IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v180y2019icp556-571.html
   My bibliography  Save this article

Incorporating agricultural waste-to-energy pathways into biomass product and process network through data-driven nonlinear adaptive robust optimization

Author

Listed:
  • Nicoletti, Jack
  • Ning, Chao
  • You, Fengqi

Abstract

A biomass product and process network that displays how organic waste and other non-traditional biomass feedstocks may be converted into useful bioproducts and biofuels is a necessary addition to the field of biomass conversion and utilization. We develop a processing network of 216 technologies and 172 materials/compounds that contains conversion pathways of agricultural and organic waste biomass sources, such as food peels, animal manure, and grease. To examine the effectiveness and economic feasibility of these conversion pathways, the biomass product and process network is optimized for return on investment. The resulting problem is a data-driven two-stage adaptive robust mixed-integer nonlinear fractional program, which was effectively solved via a tailored optimization algorithm. The proposed approach is applied to two case studies in which traditional agricultural feedstocks are used alongside biological and agricultural waste feedstocks. The selected feedstocks were used to satisfy and, in some cases, even exceed demand for selected products. The optimal pathways have returns on investment of 26.1% and 6.2%, with utilized conversion technologies ranging from hydrocracking to microwave hydrodiffusion. In both cases, we find that profitable processing pathways are utilized at maximum capacities to increase return on investment. Specifically, in the case study where orange peel wastes are used to produce pectin, we find that this pathway is highly profitable at the given market price. The two cases that are run using the proposed model are then compared to additional cases to display differences that arise when uncertainty is not considered and the objective function of the model is changed.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:energy:v:180:y:2019:i:c:p:556-571
    DOI: 10.1016/j.energy.2019.05.096
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544219309739
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2019.05.096?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

    for a different version of it.

