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Mathematical modeling of production and biorefinery of energy crops

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  • Wang, Lijun
  • Agyemang, Samuel A.
  • Amini, Hossein
  • Shahbazi, Abolghasem

Abstract

Mathematical models have been widely used to simulate all aspects of bioenergy production systems including the growth kinetics of energy crops, conversion processes, production economics, supply logistics and environmental impacts. There is limited commercial experience to produce and process energy crops at a large scale around the world. Those models can provide powerful tools to design a bioenergy system and evaluate its technical feasibility, economics and environmental impacts. A crop growth model can be used to estimate the yields of energy crops in a region under different growth conditions. A geographical information system (GIS) model can be used to maximize the energy production of energy crops by indentifying suitable land to grow them based on their specific characteristics and the current use of the land. A combination of process models and reaction kinetics provides advanced computational tools for the design and optimization of various biomass conversion processes. The biomass supply chain consists of multiple harvesting, storage, pre-processing and transport options. Mathematical models have been developed to analyze and optimize complex biomass supply systems. A life cycle assessment (LCA) model can be used to compare the environmental impacts of different biomass production and conversion technologies. Various mathematical models applied to bioenergy systems were reviewed. The challenges in mathematical modeling of bioenergy systems which include the difficulty in generalizing a bioenergy system, the lack of physical and chemical properties of various biomass, the complexity of multi-scale processes and the validation of the models were then discussed.

Suggested Citation

  • Wang, Lijun & Agyemang, Samuel A. & Amini, Hossein & Shahbazi, Abolghasem, 2015. "Mathematical modeling of production and biorefinery of energy crops," Renewable and Sustainable Energy Reviews, Elsevier, vol. 43(C), pages 530-544.
    • Handle: RePEc:eee:rensus:v:43:y:2015:i:c:p:530-544
    DOI: 10.1016/j.rser.2014.11.008
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    References listed on IDEAS

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    2. Famoso, F. & Prestipino, M. & Brusca, S. & Galvagno, A., 2020. "Designing sustainable bioenergy from residual biomass: Site allocation criteria and energy/exergy performance indicators," Applied Energy, Elsevier, vol. 274(C).
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    4. Sawant, S.S. & Gosavi, S.N. & Khadamkar, H.P. & Mathpati, C.S. & Pandit, Reena & Lali, A.M., 2019. "Energy efficient design of high depth raceway pond using computational fluid dynamics," Renewable Energy, Elsevier, vol. 133(C), pages 528-537.
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    6. Abolhasan Hashemisohi & Lijun Wang & Abolghasem Shahbazi, 2023. "Numerical Analysis of Tar and Syngas Formation during the Steam Gasification of Biomass in a Fluidized Bed," Energies, MDPI, vol. 16(14), pages 1-13, July.
    7. Sadhukhan, Jhuma & Lloyd, Jon R. & Scott, Keith & Premier, Giuliano C. & Yu, Eileen H. & Curtis, Tom & Head, Ian M., 2016. "A critical review of integration analysis of microbial electrosynthesis (MES) systems with waste biorefineries for the production of biofuel and chemical from reuse of CO2," Renewable and Sustainable Energy Reviews, Elsevier, vol. 56(C), pages 116-132.
    8. Espinoza Pérez, Andrea Teresa & Camargo, Mauricio & Narváez Rincón, Paulo César & Alfaro Marchant, Miguel, 2017. "Key challenges and requirements for sustainable and industrialized biorefinery supply chain design and management: A bibliographic analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 69(C), pages 350-359.
    9. Aalto, Mika & KC, Raghu & Korpinen, Olli-Jussi & Karttunen, Kalle & Ranta, Tapio, 2019. "Modeling of biomass supply system by combining computational methods – A review article," Applied Energy, Elsevier, vol. 243(C), pages 145-154.

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