IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v139y2017icp98-117.html
   My bibliography  Save this article

Financial risks management of heat exchanger networks under uncertain utility costs via multi-objective optimization

Author

Listed:
  • Pavão, Leandro V.
  • Pozo, Carlos
  • Costa, Caliane B.B.
  • Ravagnani, Mauro A.S.S.
  • Jiménez, Laureano

Abstract

Although various Heat Exchanger Network (HEN) synthesis methods have been proposed in the literature, fundamental study for addressing uncertainties arisen from market fluctuations using stochastic variables and parameters is scarce. Such feature certainly adds difficulties to a problem already not straightforward to solve. In that manner, this work adapts a meta-heuristic approach to be able to efficiently perform such task. Uncertainties are assumed from variations in costs of commodities related to production of utilities. Several forecast scenarios are generated via Monte Carlo Simulation in order to obtain discretized distributions for the uncertain variables. Five financial risk metrics are applied for risks management. Each metric is formulated as secondary function to expected total annual costs (ETAC) in a multi-objective optimization (MOO) model with two objective functions. A benchmark case study is adapted in order to demonstrate the method reliability. The approach is able to achieve results that fit for different types of investors (e.g., risk-averse, risk-taker), handling uncertainty by efficiently performing trade-offs in heat exchange areas and utilities requirement.

Suggested Citation

  • Pavão, Leandro V. & Pozo, Carlos & Costa, Caliane B.B. & Ravagnani, Mauro A.S.S. & Jiménez, Laureano, 2017. "Financial risks management of heat exchanger networks under uncertain utility costs via multi-objective optimization," Energy, Elsevier, vol. 139(C), pages 98-117.
  • Handle: RePEc:eee:energy:v:139:y:2017:i:c:p:98-117
    DOI: 10.1016/j.energy.2017.07.153
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544217313373
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.energy.2017.07.153?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. Nemet, Andreja & Klemeš, Jiří Jaromír & Kravanja, Zdravko, 2012. "Minimisation of a heat exchanger networks' cost over its lifetime," Energy, Elsevier, vol. 45(1), pages 264-276.
    2. Novak Pintarič, Zorka & Kravanja, Zdravko, 2015. "A methodology for the synthesis of heat exchanger networks having large numbers of uncertain parameters," Energy, Elsevier, vol. 92(P3), pages 373-382.
    3. Gary D. Eppen & R. Kipp Martin & Linus Schrage, 1989. "OR Practice—A Scenario Approach to Capacity Planning," Operations Research, INFORMS, vol. 37(4), pages 517-527, August.
    4. Nemet, Andreja & Klemeš, Jiří Jaromír & Kravanja, Zdravko, 2013. "Optimising entire lifetime economy of heat exchanger networks," Energy, Elsevier, vol. 57(C), pages 222-235.
    Full references (including those not matched with items on IDEAS)

