Stochastic optimization of cellulosic biofuel supply chain incorporating feedstock yield uncertainty

Journal Article · Fri Mar 15 00:00:00 EDT 2019 · Energy Procedia (Online)

DOI:https://doi.org/10.1016/j.egypro.2019.01.245· OSTI ID:1781085

Sharma, Bijay P. ^[1]; Yu, T. Edward ^[2]; English, Burton C. ^[2]; Boyer, Christopher N. ^[2]; Larson, James A. ^[2]

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1. Univ. of Tennessee, Knoxville, TN (United States); University of Tennessee
2. Univ. of Tennessee, Knoxville, TN (United States)

The global goal to reduce dependence on fossil fuels and to mitigate greenhouse gas emissions has resulted in research focused on environment friendly and socio-economically sustainable renewable energy sources. However, commercial production of bio-energy is constrained by biomass supply uncertainty and associated costs. This study presents an integrated approach to determining the optimal biofuel supply chain considering biomass yield uncertainty. A two-stage stochastic mixed integer linear programming is utilized to minimize the expected system cost while incorporating yield uncertainty in the strategic level decisions related to biomass production and biorefinery investment. Applicability of the stochastic model is illustrated through a case study of switchgrass-based biofuel in west Tennessee.

• Research Organization: Univ. of Tennessee, Knoxville, TN (United States)
• Sponsoring Organization: USDOE Office of Energy Efficiency and Renewable Energy (EERE), Transportation Office. Bioenergy Technologies Office
• Grant/Contract Number: EE0006639
• OSTI ID: 1781085
• Journal Information: Energy Procedia (Online), Journal Name: Energy Procedia (Online) Vol. 158; ISSN 1876-6102
• Publisher: Elsevier
• Country of Publication: United States
• Language: English

Related Subjects

09 BIOMASS FUELS
land use
stochastic
strategic decision
switchgrass
uncertainty