    References listed on IDEAS

    as
    1. Fengqi You & Ignacio Grossmann, 2013. "Multicut Benders decomposition algorithm for process supply chain planning under uncertainty," Annals of Operations Research, Springer, vol. 210(1), pages 191-211, November.
    2. Balaman, Şebnem Yılmaz & Selim, Hasan, 2014. "A network design model for biomass to energy supply chains with anaerobic digestion systems," Applied Energy, Elsevier, vol. 130(C), pages 289-304.
    3. 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.
    4. John M. Mulvey & Robert J. Vanderbei & Stavros A. Zenios, 1995. "Robust Optimization of Large-Scale Systems," Operations Research, INFORMS, vol. 43(2), pages 264-281, April.
    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. Yi Xiang & Yuke Ding & Shaohua Yin, 2024. "Does Agricultural Science and Technological Innovation Always Boost Farmers’ Income? Evidence from China," Agriculture, MDPI, vol. 14(12), pages 1-19, November.
    3. Miltiadis D. Lytras & Kwok Tai Chui, 2019. "The Recent Development of Artificial Intelligence for Smart and Sustainable Energy Systems and Applications," Energies, MDPI, vol. 12(16), pages 1-7, August.
    4. Zhao, Ning & You, Fengqi, 2022. "Sustainable power systems operations under renewable energy induced disjunctive uncertainties via machine learning-based robust optimization," Renewable and Sustainable Energy Reviews, Elsevier, vol. 161(C).
    5. Hugo Guzmán-Bello & Iosvani López-Díaz & Miguel Aybar-Mejía & Jose Atilio de Frias, 2022. "A Review of Trends in the Energy Use of Biomass: The Case of the Dominican Republic," Sustainability, MDPI, vol. 14(7), pages 1-27, March.
    6. David Palma-Heredia & Manel Poch & Miquel À. Cugueró-Escofet, 2020. "Implementation of a Decision Support System for Sewage Sludge Management," Sustainability, MDPI, vol. 12(21), pages 1-18, October.
    7. Xu, Xiao & Hu, Weihao & Du, Yuefang & Liu, Wen & Liu, Zhou & Huang, Qi & Chen, Zhe, 2020. "Robust chance-constrained gas management for a standalone gas supply system based on wind energy," Energy, Elsevier, vol. 212(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. 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. J. F. F. Almeida & S. V. Conceição & L. R. Pinto & B. R. P. Oliveira & L. F. Rodrigues, 2022. "Optimal sales and operations planning for integrated steel industries," Annals of Operations Research, Springer, vol. 315(2), pages 773-790, August.
    3. Jihee Han & KwangSup Shin, 2016. "Evaluation mechanism for structural robustness of supply chain considering disruption propagation," International Journal of Production Research, Taylor & Francis Journals, vol. 54(1), pages 135-151, January.
    4. Tsai, Jung-Fa, 2007. "An optimization approach for supply chain management models with quantity discount policy," European Journal of Operational Research, Elsevier, vol. 177(2), pages 982-994, March.
    5. Antonio G. Martín & Manuel Díaz-Madroñero & Josefa Mula, 2020. "Master production schedule using robust optimization approaches in an automobile second-tier supplier," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 28(1), pages 143-166, March.
    6. Sebastian Rachuba & Brigitte Werners, 2017. "A fuzzy multi-criteria approach for robust operating room schedules," Annals of Operations Research, Springer, vol. 251(1), pages 325-350, April.
    7. 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).
    8. McKenna, Claire & Chalabi, Zaid & Epstein, David & Claxton, Karl, 2010. "Budgetary policies and available actions: A generalisation of decision rules for allocation and research decisions," Journal of Health Economics, Elsevier, vol. 29(1), pages 170-181, January.
    9. Golpîra, Hêriş, 2020. "Smart Energy-Aware Manufacturing Plant Scheduling under Uncertainty: A Risk-Based Multi-Objective Robust Optimization Approach," Energy, Elsevier, vol. 209(C).
    10. Ulrich Dorndorf & Florian Jaehn & Erwin Pesch, 2017. "Flight gate assignment and recovery strategies with stochastic arrival and departure times," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 39(1), pages 65-93, January.
    11. Tsao, Yu-Chung & Thanh, Vo-Van & Lu, Jye-Chyi, 2019. "Multiobjective robust fuzzy stochastic approach for sustainable smart grid design," Energy, Elsevier, vol. 176(C), pages 929-939.
    12. Chen, Andrew N.K. & Goes, Paulo B. & Gupta, Alok & Marsden, James R., 2006. "Heuristics for selecting robust database structures with dynamic query patterns," European Journal of Operational Research, Elsevier, vol. 168(1), pages 200-220, January.
    13. Golpîra, Hêriş & Khan, Syed Abdul Rehman, 2019. "A multi-objective risk-based robust optimization approach to energy management in smart residential buildings under combined demand and supply uncertainty," Energy, Elsevier, vol. 170(C), pages 1113-1129.
    14. Gilani, H. & Sahebi, H. & Oliveira, Fabricio, 2020. "Sustainable sugarcane-to-bioethanol supply chain network design: A robust possibilistic programming model," Applied Energy, Elsevier, vol. 278(C).
    15. Erfan Hassannayebi & Seyed Hessameddin Zegordi & Mohammad Reza Amin-Naseri & Masoud Yaghini, 2017. "Train timetabling at rapid rail transit lines: a robust multi-objective stochastic programming approach," Operational Research, Springer, vol. 17(2), pages 435-477, July.
    16. De Rosa, Vincenzo & Gebhard, Marina & Hartmann, Evi & Wollenweber, Jens, 2013. "Robust sustainable bi-directional logistics network design under uncertainty," International Journal of Production Economics, Elsevier, vol. 145(1), pages 184-198.
    17. Bastian, Nathaniel D. & Lunday, Brian J. & Fisher, Christopher B. & Hall, Andrew O., 2020. "Models and methods for workforce planning under uncertainty: Optimizing U.S. Army cyber branch readiness and manning," Omega, Elsevier, vol. 92(C).
    18. Hosseini-Motlagh, Seyyed-Mahdi & Samani, Mohammad Reza Ghatreh & Homaei, Shamim, 2020. "Toward a coordination of inventory and distribution schedules for blood in disasters," Socio-Economic Planning Sciences, Elsevier, vol. 72(C).
    19. Mavrotas, George & Figueira, José Rui & Siskos, Eleftherios, 2015. "Robustness analysis methodology for multi-objective combinatorial optimization problems and application to project selection," Omega, Elsevier, vol. 52(C), pages 142-155.
    20. Munoz, Francisco D. & van der Weijde, Adriaan Hendrik & Hobbs, Benjamin F. & Watson, Jean-Paul, 2017. "Does risk aversion affect transmission and generation planning? A Western North America case study," Energy Economics, Elsevier, vol. 64(C), pages 213-225.

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    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:180:y:2019:i:c:p:556-571. 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.