IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v108y2013icp439-447.html
   My bibliography  Save this article

Multi-objective optimization of VOC recovery and reuse in crude oil loading

Author

Listed:
  • Lee, Sangick
  • Choi, Inhwan
  • Chang, Daejun

Abstract

A recently enforced international regulation states that a crude oil tanker must have on board and implement a volatile organic compounds (VOCs) management plan that is approved by the administration. There are few thorough investigations that have simultaneously considered the various aspects of VOC recovery from the loading of crude oil into oil tankers. The current study investigated a compression-assisted refrigeration condensation system for VOC recovery during crude oil loading operations. System performance and the profit with different operation conditions showed rather a complicated relation than just a trade-off. The optimum process configuration and the ideal operational conditions of compression pressure and refrigeration temperature were determined through process simulation combined multi-objective optimization based on economic and environmental cost-benefit assessments. Although the installation of the system requires rather expensive initial costs, the system was found to be economically beneficial in the long term if the optimal system parameters were implemented. The method presented in this study can be applied to systems optimization processes with different factor values and considerations.

Suggested Citation

  • Lee, Sangick & Choi, Inhwan & Chang, Daejun, 2013. "Multi-objective optimization of VOC recovery and reuse in crude oil loading," Applied Energy, Elsevier, vol. 108(C), pages 439-447.
    • Handle: RePEc:eee:appene:v:108:y:2013:i:c:p:439-447
    DOI: 10.1016/j.apenergy.2013.03.064
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261913002602
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.apenergy.2013.03.064?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. Ren, Hongbo & Zhou, Weisheng & Nakagami, Ken'ichi & Gao, Weijun & Wu, Qiong, 2010. "Multi-objective optimization for the operation of distributed energy systems considering economic and environmental aspects," Applied Energy, Elsevier, vol. 87(12), pages 3642-3651, December.
    2. Sanaye, Sepehr & Dehghandokht, Masoud, 2011. "Modeling and multi-objective optimization of parallel flow condenser using evolutionary algorithm," Applied Energy, Elsevier, vol. 88(5), pages 1568-1577, May.
    3. Gholap, A.K. & Khan, J.A., 2007. "Design and multi-objective optimization of heat exchangers for refrigerators," Applied Energy, Elsevier, vol. 84(12), pages 1226-1239, December.
    4. Bannai, Masaaki & Houkabe, Akira & Furukawa, Masahiko & Kashiwagi, Takao & Akisawa, Atsushi & Yoshida, Takuya & Yamada, Hiroyuki, 2006. "Development of efficiency-enhanced cogeneration system utilizing high-temperature exhaust-gas from a regenerative thermal oxidizer for waste volatile-organic-compound gases," Applied Energy, Elsevier, vol. 83(9), pages 929-942, September.
    5. Sayyaadi, Hoseyn & Babaelahi, M., 2011. "Multi-objective optimization of a joule cycle for re-liquefaction of the Liquefied Natural Gas," Applied Energy, Elsevier, vol. 88(9), pages 3012-3021.
    6. Gebreslassie, Berhane H. & Guillén-Gosálbez, Gonzalo & Jiménez, Laureano & Boer, Dieter, 2009. "Design of environmentally conscious absorption cooling systems via multi-objective optimization and life cycle assessment," Applied Energy, Elsevier, vol. 86(9), pages 1712-1722, September.
    7. Lazzaretto, A. & Toffolo, A., 2004. "Energy, economy and environment as objectives in multi-criterion optimization of thermal systems design," Energy, Elsevier, vol. 29(8), pages 1139-1157.
    8. Gebreslassie, Berhane H. & Guillén-Gosálbez, Gonzalo & Jiménez, Laureano & Boer, Dieter, 2010. "A systematic tool for the minimization of the life cycle impact of solar assisted absorption cooling systems," Energy, Elsevier, vol. 35(9), pages 3849-3862.
    9. Sayyaadi, Hoseyn, 2009. "Multi-objective approach in thermoenvironomic optimization of a benchmark cogeneration system," Applied Energy, Elsevier, vol. 86(6), pages 867-879, June.
    10. Vaskan, Pavel & Guillén-Gosálbez, Gonzalo & Jiménez, Laureano, 2012. "Multi-objective design of heat-exchanger networks considering several life cycle impacts using a rigorous MILP-based dimensionality reduction technique," Applied Energy, Elsevier, vol. 98(C), pages 149-161.
    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. Nicoletti, Jack & You, Fengqi, 2020. "Multiobjective economic and environmental optimization of global crude oil purchase and sale planning with noncooperative stakeholders," Applied Energy, Elsevier, vol. 259(C).
    2. Hwalong You & Youngkyun Seo & Cheol Huh & Daejun Chang, 2014. "Performance Analysis of Cold Energy Recovery from CO 2 Injection in Ship-Based Carbon Capture and Storage (CCS)," Energies, MDPI, vol. 7(11), pages 1-16, November.
