IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v126y2017icp488-500.html
   My bibliography  Save this article

A modified DIRECT algorithm for hidden constraints in an LNG process optimization

Author

Listed:
  • Na, Jonggeol
  • Lim, Youngsub
  • Han, Chonghun

Abstract

Optimization for process design in the chemical engineering industry has been important for energy efficiency and economic feasibility. Because many industries perform optimization with a commercial process simulator such as the Aspen HYSYS, an optimization methodology for expensive black-box functions is needed. Thus, the development of derivative free optimization algorithms has long been studied and the deterministic global search algorithm DIRECT (DIviding a hyper-RECTangle) was suggested. In this paper, a modified DIRECT algorithm with a sub-dividing step for considering hidden constraints is proposed. The effectiveness of the algorithm is exemplified by its application to a cryogenic mixed refrigerant process using a single mixed refrigerant for natural gas liquefaction and its comparison with a well-known stochastic algorithm (GA, PSO, SA), and model based search algorithm (SNOBFIT), local solver (GPS, GSS, MADS, active-set, interior-point, SQP), and other hidden constraint handling methods, including the barrier approach and the neighborhood assignment strategy. Optimal solution calculated by the proposed algorithms decreases the specific power required for natural gas liquefaction to 18.9% compared to the base case.

Suggested Citation

  • 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.
  • Handle: RePEc:eee:energy:v:126:y:2017:i:c:p:488-500
    DOI: 10.1016/j.energy.2017.03.047
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544217304164
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.energy.2017.03.047?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. 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.
    2. 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.
    3. Hakimi, S.M. & Moghaddas-Tafreshi, S.M., 2009. "Optimal sizing of a stand-alone hybrid power system via particle swarm optimization for Kahnouj area in south-east of Iran," Renewable Energy, Elsevier, vol. 34(7), pages 1855-1862.
    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. 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.
    6. Luis Rios & Nikolaos Sahinidis, 2013. "Derivative-free optimization: a review of algorithms and comparison of software implementations," Journal of Global Optimization, Springer, vol. 56(3), pages 1247-1293, July.
    7. 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.
    8. 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.
    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. Donald R. Jones & Joaquim R. R. A. Martins, 2021. "The DIRECT algorithm: 25 years Later," Journal of Global Optimization, Springer, vol. 79(3), pages 521-566, March.
    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.
    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. Aslambakhsh, Amir Hamzeh & Moosavian, Mohammad Ali & Amidpour, Majid & Hosseini, Mohammad & AmirAfshar, Saeedeh, 2018. "Global cost optimization of a mini-scale liquefied natural gas plant," Energy, Elsevier, vol. 148(C), pages 1191-1200.
    5. Jin, Chunhe & Yuan, Yilong & Son, Heechang & Lim, Youngsub, 2022. "Novel propane-free mixed refrigerant integrated with nitrogen expansion natural gas liquefaction process for offshore units," Energy, Elsevier, vol. 238(PA).
    6. Linas Stripinis & Remigijus Paulavičius, 2023. "Novel Algorithm for Linearly Constrained Derivative Free Global Optimization of Lipschitz Functions," Mathematics, MDPI, vol. 11(13), pages 1-19, June.
    7. Ayub, Yousaf & Zhou, Jianzhao & Shen, Weifeng & Ren, Jingzheng, 2023. "Innovative valorization of biomass waste through integration of pyrolysis and gasification: Process design, optimization, and multi-scenario sustainability analysis," Energy, Elsevier, vol. 282(C).
    8. He, Tianbiao & Zhou, Zhongming & Mao, Ning & Qyyum, Muhammad Abdul, 2024. "Transcritical CO2 precooled single mixed refrigerant natural gas liquefaction process: Exergy and Exergoeconomic optimization," Energy, Elsevier, vol. 294(C).
    9. Yu, Taejong & Kim, Donghoi & Gundersen, Truls & Lim, Youngsub, 2023. "A feasibility study of HFO refrigerants for onboard BOG liquefaction processes," Energy, Elsevier, vol. 282(C).

