IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v15y2022i23p9166-d992070.html
   My bibliography  Save this article

A Two-Tier Superstructure Model for Optimization of Microalgae-Based Biorefinery

Author

Listed:
  • Siwen Gu

    (School of Photoelectric Engineering, Changzhou Institute of Technology, Changzhou 213032, China
    Frontiers Science Center for Smart Materials Oriented Chemical Engineering, Institute of Chemical Process Systems Engineering, School of Chemical Engineering, Dalian University of Technology, Dalian 116024, China)

  • Jiaan Wang

    (School of Photoelectric Engineering, Changzhou Institute of Technology, Changzhou 213032, China)

  • Yu Zhuang

    (Frontiers Science Center for Smart Materials Oriented Chemical Engineering, Institute of Chemical Process Systems Engineering, School of Chemical Engineering, Dalian University of Technology, Dalian 116024, China)

Abstract

Microalgae have attracted great research interest as a feedstock for producing a wide range of end-products. However, recent studies show that the tight processing integration technology for microalgae-based biorefinery makes production less economical and even has a negative impact on sustainability. In this study, a new two-tier superstructure optimization design methodology is proposed to locate the optimal processing pathway. This model is developed based on the decomposition strategy and the relationship-based investigation, coupling an outer-tier structure with an inner-tier structure, wherein the outlet flows of the middle stages is relaxed and then an appropriate level of redundancy for designing the processing is provided. Two scenarios are developed to compare the most promising biorefinery configurations under two different design option favors. By solving the mixed integer nonlinear programming model with the objective functions of maximizing the yield of the desired products and maximizing the gross operating margin, the optimization results obtained show the ability of this framework to provide the promising configurations and cost-effectiveness of microalgae-based biorefinery. Compared with Scenario 1, the optimized solutions in Scenario 2 feature a gross operating margin increase up to 27.09% and an increase in product yield up to 25.00%. The proposed method improves the original huge computing scale and ensures economics without simplifying the processing pathways.

