IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v116y2016ip2p1334-1347.html
   My bibliography  Save this article

Target-oriented robust optimization of polygeneration systems under uncertainty

Author

Listed:
  • Sy, Charlle L.
  • Aviso, Kathleen B.
  • Ubando, Aristotle T.
  • Tan, Raymond R.

Abstract

Production of clean, low-carbon energy and by-products is possible through the use of highly integrated, efficient systems such as polygeneration plants. Mathematical programming methods have proven to be valuable for the optimal synthesis of such systems. However, in practice, numerical parameters used in optimization models may be subject to uncertainties. Examples include cost coefficients in volatile markets, and thermodynamic coefficients in new process technologies. In such cases, it is necessary for the uncertainties to be incorporated into the optimization procedure. This paper presents a target-oriented robust optimization (TORO) approach for the synthesis of polygeneration systems. The use of this methodology leads to the development of a mathematical model that maximizes robustness against uncertainty, subject to the achievement of system targets. Its properties allow us to preserve computational tractability and obtain solutions to realistic-sized problems. The methodology is demonstrated for the synthesis of polygeneration systems using TORO with an illustrative case study.

Suggested Citation

  • Sy, Charlle L. & Aviso, Kathleen B. & Ubando, Aristotle T. & Tan, Raymond R., 2016. "Target-oriented robust optimization of polygeneration systems under uncertainty," Energy, Elsevier, vol. 116(P2), pages 1334-1347.
  • Handle: RePEc:eee:energy:v:116:y:2016:i:p2:p:1334-1347
    DOI: 10.1016/j.energy.2016.06.057
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544216308313
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.energy.2016.06.057?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. Mancarella, Pierluigi, 2014. "MES (multi-energy systems): An overview of concepts and evaluation models," Energy, Elsevier, vol. 65(C), pages 1-17.
    2. Serra, Luis M. & Lozano, Miguel-Angel & Ramos, Jose & Ensinas, Adriano V. & Nebra, Silvia A., 2009. "Polygeneration and efficient use of natural resources," Energy, Elsevier, vol. 34(5), pages 575-586.
    3. Van Dael, Miet & Van Passel, Steven & Pelkmans, Luc & Guisson, Ruben & Reumermann, Patrick & Luzardo, Nathalie Marquez & Witters, Nele & Broeze, Jan, 2013. "A techno-economic evaluation of a biomass energy conversion park," Applied Energy, Elsevier, vol. 104(C), pages 611-622.
    4. Carvalho, Monica & Serra, Luis Maria & Lozano, Miguel Angel, 2011. "Optimal synthesis of trigeneration systems subject to environmental constraints," Energy, Elsevier, vol. 36(6), pages 3779-3790.
    5. Tan, Raymond R. & Cayamanda, Christina D. & Aviso, Kathleen B., 2014. "P-graph approach to optimal operational adjustment in polygeneration plants under conditions of process inoperability," Applied Energy, Elsevier, vol. 135(C), pages 402-406.
    6. Andiappan, Viknesh & Tan, Raymond R. & Aviso, Kathleen B. & Ng, Denny K.S., 2015. "Synthesis and optimisation of biomass-based tri-generation systems with reliability aspects," Energy, Elsevier, vol. 89(C), pages 803-818.
    7. Foo, Dominic C.Y. & Tan, Raymond R. & Lam, Hon Loong & Abdul Aziz, Mustafa Kamal & Klemeš, Jiří Jaromír, 2013. "Robust models for the synthesis of flexible palm oil-based regional bioenergy supply chain," Energy, Elsevier, vol. 55(C), pages 68-73.
