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Stochastic Programming Model Integrating Pyrolysis Byproducts in the Design of Bioenergy Supply Chains

Author

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  • Kolton Keith

    (Mechanical Engineering Department and Texas Sustainable Energy Research Institute, The University of Texas at San Antonio, One UTSA Circle, San Antonio, TX 78249, USA)

  • Krystel K. Castillo-Villar

    (Mechanical Engineering Department and Texas Sustainable Energy Research Institute, The University of Texas at San Antonio, One UTSA Circle, San Antonio, TX 78249, USA)

Abstract

Biomass is an abundant resource for energy production and it has gained attention as a mainstream option to meet increasing energy demands. Pyrolysis has been one of the most prevalent thermochemical processes for biomass conversion. In the pyrolysis process, the biomass decomposes into three byproducts: bio-oil (60–75%), biochar (15–25%), and syngas (10–20%), depending on the feedstock and its composition. The energy required to convert the biomass varies depending on the levels of cellulose, hemicellulose, and lignin. This work proposes a novel two-stage stochastic model that designs an efficient biomass supply chain mindful of the trade-offs between pyrolysis byproducts (bioethanol and biochar). Remarkably, the model integrates biomass quality-related costs associated with moisture and ash content such as the energy consumption of preprocessing equipment and boiler maintenance due to excess ash. Biomass quality directly affects the production yield as well as the total cost of production and distribution. The results from our case study indicate a shortage of biomass from the suppliers to fulfill the demand for biochar from the power plants and bioethanol from the cities. Furthermore, the bioethanol price has the most impact on the total supply chain according to our sensitivity analysis.

Suggested Citation

  • Kolton Keith & Krystel K. Castillo-Villar, 2023. "Stochastic Programming Model Integrating Pyrolysis Byproducts in the Design of Bioenergy Supply Chains," Energies, MDPI, vol. 16(10), pages 1-17, May.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:10:p:4070-:d:1146163
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    References listed on IDEAS

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    1. Huang, Yongxi & Chen, Chien-Wei & Fan, Yueyue, 2010. "Multistage optimization of the supply chains of biofuels," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 46(6), pages 820-830, November.
    2. Zhao, Peitao & Shen, Yafei & Ge, Shifu & Chen, Zhenqian & Yoshikawa, Kunio, 2014. "Clean solid biofuel production from high moisture content waste biomass employing hydrothermal treatment," Applied Energy, Elsevier, vol. 131(C), pages 345-367.
    3. Mario Aboytes-Ojeda & Krystel K. Castillo-Villar & Sandra D. Eksioglu, 2022. "Modeling and optimization of biomass quality variability for decision support systems in biomass supply chains," Annals of Operations Research, Springer, vol. 314(2), pages 319-346, July.
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    Cited by:

    1. Jan Banaś & Katarzyna Utnik-Banaś & Stanisław Zięba, 2024. "Optimizing Biomass Supply Chains to Power Plants under Ecological and Social Restrictions: Case Study from Poland," Energies, MDPI, vol. 17(13), pages 1-15, June.

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