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Model-size reduction techniques for large-scale biomass production and supply networks

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  • Lam, Hon Loong
  • Klemeš, Jiří Jaromír
  • Kravanja, Zdravko

Abstract

This paper is concerned with developing several model-size reduction techniques for the analysis of large-scale renewable production and supply networks. They are (i) Reducing the connectivity in a biomass supply chain network, (ii) Eliminating unnecessary variables and constraints, (iii) Merging the collection centres. The proposed model-size reduction techniques brought computational time improvements of several magnitudes compared, with the high performance linear system solution techniques and still with a little loss in accuracy. When the methods are combined the time reductions are more significant. A proposed procedure for combining the methods can be implemented for any supply chain model with a large number of components.

Suggested Citation

  • Lam, Hon Loong & Klemeš, Jiří Jaromír & Kravanja, Zdravko, 2011. "Model-size reduction techniques for large-scale biomass production and supply networks," Energy, Elsevier, vol. 36(8), pages 4599-4608.
    • Handle: RePEc:eee:energy:v:36:y:2011:i:8:p:4599-4608
    DOI: 10.1016/j.energy.2011.03.036
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    2. Čuček, Lidija & Varbanov, Petar Sabev & Klemeš, Jiří Jaromír & Kravanja, Zdravko, 2012. "Total footprints-based multi-criteria optimisation of regional biomass energy supply chains," Energy, Elsevier, vol. 44(1), pages 135-145.
    3. Sharma, B. & Ingalls, R.G. & Jones, C.L. & Khanchi, A., 2013. "Biomass supply chain design and analysis: Basis, overview, modeling, challenges, and future," Renewable and Sustainable Energy Reviews, Elsevier, vol. 24(C), pages 608-627.
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    5. Potrč, Sanja & Nemet, Andreja & Čuček, Lidija & Varbanov, Petar Sabev & Kravanja, Zdravko, 2022. "Synthesis of a regenerative energy system – beyond carbon emissions neutrality," Renewable and Sustainable Energy Reviews, Elsevier, vol. 169(C).
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    7. Baglivi, Antonella & Fiorese, Giulia & Guariso, Giorgio & Uggè, Clara, 2015. "Valuing crop diversity in biodiesel production plans," Energy, Elsevier, vol. 93(P2), pages 2351-2362.
    8. De Laporte, Aaron V. & Weersink, Alfons J. & McKenney, Daniel W., 2016. "Effects of supply chain structure and biomass prices on bioenergy feedstock supply," Applied Energy, Elsevier, vol. 183(C), pages 1053-1064.
    9. Akhtari, Shaghaygh & Sowlati, Taraneh, 2020. "Hybrid optimization-simulation for integrated planning of bioenergy and biofuel supply chains," Applied Energy, Elsevier, vol. 259(C).
    10. Radovan Šomplák & Jiří Kropáč & Jaroslav Pluskal & Martin Pavlas & Boris Urbánek & Petra Vítková, 2022. "A Multi-Commodity Mathematical Modelling Approach—Hazardous Waste Treatment Infrastructure Planning in the Czech Republic," Sustainability, MDPI, vol. 14(6), pages 1-20, March.
    11. Ratkiewicz, Artur & Truong, Thanh N., 2012. "A canonical form of the complex reaction mechanism," Energy, Elsevier, vol. 43(1), pages 64-72.
    12. Osmani, Atif & Zhang, Jun, 2014. "Economic and environmental optimization of a large scale sustainable dual feedstock lignocellulosic-based bioethanol supply chain in a stochastic environment," Applied Energy, Elsevier, vol. 114(C), pages 572-587.
    13. Potrč, Sanja & Čuček, Lidija & Martin, Mariano & Kravanja, Zdravko, 2021. "Sustainable renewable energy supply networks optimization – The gradual transition to a renewable energy system within the European Union by 2050," Renewable and Sustainable Energy Reviews, Elsevier, vol. 146(C).
    14. Ng, Rex T.L. & Kurniawan, Daniel & Wang, Hua & Mariska, Brian & Wu, Wenzhao & Maravelias, Christos T., 2018. "Integrated framework for designing spatially explicit biofuel supply chains," Applied Energy, Elsevier, vol. 216(C), pages 116-131.
    15. He-Lambert, Lixia & English, Burton C. & Lambert, Dayton M. & Shylo, Oleg & Larson, James A. & Yu, T. Edward & Wilson, Bradly, 2018. "Determining a geographic high resolution supply chain network for a large scale biofuel industry," Applied Energy, Elsevier, vol. 218(C), pages 266-281.

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