Suggested Citation

  • Siwen Gu & Jiaan Wang & Yu Zhuang, 2022. "A Two-Tier Superstructure Model for Optimization of Microalgae-Based Biorefinery," Energies, MDPI, vol. 15(23), pages 1-17, December.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:23:p:9166-:d:992070
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/15/23/9166/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/15/23/9166/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Dickson, Rofice & Liu, J. Jay, 2021. "A strategy for advanced biofuel production and emission utilization from macroalgal biorefinery using superstructure optimization," Energy, Elsevier, vol. 221(C).
    2. Rizwan, Muhammad & Lee, Jay H. & Gani, Rafiqul, 2015. "Optimal design of microalgae-based biorefinery: Economics, opportunities and challenges," Applied Energy, Elsevier, vol. 150(C), pages 69-79.
    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. Narula, Vishal & Khan, Mohd. Fazil & Negi, Ankit & Kalra, Shashvat & Thakur, Aman & Jain, Siddharth, 2017. "Low temperature optimization of biodiesel production from algal oil using CaO and CaO/Al2O3 as catalyst by the application of response surface methodology," Energy, Elsevier, vol. 140(P1), pages 879-884.
    2. Narula, Vishal & Thakur, Aman & Uniyal, Ankit & Kalra, Shashvat & Jain, Siddharth, 2017. "Process parameter optimization of low temperature transesterification of algae-Jatropha Curcas oil blend," Energy, Elsevier, vol. 119(C), pages 983-988.
    3. Lim, Juin Yau & Teng, Sin Yong & How, Bing Shen & Nam, KiJeon & Heo, SungKu & Máša, Vítězslav & Stehlík, Petr & Yoo, Chang Kyoo, 2022. "From microalgae to bioenergy: Identifying optimally integrated biorefinery pathways and harvest scheduling under uncertainties in predicted climate," Renewable and Sustainable Energy Reviews, Elsevier, vol. 168(C).
    4. González Álvarez, José Francisco & Gonzalo de Grado, Jesús, 2019. "Study of combustion in CO2-Capturing semi-closed Brayton cycle conditions," Energy, Elsevier, vol. 166(C), pages 1276-1290.
    5. Rodríguez, R. & Espada, J.J. & Moreno, J. & Vicente, G. & Bautista, L.F. & Morales, V. & Sánchez-Bayo, A. & Dufour, J., 2018. "Environmental analysis of Spirulina cultivation and biogas production using experimental and simulation approach," Renewable Energy, Elsevier, vol. 129(PB), pages 724-732.
    6. Ansub Khan, Mohammad & Abbas, Abiha & Dickson, Rofice, 2023. "A strategy for commercialization of macroalga biorefineries," Renewable and Sustainable Energy Reviews, Elsevier, vol. 187(C).
    7. Nicoletti, Jack & Ning, Chao & You, Fengqi, 2019. "Incorporating agricultural waste-to-energy pathways into biomass product and process network through data-driven nonlinear adaptive robust optimization," Energy, Elsevier, vol. 180(C), pages 556-571.
    8. Marwa G. Saad & Noura S. Dosoky & Mohamed S. Zoromba & Hesham M. Shafik, 2019. "Algal Biofuels: Current Status and Key Challenges," Energies, MDPI, vol. 12(10), pages 1-22, May.
    9. Wu, Wei & Wang, Po-Han & Lee, Duu-Jong & Chang, Jo-Shu, 2017. "Global optimization of microalgae-to-biodiesel chains with integrated cogasification combined cycle systems based on greenhouse gas emissions reductions," Applied Energy, Elsevier, vol. 197(C), pages 63-82.
    10. Simona Armeli Minicante & Lucia Bongiorni & Amelia De Lazzari, 2022. "Bio-Based Products from Mediterranean Seaweeds: Italian Opportunities and Challenges for a Sustainable Blue Economy," Sustainability, MDPI, vol. 14(9), pages 1-22, May.
    11. Zhang, Quanguo & Nurhayati, & Cheng, Chieh-Lun & Nagarajan, Dillirani & Chang, Jo-Shu & Hu, Jianjun & Lee, Duu-Jong, 2017. "Carbon capture and utilization of fermentation CO2: Integrated ethanol fermentation and succinic acid production as an efficient platform," Applied Energy, Elsevier, vol. 206(C), pages 364-371.
    12. Cuevas-Castillo, Gabriela A. & Navarro-Pineda, Freddy S. & Baz Rodríguez, Sergio A. & Sacramento Rivero, Julio C., 2020. "Advances on the processing of microalgal biomass for energy-driven biorefineries," Renewable and Sustainable Energy Reviews, Elsevier, vol. 125(C).
    13. Fasahati, Peyman & Wu, Wenzhao & Maravelias, Christos T., 2019. "Process synthesis and economic analysis of cyanobacteria biorefineries: A superstructure-based approach," Applied Energy, Elsevier, vol. 253(C), pages 1-1.
    14. González Álvarez, José Francisco & Gonzalo de Grado, Jesús, 2016. "Study of a modern industrial low pressure turbine for electricity production employed in oxy-combustion cycles with CO2 capture purposes," Energy, Elsevier, vol. 107(C), pages 734-747.
    15. Gnansounou, Edgard & Kenthorai Raman, Jegannathan, 2016. "Life cycle assessment of algae biodiesel and its co-products," Applied Energy, Elsevier, vol. 161(C), pages 300-308.
    16. Cruce, Jesse R. & Quinn, Jason C., 2019. "Economic viability of multiple algal biorefining pathways and the impact of public policies," Applied Energy, Elsevier, vol. 233, pages 735-746.
    17. Judd, S.J. & Al Momani, F.A.O. & Znad, H. & Al Ketife, A.M.D., 2017. "The cost benefit of algal technology for combined CO2 mitigation and nutrient abatement," Renewable and Sustainable Energy Reviews, Elsevier, vol. 71(C), pages 379-387.
    18. Omar Morsy & Farzad Hourfar & Qinqin Zhu & Ali Almansoori & Ali Elkamel, 2023. "A Superstructure Mixed-Integer Nonlinear Programming Optimization for the Optimal Processing Pathway Selection of Sludge-to-Energy Technologies," Sustainability, MDPI, vol. 15(5), pages 1-34, February.
    19. Liu, J. Jay & Dickson, Rofice & Niaz, Haider & Van Hal, Jaap W. & Dijkstra, J.W. & Fasahati, Peyman, 2022. "Production of fuels and chemicals from macroalgal biomass: Current status, potentials, challenges, and prospects," Renewable and Sustainable Energy Reviews, Elsevier, vol. 169(C).
    20. Kate Kim & Farzad Hourfar & Abdul Halim Bin Abdul Razik & Muhammad Rizwan & Ali Almansoori & Michael Fowler & Ali Elkamel, 2023. "Importance of Microalgae and Municipal Waste in Bioenergy Products Hierarchy—Integration of Biorefineries for Microalgae and Municipal Waste Processing: A Review," Energies, MDPI, vol. 16(17), pages 1-39, September.

    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:gam:jeners:v:15:y:2022:i:23:p:9166-:d:992070. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.