An Application of GIS-Linked Biofuel Supply Chain Optimization Model for Various Transportation Network Scenarios in Northern Great Plains (NGP), USA

Abstract

Industrial oilseed and lignocellulosic crops can be produced on marginal lands. These advanced biofuel feedstock crops are critical to increase the production of renewable liquid fuels. However, rural areas with significant, existing amounts of available marginal cropland have spartan infrastructure, and it is costly to transport feedstocks and bioproducts within and from these regions. Therefore, it is important to consider varied feedstock and co-product transportation network options and supply chain optimization. This study applied a supply chain optimization model linked with geographical information system (GIS) developed using mixed-integer linear programming (MILP) for the northern Great Plains (NGP) region. An investigation on the influence of petroleum product pipeline usage and/or new infrastructure development on supply chain optimization was performed, and optimum routes were suggested. Four different multimodal transport routes of oilseed, biodiesel, livestock meal, and the capacities of biodiesel plants were evaluated for cost optimization. Selective rural rail infrastructure redevelopment of abandoned lines and strategically improving connectivity by adding 380 km of line could reduce biofuel transportation costs by up to 38%. Using existing petroleum pipeline in Montana reduced costs of biofuel transport; however, pipelines had little effect within the Dakotas. Railroad construction was the most effective mechanism to reduce transportation costs in both North and South Dakota. Variables such as transloading and construction costs, topographical constraints, and transportation network boundary could be used to further improve the optimization model and results.