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Supply chain optimisation of pyrolysis plant deployment using goal programming

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  • Nixon, J.D.
  • Dey, P.K.
  • Davies, P.A.
  • Sagi, S.
  • Berry, R.F.

Abstract

This paper presents a goal programming model to optimise the deployment of pyrolysis plants in Punjab, India. Punjab has an abundance of waste straw and pyrolysis can convert this waste into alternative bio-fuels, which will facilitate the provision of valuable energy services and reduce open field burning. A goal programming model is outlined and demonstrated in two case study applications: small scale operations in villages and large scale deployment across Punjab's districts. To design the supply chain, optimal decisions for location, size and number of plants, downstream energy applications and feedstocks processed are simultaneously made based on stakeholder requirements for capital cost, payback period and production cost of bio-oil and electricity. The model comprises quantitative data obtained from primary research and qualitative data gathered from farmers and potential investors. The Punjab district of Fatehgarh Sahib is found to be the ideal location to initially utilise pyrolysis technology. We conclude that goal programming is an improved method over more conventional methods used in the literature for project planning in the field of bio-energy. The model and findings developed from this study will be particularly valuable to investors, plant developers and municipalities interested in waste to energy in India and elsewhere.

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  • Nixon, J.D. & Dey, P.K. & Davies, P.A. & Sagi, S. & Berry, R.F., 2014. "Supply chain optimisation of pyrolysis plant deployment using goal programming," Energy, Elsevier, vol. 68(C), pages 262-271.
    • Handle: RePEc:eee:energy:v:68:y:2014:i:c:p:262-271
    DOI: 10.1016/j.energy.2014.02.058
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    Cited by:

    1. Roy, Poritosh & Dias, Goretty, 2017. "Prospects for pyrolysis technologies in the bioenergy sector: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 77(C), pages 59-69.
    2. Vlachokostas, Ch. & Michailidou, A.V. & Achillas, Ch., 2021. "Multi-Criteria Decision Analysis towards promoting Waste-to-Energy Management Strategies: A critical review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 138(C).
    3. Li, Qi & Hu, Guiping, 2014. "Supply chain design under uncertainty for advanced biofuel production based on bio-oil gasification," Energy, Elsevier, vol. 74(C), pages 576-584.
    4. Ivanov, Boyan & Stoyanov, Stoyan, 2016. "A mathematical model formulation for the design of an integrated biodiesel-petroleum diesel blends system," Energy, Elsevier, vol. 99(C), pages 221-236.
    5. Zhong, Jia & Yu, T. Edward & Larson, James A. & English, Burton C. & Fu, Joshua S. & Calcagno, James, 2016. "Analysis of environmental and economic tradeoffs in switchgrass supply chains for biofuel production," Energy, Elsevier, vol. 107(C), pages 791-803.
    6. Cinzia Colapinto & Raja Jayaraman & Simone Marsiglio, 2017. "Multi-criteria decision analysis with goal programming in engineering, management and social sciences: a state-of-the art review," Annals of Operations Research, Springer, vol. 251(1), pages 7-40, April.
    7. Wątróbski, Jarosław & Jankowski, Jarosław & Ziemba, Paweł & Karczmarczyk, Artur & Zioło, Magdalena, 2019. "Generalised framework for multi-criteria method selection," Omega, Elsevier, vol. 86(C), pages 107-124.
    8. Jones, Dylan & Florentino, Helenice & Cantane, Daniela & Oliveira, Rogerio, 2016. "An extended goal programming methodology for analysis of a network encompassing multiple objectives and stakeholders," European Journal of Operational Research, Elsevier, vol. 255(3), pages 845-855.
    9. Büyüközkan, Gülçin & Karabulut, Yağmur, 2017. "Energy project performance evaluation with sustainability perspective," Energy, Elsevier, vol. 119(C), pages 549-560.
    10. Nixon, J.D., 2016. "Designing and optimising anaerobic digestion systems: A multi-objective non-linear goal programming approach," Energy, Elsevier, vol. 114(C), pages 814-822.

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