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Optimal running and planning of a biomass-based energy production process

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  • Bruglieri, Maurizio
  • Liberti, Leo

Abstract

We propose mathematical programming models for solving problems arising from planning and running an energy production process based on burning biomasses. The models take into account different aspects of the problem: determination of the biomasses to produce and/or buy, transportation decisions to convey the materials to the respective plants, and plant site locations. Whereas the "running model" is linear, we propose two "planning models", both of which are mixed-integer nonlinear programming problems. We show that a spatial branch-and-bound type algorithm applied to them is guaranteed to converge to an exact optimum in a finite number of steps.

Suggested Citation

  • Bruglieri, Maurizio & Liberti, Leo, 2008. "Optimal running and planning of a biomass-based energy production process," Energy Policy, Elsevier, vol. 36(7), pages 2430-2438, July.
    • Handle: RePEc:eee:enepol:v:36:y:2008:i:7:p:2430-2438
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    References listed on IDEAS

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    Cited by:

    1. Leo Liberti, 2015. "Optimization and sustainable development," Computational Management Science, Springer, vol. 12(3), pages 371-395, July.
    2. Daniela Guericke & Ignacio Blanco & Juan M. Morales & Henrik Madsen, 2020. "A two-phase stochastic programming approach to biomass supply planning for combined heat and power plants," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 42(4), pages 863-900, December.
    3. Namuli, R. & Jaumard, B. & Awasthi, A. & Pillay, P., 2013. "Optimisation of biomass waste to energy conversion systems for rural grid-connected applications," Applied Energy, Elsevier, vol. 102(C), pages 1013-1021.
    4. Pablo Benalcazar & Jacek Kamiński & Karol Stós, 2022. "An Integrated Approach to Long-Term Fuel Supply Planning in Combined Heat and Power Systems," Energies, MDPI, vol. 15(22), pages 1-22, November.
    5. Yunusoglu, Pinar & Ozsoydan, Fehmi Burcin & Bilgen, Bilge, 2024. "A machine learning-based two-stage approach for the location of undesirable facilities in the biomass-to-bioenergy supply chain," Applied Energy, Elsevier, vol. 362(C).
    6. Shadbahr, Jalil & Ebadian, Mahmood & Gonzales-Calienes, Giovanna & Kannangara, Miyuru & Ahmadi, Leila & Bensebaa, Farid, 2022. "Impact of waste management and conversion technologies on cost and carbon footprint - Case studies in rural and urban cities," Renewable and Sustainable Energy Reviews, Elsevier, vol. 168(C).
    7. Pantaleo, Antonio & Candelise, Chiara & Bauen, Ausilio & Shah, Nilay, 2014. "ESCO business models for biomass heating and CHP: Profitability of ESCO operations in Italy and key factors assessment," Renewable and Sustainable Energy Reviews, Elsevier, vol. 30(C), pages 237-253.
    8. Nunes, L.J.R. & Causer, T.P. & Ciolkosz, D., 2020. "Biomass for energy: A review on supply chain management models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 120(C).
    9. Cai, Y.P. & Huang, G.H. & Yang, Z.F. & Tan, Q., 2009. "Identification of optimal strategies for energy management systems planning under multiple uncertainties," Applied Energy, Elsevier, vol. 86(4), pages 480-495, April.
    10. Nasiri, Fuzhan & Zaccour, Georges, 2009. "An exploratory game-theoretic analysis of biomass electricity generation supply chain," Energy Policy, Elsevier, vol. 37(11), pages 4514-4522, November.

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