    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. Pavão, Leandro V. & Miranda, Camila B. & Costa, Caliane B.B. & Ravagnani, Mauro A.S.S., 2018. "Efficient multiperiod heat exchanger network synthesis using a meta-heuristic approach," Energy, Elsevier, vol. 142(C), pages 356-372.
    2. Huang, Kefeng & Karimi, I.A., 2016. "Work-heat exchanger network synthesis (WHENS)," Energy, Elsevier, vol. 113(C), pages 1006-1017.
    3. Zhang, B.J. & Li, J. & Zhang, Z.L. & Wang, K. & Chen, Q.L., 2016. "Simultaneous design of heat exchanger network for heat integration using hot direct discharges/feeds between process plants," Energy, Elsevier, vol. 109(C), pages 400-411.
    4. Kang, Lixia & Liu, Yongzhong & Wu, Le, 2016. "Synthesis of multi-period heat exchanger networks based on features of sub-period durations," Energy, Elsevier, vol. 116(P2), pages 1302-1311.
    5. Wang, Bohong & Klemeš, Jiří Jaromír & Li, Nianqi & Zeng, Min & Varbanov, Petar Sabev & Liang, Yongtu, 2021. "Heat exchanger network retrofit with heat exchanger and material type selection: A review and a novel method," Renewable and Sustainable Energy Reviews, Elsevier, vol. 138(C).
    6. Sabet, Ehsan & Yazdani, Baback & Kian, Ramez & Galanakis, Kostas, 2020. "A strategic and global manufacturing capacity management optimisation model: A Scenario-based multi-stage stochastic programming approach," Omega, Elsevier, vol. 93(C).
    7. Hongmin Li & Stephen C. Graves & Woonghee Tim Huh, 2014. "Optimal Capacity Conversion for Product Transitions Under High Service Requirements," Manufacturing & Service Operations Management, INFORMS, vol. 16(1), pages 46-60, February.
    8. Jaume Belles‐Sampera & Montserrat Guillén & Miguel Santolino, 2014. "Beyond Value‐at‐Risk: GlueVaR Distortion Risk Measures," Risk Analysis, John Wiley & Sons, vol. 34(1), pages 121-134, January.
    9. Kai Huang & Shabbir Ahmed, 2009. "The Value of Multistage Stochastic Programming in Capacity Planning Under Uncertainty," Operations Research, INFORMS, vol. 57(4), pages 893-904, August.
    10. Z Degraeve & F Roodhooft & B van Doveren, 2005. "The use of total cost of ownership for strategic procurement: a company-wide management information system," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 56(1), pages 51-59, January.
    11. Bex George Thomas & Srinivas Bollapragada, 2010. "General Electric Uses an Integrated Framework for Product Costing, Demand Forecasting, and Capacity Planning of New Photovoltaic Technology Products," Interfaces, INFORMS, vol. 40(5), pages 353-367, October.
    12. Elena Katok & William Tarantino & Terry P. Harrison, 2003. "Investment in production resource flexibility: An empirical investigation of methods for planning under uncertainty," Naval Research Logistics (NRL), John Wiley & Sons, vol. 50(2), pages 105-129, March.
    13. Hosseini-Motlagh, Seyyed-Mahdi & Govindan, Kannan & Nematollahi, Mohammadreza & Jokar, Abbas, 2019. "An adjustable bi-level wholesale price contract for coordinating a supply chain under scenario-based stochastic demand," International Journal of Production Economics, Elsevier, vol. 214(C), pages 175-195.
    14. Chang, Chenglin & Chen, Xiaolu & Wang, Yufei & Feng, Xiao, 2017. "Simultaneous optimization of multi-plant heat integration using intermediate fluid circles," Energy, Elsevier, vol. 121(C), pages 306-317.
    15. Zirngast, Klavdija & Kravanja, Zdravko & Novak Pintarič, Zorka, 2021. "An improved algorithm for synthesis of heat exchanger network with a large number of uncertain parameters," Energy, Elsevier, vol. 233(C).
    16. Van-Anh Truong & Robin O. Roundy, 2011. "Multidimensional Approximation Algorithms for Capacity-Expansion Problems," Operations Research, INFORMS, vol. 59(2), pages 313-327, April.
    17. Mojtaba Farrokh & Ehsan Ahmadi & Minghe Sun, 2023. "A robust stochastic possibilistic programming model for dynamic supply chain network design with pricing and technology selection decisions," OPSEARCH, Springer;Operational Research Society of India, vol. 60(3), pages 1082-1120, September.
    18. S Mudchanatongsuk & F Ordóñez & J Liu, 2008. "Robust solutions for network design under transportation cost and demand uncertainty," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 59(5), pages 652-662, May.
    19. Song, Sangcheol, 2021. "When do multinational corporations adjust production volume flexibly among in-network subsidiaries?," Journal of Business Research, Elsevier, vol. 135(C), pages 532-542.
    20. C A Poojari & C Lucas & G Mitra, 2008. "Robust solutions and risk measures for a supply chain planning problem under uncertainty," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 59(1), pages 2-12, January.

    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:139:y:2017:i:c:p:98-117. 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.