    8. Nemet, Andreja & Klemeš, Jiří Jaromír & Kravanja, Zdravko, 2013. "Optimising entire lifetime economy of heat exchanger networks," Energy, Elsevier, vol. 57(C), pages 222-235.
    9. Arthur M. Geoffrion, 1976. "The Purpose of Mathematical Programming is Insight, Not Numbers," Interfaces, INFORMS, vol. 7(1), pages 81-92, November.
    10. Gil-Alana, Luis A. & Gupta, Rangan & Olubusoye, Olusanya E. & Yaya, OlaOluwa S., 2016. "Time series analysis of persistence in crude oil price volatility across bull and bear regimes," Energy, Elsevier, vol. 109(C), pages 29-37.
    11. Khan, Ershad Ullah & Martin, Andrew R., 2015. "Optimization of hybrid renewable energy polygeneration system with membrane distillation for rural households in Bangladesh," Energy, Elsevier, vol. 93(P1), pages 1116-1127.
    12. 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.
    13. Lozano, M.A. & Carvalho, M. & Serra, L.M., 2009. "Operational strategy and marginal costs in simple trigeneration systems," Energy, Elsevier, vol. 34(11), pages 2001-2008.
    14. Kasivisvanathan, Harresh & Barilea, Ivan Dale U. & Ng, Denny K.S. & Tan, Raymond R., 2013. "Optimal operational adjustment in multi-functional energy systems in response to process inoperability," Applied Energy, Elsevier, vol. 102(C), pages 492-500.
    15. Nemet, Andreja & Klemeš, Jiří Jaromír & Varbanov, Petar Sabev & Kravanja, Zdravko, 2012. "Methodology for maximising the use of renewables with variable availability," Energy, Elsevier, vol. 44(1), pages 29-37.
    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. Ngan, Sue Lin & How, Bing Shen & Teng, Sin Yong & Leong, Wei Dong & Loy, Adrian Chun Minh & Yatim, Puan & Promentilla, Michael Angelo B. & Lam, Hon Loong, 2020. "A hybrid approach to prioritize risk mitigation strategies for biomass polygeneration systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 121(C).
    2. Luo, Yan & Wang, Zhiyuan & Zhu, Jiamin & Lu, Tao & Xiao, Gang & Chu, Fengming & Wang, Ruixing, 2022. "Multi-objective robust optimization of a solar power tower plant under uncertainty," Energy, Elsevier, vol. 238(PA).
    3. Tan, Raymond R. & Aviso, Kathleen B. & Foo, Dominic C.Y. & Lee, Jui-Yuan & Ubando, Aristotle T., 2019. "Optimal synthesis of negative emissions polygeneration systems with desalination," Energy, Elsevier, vol. 187(C).
    4. Yuan, Jiahang & Luo, Xinggang & Li, Yun & Hu, Xiaoqing & Chen, Wenchong & Zhang, Yue, 2022. "Multi criteria decision-making for distributed energy system based on multi-source heterogeneous data," Energy, Elsevier, vol. 239(PD).
    5. Majewski, Dinah Elena & Lampe, Matthias & Voll, Philip & Bardow, André, 2017. "TRusT: A Two-stage Robustness Trade-off approach for the design of decentralized energy supply systems," Energy, Elsevier, vol. 118(C), pages 590-599.
    6. Aviso, Kathleen B. & Tan, Raymond R., 2018. "Fuzzy P-graph for optimal synthesis of cogeneration and trigeneration systems," Energy, Elsevier, vol. 154(C), pages 258-268.
    7. Pina, Eduardo A. & Lozano, Miguel A. & Ramos, José C. & Serra, Luis M., 2020. "Tackling thermal integration in the synthesis of polygeneration systems for buildings," Applied Energy, Elsevier, vol. 269(C).
    8. Zhang, Yan & Fu, Lijun & Zhu, Wanlu & Bao, Xianqiang & Liu, Cang, 2018. "Robust model predictive control for optimal energy management of island microgrids with uncertainties," Energy, Elsevier, vol. 164(C), pages 1229-1241.
    9. Frangopoulos, Christos A., 2018. "Recent developments and trends in optimization of energy systems," Energy, Elsevier, vol. 164(C), pages 1011-1020.