    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. 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.
    2. Fazlollahi, Farhad & Bown, Alex & Ebrahimzadeh, Edris & Baxter, Larry L., 2015. "Design and analysis of the natural gas liquefaction optimization process- CCC-ES (energy storage of cryogenic carbon capture)," Energy, Elsevier, vol. 90(P1), pages 244-257.
    3. He, Tianbiao & Liu, Zuming & Ju, Yonglin & Parvez, Ashak Mahmud, 2019. "A comprehensive optimization and comparison of modified single mixed refrigerant and parallel nitrogen expansion liquefaction process for small-scale mobile LNG plant," Energy, Elsevier, vol. 167(C), pages 1-12.
    4. 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.
    5. Jiheon Ryu & Chihun Lee & Yutaek Seo & Juneyoung Kim & Suwon Seo & Daejun Chang, 2016. "A Novel Boil-Off Gas Re-Liquefaction Using a Spray Recondenser for Liquefied Natural-Gas Bunkering Operations," Energies, MDPI, vol. 9(12), pages 1-20, November.
    6. 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.
    7. Brodal, Eivind & Jackson, Steve & Eiksund, Oddmar, 2019. "Performance and design study of optimized LNG Mixed Fluid Cascade processes," Energy, Elsevier, vol. 189(C).
    8. Bian, Jiang & Cao, Xuewen & Yang, Wen & Edem, Mawugbe Ayivi & Yin, Pengbo & Jiang, Wenming, 2018. "Supersonic liquefaction properties of natural gas in the Laval nozzle," Energy, Elsevier, vol. 159(C), pages 706-715.
    9. 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.
    10. Sanavandi, Hamid & Mafi, Mostafa & Ziabasharhagh, Masoud, 2019. "Normalized sensitivity analysis of LNG processes - Case studies: Cascade and single mixed refrigerant systems," Energy, Elsevier, vol. 188(C).
    11. He, Tianbiao & Mao, Ning & Liu, Zuming & Qyyum, Muhammad Abdul & Lee, Moonyong & Pravez, Ashak Mahmud, 2020. "Impact of mixed refrigerant selection on energy and exergy performance of natural gas liquefaction processes," Energy, Elsevier, vol. 199(C).
    12. 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.
    13. Ghorbani, Bahram & Mehrpooya, Mehdi & Ghasemzadeh, Hossein, 2018. "Investigation of a hybrid water desalination, oxy-fuel power generation and CO2 liquefaction process," Energy, Elsevier, vol. 158(C), pages 1105-1119.
    14. Yu, Taejong & Kim, Donghoi & Gundersen, Truls & Lim, Youngsub, 2023. "A feasibility study of HFO refrigerants for onboard BOG liquefaction processes," Energy, Elsevier, vol. 282(C).
    15. Mofid, Hossein & Jazayeri-Rad, Hooshang & Shahbazian, Mehdi & Fetanat, Abdolvahhab, 2019. "Enhancing the performance of a parallel nitrogen expansion liquefaction process (NELP) using the multi-objective particle swarm optimization (MOPSO) algorithm," Energy, Elsevier, vol. 172(C), pages 286-303.
    16. 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).
    17. Xiong, Xiaojun & Lin, Wensheng & Gu, Anzhong, 2015. "Integration of CO2 cryogenic removal with a natural gas pressurized liquefaction process using gas expansion refrigeration," Energy, Elsevier, vol. 93(P1), pages 1-9.
    18. Li, Yong & Xie, Gongnan & Sunden, Bengt & Lu, Yuanwei & Wu, Yuting & Qin, Jiang, 2018. "Performance study on a single-screw compressor for a portable natural gas liquefaction process," Energy, Elsevier, vol. 148(C), pages 1032-1045.
    19. 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.
    20. 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).

    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:126:y:2017:i:c:p:488-500. 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.