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Robust models for the synthesis of flexible palm oil-based regional bioenergy supply chain

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  • Foo, Dominic C.Y.
  • Tan, Raymond R.
  • Lam, Hon Loong
  • Abdul Aziz, Mustafa Kamal
  • Klemeš, Jiří Jaromír

Abstract

EFB (Empty fruit bunch) is among the palm oil biomass residues that have been identified as the most abundant bioenergy resources in Southeast Asia. EFB has a good potential to meet the targeted share of renewable energy in this region. This work presents robust LP (linear programming) model to allow for the synthesis of EFB allocation networks that exhibit operational flexibility under multiple biomass supply scenarios. Such multiple scenarios may arise due to many uncertain factors, such as anticipated closure or expansion of mills. A MILP (mixed integer linear programming) extension of the model is then developed. Real life-based case studies of an industrial application are presented to illustrate the use of both variants of the model.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:energy:v:55:y:2013:i:c:p:68-73
    DOI: 10.1016/j.energy.2013.01.045
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    References listed on IDEAS

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    1. Perry, Simon & Klemeš, Jiří & Bulatov, Igor, 2008. "Integrating waste and renewable energy to reduce the carbon footprint of locally integrated energy sectors," Energy, Elsevier, vol. 33(10), pages 1489-1497.
    2. Sayigh, Ali, 1999. "Renewable energy -- the way forward," Applied Energy, Elsevier, vol. 64(1-4), pages 15-30, September.
    3. 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.
    4. Tan, Raymond R., 2011. "A general source-sink model with inoperability constraints for robust energy sector planning," Applied Energy, Elsevier, vol. 88(11), pages 3759-3764.
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    4. Lee, Ming Kwee & Hashim, Haslenda & Lim, Jeng Shiun & Taib, Mohd Rozainee, 2019. "Spatial planning and optimisation for virtual distribution of BioCNG derived from palm oil mill effluent to meet industrial energy demand," Renewable Energy, Elsevier, vol. 141(C), pages 526-540.
    5. Tang, J.P. & Lam, H.L. & Abdul Aziz, M.K. & Morad, N.A., 2017. "Palm biomass strategic resource managment – A competitive game analysis," Energy, Elsevier, vol. 118(C), pages 456-463.
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    9. Islam Hassanin & Matjaz Knez, 2022. "Managing Supply Chain Activities in the Field of Energy Production Focusing on Renewables," Sustainability, MDPI, vol. 14(12), pages 1-33, June.
    10. Zailan, Roziah & Lim, Jeng Shiun & Manan, Zainuddin Abdul & Alwi, Sharifah Rafidah Wan & Mohammadi-ivatloo, Behnam & Jamaluddin, Khairulnadzmi, 2021. "Malaysia scenario of biomass supply chain-cogeneration system and optimization modeling development: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 148(C).
    11. Sharifzadeh, Mahdi & Hien, Raymond Khoo Teck & Shah, Nilay, 2019. "China’s roadmap to low-carbon electricity and water: Disentangling greenhouse gas (GHG) emissions from electricity-water nexus via renewable wind and solar power generation, and carbon capture and sto," Applied Energy, Elsevier, vol. 235(C), pages 31-42.
    12. 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.
    13. Tan, Yue Dian & Lim, Jeng Shiun & Wan Alwi, Sharifah Rafidah, 2020. "Multi-objective optimal design for integrated palm oil mill complex with consideration of effluent elimination," Energy, Elsevier, vol. 202(C).
    14. Hoo Poh Ying & Cassendra Bong Phun Chien & Fan Yee Van, 2020. "Operational Management Implemented in Biofuel Upstream Supply Chain and Downstream International Trading: Current Issues in Southeast Asia," Energies, MDPI, vol. 13(7), pages 1-26, April.
    15. Fumi Harahap & Sylvain Leduc & Sennai Mesfun & Dilip Khatiwada & Florian Kraxner & Semida Silveira, 2019. "Opportunities to Optimize the Palm Oil Supply Chain in Sumatra, Indonesia," Energies, MDPI, vol. 12(3), pages 1-24, January.
    16. Yılmaz Balaman, Şebnem & Selim, Hasan, 2014. "A fuzzy multiobjective linear programming model for design and management of anaerobic digestion based bioenergy supply chains," Energy, Elsevier, vol. 74(C), pages 928-940.

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