Supply chain design and operational planning models for biomass to drop-in fuel production

• Published in: Biomass & bioenergy Vol. 58; pp. 238 - 250
• Main Authors: Zhang, Leilei, Hu, Guiping
• Format: Journal Article
• Language: English
• Published: Kidlington Elsevier Ltd 01-11-2013; Elsevier
• Subjects: Alternative fuels. Production and utilization; Applied sciences; biofuels; Biomass; Biorefinery; case studies; corn stover; economic feasibility; Energy; Exact sciences and technology; Facility allocation; feedstocks; fossils; fuel production; Fuels; linear programming; Miscellaneous; Natural energy; Operational planning; planning; pyrolysis; Second-generation biofuel; statistical models; Supply chain; Iowa; USA, Iowa; Supply chain; Operational planning; Biorefinery; Facility allocation; Second-generation biofuel; Biofuel; Biomass; Modeling; Design; Case study; Production; Models; Planning
• ISSN: 0961-9534; 1873-2909
• DOI: 10.1016/j.biombioe.2013.08.016

Renewable fuel is playing an increasingly important role as a substitute for fossil based energy. The US Department of Energy (DOE) has identified pyrolysis based platforms as promising biofuel production pathways. In this paper, we present a general biofuel supply chain model with a Mixed Integer Linear Programming (MILP) methodology to investigate the biofuel supply chain facility location, facility capacity at strategic levels, and biofuel production decisions at operational levels. In the model, we accommodate different biomass supplies and biofuel demands with biofuel supply shortage penalty and storage cost. The model is then applied to corn stover fast pyrolysis pathway with upgrading to hydrocarbon fuel since corn stover is the main feedstock for second generation biofuel production in the US Midwestern states. Numerical results illustrate unit cost for biofuel production, biomass, and biofuel allocation. The case study demonstrates the economic feasibility of producing biofuel from biomass at a commercial scale in Iowa.
•Supply chain design and operational planning are studied for biofuel production.•Mixed Integer Linear Programming methodology is utilized.•Facility location, capacity, and biofuel production decisions are analyzed.•Case study in Iowa demonstrates the applicability of the models.