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Optimizing the Biofuels Infrastructure: Transportation Networks and Biorefinery Locations in Illinois

In: Handbook of Bioenergy Economics and Policy

Author

Listed:
  • Seungmo Kang

    (University of Illinois)

  • Hayri Önal

    (University of Illinois)

  • Yanfeng Ouyang

    (University of Illinois)

  • Jürgen Scheffran

    (University of Illinois
    Hamburg University)

  • Ü Deniz Tursun

    (University of Illinois)

Abstract

Growing biofuel mandates pose considerable challenges to the infrastructure needed across all stages of the supply chain − from crop production, feedstock harvesting, storage, transportation, and processing to biofuel distribution and use. This chapter focuses on the biofuel transportation and distribution network infrastructure, using Illinois as a case study. Building on an optimal land use allocation model for feedstock production, a mathematical programming model is used to determine optimal locations and capacities of biorefineries, delivery of bioenergy crops to biorefineries, and processing and distribution of ethanol and co-products (DDGS). The model aims to minimize total system costs in a multiyear planning horizon for the period of 2007–2022. Certain locations may be more suitable for corn and corn stover-based ethanol plants, others more for producing ethanol using perennial grasses (miscanthus)

Suggested Citation

  • Seungmo Kang & Hayri Önal & Yanfeng Ouyang & Jürgen Scheffran & Ü Deniz Tursun, 2010. "Optimizing the Biofuels Infrastructure: Transportation Networks and Biorefinery Locations in Illinois," Natural Resource Management and Policy, in: Madhu Khanna & Jürgen Scheffran & David Zilberman (ed.), Handbook of Bioenergy Economics and Policy, chapter 0, pages 151-173, Springer.
    • Handle: RePEc:spr:nrmchp:978-1-4419-0369-3_10
    DOI: 10.1007/978-1-4419-0369-3_10
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    Citations

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    Cited by:

    1. Kumarappan, Subbu & Joshi, Satish V., 2012. "Optimal biomass-harvesting model for biobutanol biorefineries," 2012 Annual Meeting, August 12-14, 2012, Seattle, Washington 124717, Agricultural and Applied Economics Association.
    2. Wang, Xiaolei & Ouyang, Yanfeng & Yang, Hai & Bai, Yun, 2013. "Optimal biofuel supply chain design under consumption mandates with renewable identification numbers," Transportation Research Part B: Methodological, Elsevier, vol. 57(C), pages 158-171.
    3. Mohammad Marufuzzaman & Sandra Duni Ekşioğlu, 2017. "Designing a Reliable and Dynamic Multimodal Transportation Network for Biofuel Supply Chains," Transportation Science, INFORMS, vol. 51(2), pages 494-517, May.
    4. Bai, Yun & Ouyang, Yanfeng & Pang, Jong-Shi, 2016. "Enhanced models and improved solution for competitive biofuel supply chain design under land use constraints," European Journal of Operational Research, Elsevier, vol. 249(1), pages 281-297.
    5. Jason Wood & James Nolan, 2021. "Plant location decisions in the ethanol industry: a dynamic and spatial analysis," Computational Economics, Springer;Society for Computational Economics, vol. 58(1), pages 103-132, June.
    6. Wang, Xin & Lim, Michael K. & Ouyang, Yanfeng, 2017. "Food-energy-environment trilemma: Policy impacts on farmland use and biofuel industry development," Energy Economics, Elsevier, vol. 67(C), pages 35-48.
    7. Bai, Yun & Ouyang, Yanfeng & Pang, Jong-Shi, 2012. "Biofuel supply chain design under competitive agricultural land use and feedstock market equilibrium," Energy Economics, Elsevier, vol. 34(5), pages 1623-1633.
    8. Chao Bi & Jingjing Zeng & Wanli Zhang & Yonglin Wen, 2020. "Modelling the Coevolution of the Fuel Ethanol Industry, Technology System, and Market System in China: A History-Friendly Model," Energies, MDPI, vol. 13(5), pages 1-26, February.
    9. Ripplinger, David, 2017. "Future US Ethanol Transportation Network Design and Performance," 2017 Annual Meeting, July 30-August 1, Chicago, Illinois 258479, Agricultural and Applied Economics Association.

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