    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. Aviso, Kathleen B. & Tan, Raymond R., 2018. "Fuzzy P-graph for optimal synthesis of cogeneration and trigeneration systems," Energy, Elsevier, vol. 154(C), pages 258-268.
    2. Tan, Raymond R. & Cayamanda, Christina D. & Aviso, Kathleen B., 2014. "P-graph approach to optimal operational adjustment in polygeneration plants under conditions of process inoperability," Applied Energy, Elsevier, vol. 135(C), pages 402-406.
    3. Mancarella, Pierluigi, 2014. "MES (multi-energy systems): An overview of concepts and evaluation models," Energy, Elsevier, vol. 65(C), pages 1-17.
    4. Pina, Eduardo A. & Lozano, Miguel A. & Serra, Luis M., 2018. "Thermoeconomic cost allocation in simple trigeneration systems including thermal energy storage," Energy, Elsevier, vol. 153(C), pages 170-184.
    5. Monica Carvalho & Dean L. Millar, 2012. "Concept Development of Optimal Mine Site Energy Supply," Energies, MDPI, vol. 5(11), pages 1-20, November.
    6. Jana, Kuntal & Ray, Avishek & Majoumerd, Mohammad Mansouri & Assadi, Mohsen & De, Sudipta, 2017. "Polygeneration as a future sustainable energy solution – A comprehensive review," Applied Energy, Elsevier, vol. 202(C), pages 88-111.
    7. Pina, Eduardo A. & Lozano, Miguel A. & Serra, Luis M., 2017. "Optimal operation and marginal costs in simple trigeneration systems including thermal energy storage," Energy, Elsevier, vol. 135(C), pages 788-798.
    8. Lozano, Miguel A. & Serra, Luis M. & Pina, Eduardo A., 2022. "Optimal design of trigeneration systems for buildings considering cooperative game theory for allocating production cost to energy services," Energy, Elsevier, vol. 261(PB).
    9. Andiappan, Viknesh & Ng, Denny K.S. & Tan, Raymond R., 2017. "Design Operability and Retrofit Analysis (DORA) framework for energy systems," Energy, Elsevier, vol. 134(C), pages 1038-1052.
    10. 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.
    11. 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.
    12. Calise, Francesco & de Notaristefani di Vastogirardi, Giulio & Dentice d'Accadia, Massimo & Vicidomini, Maria, 2018. "Simulation of polygeneration systems," Energy, Elsevier, vol. 163(C), pages 290-337.
    13. Cabral, Charlette & Andiappan, Viknesh & Aviso, Kathleen & Tan, Raymond, 2021. "Equipment size selection for optimizing polygeneration systems with reliability aspects," Energy, Elsevier, vol. 234(C).
    14. Miao Li & Hailin Mu & Huanan Li, 2013. "Analysis and Assessments of Combined Cooling, Heating and Power Systems in Various Operation Modes for a Building in China, Dalian," Energies, MDPI, vol. 6(5), pages 1-22, May.
    15. Lythcke-Jørgensen, Christoffer & Ensinas, Adriano Viana & Münster, Marie & Haglind, Fredrik, 2016. "A methodology for designing flexible multi-generation systems," Energy, Elsevier, vol. 110(C), pages 34-54.
    16. Pina, Eduardo A. & Lozano, Miguel A. & Serra, Luis M., 2018. "Allocation of economic costs in trigeneration systems at variable load conditions including renewable energy sources and thermal energy storage," Energy, Elsevier, vol. 151(C), pages 633-646.
    17. Pina, Eduardo A. & Lozano, Miguel A. & Serra, Luis M., 2021. "Assessing the influence of legal constraints on the integration of renewable energy technologies in polygeneration systems for buildings," Renewable and Sustainable Energy Reviews, Elsevier, vol. 149(C).
    18. Wegener, Moritz & Villarroel Schneider, J. & Malmquist, Anders & Isalgue, Antonio & Martin, Andrew & Martin, Viktoria, 2021. "Techno-economic optimization model for polygeneration hybrid energy storage systems using biogas and batteries," Energy, Elsevier, vol. 218(C).
    19. Stojiljković, Mirko M., 2017. "Bi-level multi-objective fuzzy design optimization of energy supply systems aided by problem-specific heuristics," Energy, Elsevier, vol. 137(C), pages 1231-1251.
    20. Mavromatidis, Georgios & Orehounig, Kristina & Carmeliet, Jan, 2018. "Uncertainty and global sensitivity analysis for the optimal design of distributed energy systems," Applied Energy, Elsevier, vol. 214(C), pages 219-238.

    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:116:y:2016:i:p2:p:1334-1347. 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.