    3. Xu, Hao & Xu, Xiafan & Chen, Liubiao & Guo, Jia & Wang, Junjie, 2022. "A novel cryogenic condensation system combined with gas turbine with low carbon emission for volatile compounds recovery," Energy, Elsevier, vol. 248(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. Gebreslassie, Berhane H. & Groll, Eckhard A. & Garimella, Suresh V., 2012. "Multi-objective optimization of sustainable single-effect water/Lithium Bromide absorption cycle," Renewable Energy, Elsevier, vol. 46(C), pages 100-110.
    2. Mallikarjun, Sreekanth & Lewis, Herbert F., 2014. "Energy technology allocation for distributed energy resources: A strategic technology-policy framework," Energy, Elsevier, vol. 72(C), pages 783-799.
    3. Fazlollahi, Samira & Mandel, Pierre & Becker, Gwenaelle & Maréchal, Francois, 2012. "Methods for multi-objective investment and operating optimization of complex energy systems," Energy, Elsevier, vol. 45(1), pages 12-22.
    4. Carvalho, Monica & Lozano, Miguel A. & Serra, Luis M., 2012. "Multicriteria synthesis of trigeneration systems considering economic and environmental aspects," Applied Energy, Elsevier, vol. 91(1), pages 245-254.
    5. Ren, Hongbo & Zhou, Weisheng & Nakagami, Ken'ichi & Gao, Weijun & Wu, Qiong, 2010. "Multi-objective optimization for the operation of distributed energy systems considering economic and environmental aspects," Applied Energy, Elsevier, vol. 87(12), pages 3642-3651, December.
    6. Luo, Xianglong & Yi, Zhitong & Zhang, Bingjian & Mo, Songping & Wang, Chao & Song, Mengjie & Chen, Ying, 2017. "Mathematical modelling and optimization of the liquid separation condenser used in organic Rankine cycle," Applied Energy, Elsevier, vol. 185(P2), pages 1309-1323.
    7. Luo, Zhongyang & Sultan, Umair & Ni, Mingjiang & Peng, Hao & Shi, Bingwei & Xiao, Gang, 2016. "Multi-objective optimization for GPU3 Stirling engine by combining multi-objective algorithms," Renewable Energy, Elsevier, vol. 94(C), pages 114-125.
    8. Nondy, J. & Gogoi, T.K., 2021. "Performance comparison of multi-objective evolutionary algorithms for exergetic and exergoenvironomic optimization of a benchmark combined heat and power system," Energy, Elsevier, vol. 233(C).
    9. Sayyaadi, Hoseyn & Mehrabipour, Reza, 2012. "Efficiency enhancement of a gas turbine cycle using an optimized tubular recuperative heat exchanger," Energy, Elsevier, vol. 38(1), pages 362-375.
    10. Shirazi, Ali & Najafi, Behzad & Aminyavari, Mehdi & Rinaldi, Fabio & Taylor, Robert A., 2014. "Thermal–economic–environmental analysis and multi-objective optimization of an ice thermal energy storage system for gas turbine cycle inlet air cooling," Energy, Elsevier, vol. 69(C), pages 212-226.
    11. Sayyaadi, Hoseyn & Baghsheikhi, Mostafa, 2019. "Retrofit of a steam power plant using the adaptive neuro-fuzzy inference system in response to the load variation," Energy, Elsevier, vol. 175(C), pages 1164-1173.
    12. Gimelli, Alfredo & Muccillo, Massimiliano, 2013. "Optimization criteria for cogeneration systems: Multi-objective approach and application in an hospital facility," Applied Energy, Elsevier, vol. 104(C), pages 910-923.
    13. Sayyaadi, Hoseyn & Babaie, Meisam & Farmani, Mohammad Reza, 2011. "Implementing of the multi-objective particle swarm optimizer and fuzzy decision-maker in exergetic, exergoeconomic and environmental optimization of a benchmark cogeneration system," Energy, Elsevier, vol. 36(8), pages 4777-4789.
    14. Lee, Su Kyoung & Lee, Jae Won & Lee, Hoseong & Chung, Jin Taek & Kang, Yong Tae, 2019. "Optimal design of generators for H2O/LiBr absorption chiller with multi-heat sources," Energy, Elsevier, vol. 167(C), pages 47-59.
    15. Sayyaadi, Hoseyn & Aminian, Hamid Reza, 2010. "Design and optimization of a non-TEMA type tubular recuperative heat exchanger used in a regenerative gas turbine cycle," Energy, Elsevier, vol. 35(4), pages 1647-1657.
    16. Pavão, L.V. & Costa, C.B.B. & Ravagnani, M.A.S.S. & Jiménez, L., 2017. "Costs and environmental impacts multi-objective heat exchanger networks synthesis using a meta-heuristic approach," Applied Energy, Elsevier, vol. 203(C), pages 304-320.
    17. Sanaye, Sepehr & Dehghandokht, Masoud, 2011. "Modeling and multi-objective optimization of parallel flow condenser using evolutionary algorithm," Applied Energy, Elsevier, vol. 88(5), pages 1568-1577, May.
    18. Sayyaadi, Hoseyn & Baghsheikhi, Mostafa, 2018. "Developing a novel methodology based on the adaptive neuro-fuzzy interference system for the exergoeconomic optimization of energy systems," Energy, Elsevier, vol. 164(C), pages 218-235.
    19. Buoro, D. & Casisi, M. & De Nardi, A. & Pinamonti, P. & Reini, M., 2013. "Multicriteria optimization of a distributed energy supply system for an industrial area," Energy, Elsevier, vol. 58(C), pages 128-137.
    20. Ligang Wang & Zhiping Yang & Shivom Sharma & Alberto Mian & Tzu-En Lin & George Tsatsaronis & François Maréchal & Yongping Yang, 2018. "A Review of Evaluation, Optimization and Synthesis of Energy Systems: Methodology and Application to Thermal Power Plants," Energies, MDPI, vol. 12(1), pages 1-53, December.

    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:appene:v:108:y:2013:i:c:p:439-447. 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.elsevier.com/wps/find/journaldescription.cws_home/405891/description#description .

    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.