(420a) Economic and Energetic Analysis of Biofuel Supply Chains
Rex T. L. Ng1,2 and Christos T. Maravelias1,2
1Department of Chemical and Biological Engineering and 2DOE
Great Lakes Bioenergy Research Center, University of Wisconsin-Madison,
The efficient and effective
transportation of lignocellulosic biomass is one of the critical challenges in
biofuel production, due to its low bulk density and durability properties. Generally,
in a biofuel supply chain (SC), baled biomass is either transported to a
biorefinery directly, or sent to a depot for densification prior to transporting
densified biomass to a biorefinery .
Many studies show the installation of depots in biofuel SCs offer better
economic performance in large scale biorefineries .
However, from an energy point of view, depots may be infeasible if the total primary
energy input (e.g., biomass harvesting and collection, depot operation, and baled
and densified biomass transportation) is higher than the energy content of biofuel.
To better understand what supply
chain configurations are preferable under different scenarios, we develop systematic
methods to compare the cost and energy efficiency of biofuel SC under different
configurations. We define a configuration as a combination of depot selection
(with and without depots) and transportation modes (truck and rail). The
analysis aims to provide some insights into the following questions: When
should we ship biomass directly to the biorefinery? When depot is economically
and energetically feasible? Which transportation mode yields low cost and high
energy efficiency? What is the trade-off between the improvement of densification
technology and cost or energy efficiency?
In this analysis, we consider corn
stover which is collected from 12 Midwest states in the US. We assume that corn
stover productivity is on an annual basis. A high moisture pelleting process 
is employed at the depot, while dilute acid pretreatment, separate hydrolysis
and fermentation are employed at the biochemical biorefinery .
Note that the analysis can be repeated using the proposed method for any
feedstock, technology, and type of productivity (annual, seasonal or monthly
basis). We estimate the minimum ethanol selling price (MESP) and total energy
input based assuming the feedstock collection area to be circular with the biorefinery
or the depot located at its center. When a combination of two or more
configurations leads to better economic or energy benefits (referred to in this
work as hybrid configuration), the average distance from depots in the
annular area to the biorefinery at the center is estimated.
The results show what reductions
in cost and energy input can be achieved through a hybrid configuration (Fig.
1A). From an economic point of view, direct shipment of baled corn stover
(orange region) is preferred if the distance between biorefinery and harvesting
site is lower than 155 km. Depots installation and truck transportation of
densified corn stover (blue region) are favorable if the distance ranges between
155 to 260 km; while rail transportation of densified corn stover (red region)
will only lead to better economic benefits at larger distance (≥260 km).
From an energy point of view, rail transportation of densified biomass is
always better than truck transportation. The depot installations with rail
transportation have lower total energy input values than those with truck
shipment of baled biomass if the distance is greater than 170 km. We further
discuss key cost and energy efficiency drivers: corn stover productivity,
biorefinery size, and densification efficiency. The MESP decreases with the
increase of productivity and biorefinery size (Fig. 1B). We will show how the
improvements in densification technologies can reduce transportation cost and
Finally, we will briefly discuss
how the finding of this study can be used to formulate tractable mixed-integer
programming (MIP) models for biofuel SCs operational planning, which account
for non-uniform biomass availability and other practical considerations. We
will show results from two case studies in southern Wisconsin.
Figure 1: (A) Hybrid configuration, and (B) MESP as a
function of biomass productivity and biorefinery capacity.
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