," INFORMS Journal on Computing, INFORMS, vol. 28(4), pages 645-656, November.
    9. Andreas Lundell & Jan Kronqvist & Tapio Westerlund, 2022. "The supporting hyperplane optimization toolkit for convex MINLP," Journal of Global Optimization, Springer, vol. 84(1), pages 1-41, September.
    10. Tosoni, E. & Salo, A. & Govaerts, J. & Zio, E., 2019. "Comprehensiveness of scenarios in the safety assessment of nuclear waste repositories," Reliability Engineering and System Safety, Elsevier, vol. 188(C), pages 561-573.
    11. Durand-Lasserve, Olivier & Almutairi, Hossa & Aljarboua, Abdullah & Pierru, Axel & Pradhan, Shreekar & Murphy, Frederic, 2023. "Hard-linking a top-down economic model with a bottom-up energy system for an oil-exporting country with price controls," Energy, Elsevier, vol. 266(C).
    12. Masaki Kimizuka & Sunyoung Kim & Makoto Yamashita, 2019. "Solving pooling problems with time discretization by LP and SOCP relaxations and rescheduling methods," Journal of Global Optimization, Springer, vol. 75(3), pages 631-654, November.
    13. Michael D. Teter & Johannes O. Royset & Alexandra M. Newman, 2019. "Modeling uncertainty of expert elicitation for use in risk-based optimization," Annals of Operations Research, Springer, vol. 280(1), pages 189-210, September.
    14. Rastinejad, Justin & Putnam, Sloane & Stuber, Matthew D., 2023. "Technoeconomic assessment of solar technologies for the hybridization of industrial process heat systems using deterministic global dynamic optimization," Renewable Energy, Elsevier, vol. 216(C).
    15. Emmanuel Ogbe & Xiang Li, 2019. "A joint decomposition method for global optimization of multiscenario nonconvex mixed-integer nonlinear programs," Journal of Global Optimization, Springer, vol. 75(3), pages 595-629, November.
    16. Leon Lasdon & Judith S. Liebman, 1998. "The Teachers' Forum: Teaching Nonlinear Programming Using Cooperative Active Learning," Interfaces, INFORMS, vol. 28(4), pages 119-132, August.
    17. Marian Leimbach & Anselm Schultes & Lavinia Baumstark & Anastasis Giannousakis & Gunnar Luderer, 2017. "Solution algorithms for regional interactions in large-scale integrated assessment models of climate change," Annals of Operations Research, Springer, vol. 255(1), pages 29-45, August.
    18. Ximing Cai & Daene C. McKinney & Leon S. Lasdon & David W. Watkins, 2001. "Solving Large Nonconvex Water Resources Management Models Using Generalized Benders Decomposition," Operations Research, INFORMS, vol. 49(2), pages 235-245, April.
    19. Xu, Jianwei & Liang, Yingzong & Luo, Xianglong & Chen, Jianyong & Yang, Zhi & Chen, Ying, 2023. "Techno-economic-environmental analysis of direct-contact membrane distillation systems integrated with low-grade heat sources: A multi-objective optimization approach," Applied Energy, Elsevier, vol. 349(C).
    20. Persson, Maria, 2007. "Trade Facilitation and the EU-ACP Economic Partnership Agreements: Who Has the Most to Gain?," Conference papers 331619, Purdue University, Center for Global Trade Analysis, Global Trade Analysis Project.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:energy:v:150:y:2018:i:c:p:860-876. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/energy .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.