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Early-stage decision making approach for the selection of optimally integrated biorefinery processes

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  • Celebi, Ayse Dilan
  • Ensinas, Adriano Viana
  • Sharma, Shivom
  • Maréchal, François

Abstract

Lignocellulosic biorefineries are the best non-petroleum alternatives for a sustainable development. In the biorefinery process design, it is important to implement an algorithm that allows systematic generation, evaluation of energy conversion chains and making comparison of different pathways, ranking them according to different performance criteria. To achieve these goals, a methodology has been proposed to systematically define an ordered set of solutions using mixed integer linear programming models with integer cut constraints. In this study, we apply a systematic approach which adopts thermo-environomic optimization together with heat integration to assess the economic performance, environmental impact and energy requirement of several process options. Both sugars and syngas platforms are compared considering multiple products (energy services, valuable chemicals, fuels). A superstructure of different processes is developed and heat recovery potentials in the systems are analyzed using pinch analysis. Different pathways are evaluated and ranked according to different objective functions to understand the best combination of products and the synergies between them. Our results provide a set of candidate solutions according to minimum total cost and environmental impact as objective functions, considering benefit of heat integration between different pathways to obtain energy efficient biorefinery systems with improved process economics and reduced environmental impacts.

Suggested Citation

  • Celebi, Ayse Dilan & Ensinas, Adriano Viana & Sharma, Shivom & Maréchal, François, 2017. "Early-stage decision making approach for the selection of optimally integrated biorefinery processes," Energy, Elsevier, vol. 137(C), pages 908-916.
    • Handle: RePEc:eee:energy:v:137:y:2017:i:c:p:908-916
    DOI: 10.1016/j.energy.2017.03.080
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    References listed on IDEAS

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    1. Steubing, Bernhard & Ballmer, Isabel & Gassner, Martin & Gerber, Léda & Pampuri, Luca & Bischof, Sandro & Thees, Oliver & Zah, Rainer, 2014. "Identifying environmentally and economically optimal bioenergy plant sizes and locations: A spatial model of wood-based SNG value chains," Renewable Energy, Elsevier, vol. 61(C), pages 57-68.
    2. Hamelinck, Carlo N. & Faaij, André P.C. & den Uil, Herman & Boerrigter, Harold, 2004. "Production of FT transportation fuels from biomass; technical options, process analysis and optimisation, and development potential," Energy, Elsevier, vol. 29(11), pages 1743-1771.
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    1. Pavão, Leandro V. & Santos, Lucas F. & Oliveira, Cássia M. & Cruz, Antonio J.G. & Ravagnani, Mauro A.S.S. & Costa, Caliane B.B., 2023. "Flexible heat integration system in first-/second-generation ethanol production via screening pinch-based method and multiperiod model," Energy, Elsevier, vol. 271(C).
    2. Granacher, Julia & Nguyen, Tuong-Van & Castro-Amoedo, Rafael & Maréchal, François, 2022. "Overcoming decision paralysis—A digital twin for decision making in energy system design," Applied Energy, Elsevier, vol. 306(PA).
    3. Furtado Júnior, Juarez Corrêa & Palacio, José Carlos Escobar & Leme, Rafael Coradi & Lora, Electo Eduardo Silva & da Costa, José Eduardo Loureiro & Reyes, Arnaldo Martín Martínez & del Olmo, Oscar Alm, 2020. "Biorefineries productive alternatives optimization in the brazilian sugar and alcohol industry," Applied Energy, Elsevier, vol. 259(C).
    4. Bianca Köck & Anton Friedl & Sebastián Serna Loaiza & Walter Wukovits & Bettina Mihalyi-Schneider, 2023. "Automation of Life Cycle Assessment—A Critical Review of Developments in the Field of Life Cycle Inventory Analysis," Sustainability, MDPI, vol. 15(6), pages 1-40, March.

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