Biorefinery scale-up is a common approach to reducing costs by capital intensification. This approach has been proven in the fossil fuel industry where the average US coal plant generates over 227 gigawatts (in compari­son, the energy production rate of a 100 million gallon (379 million liter) per year ethanol plant is equivalent to about 280 megawatts). Although biorefineries can benefit from economies of scale, they also suffer from diseconomies of scale that limits their ability to increase capacity (Wright and Brown, 2007b). Here we discuss the impact of scale on biorefinery costs and strategies to mitigate diseconomies of scale.

Product costs consist of three major categories: capital, operating, and feedstock costs. Capital costs include equipment depreciation, taxes, and the return on investment required to recoup the initial capital with a desired profit. Operating costs are expenses required to operate the facility such as
labor and maintenance. Finally, feedstock costs are spent to acquire requisite raw materials. These costs are difficult to estimate, which has led to the development of sophisticated tools that depend on prior knowledge to determine costs for novel processes.

Product costs are a function of a plant’s capacity. The relationship between a plant’s capacity and the various cost components can be approximated with power law equations (Wright and Brown, 2007b):

[2.3]

where C, O, and F stand for capital, operating, and feedstock costs. Variables with subscript 0 correspond to known costs and capacities for a baseline facility. The scale factors n, m, and p relate to the scaling behavior of each cost component. Scale factor values vary between technologies, but there are commonly accepted values employed in industry for major facility categories. In the thermochemical industry, n is commonly assumed as 0.63 or 0.7, m is approximately linear (between 0.9 and 1), and p can be either smaller or greater than 1. In general, scale factors that are less than unity represent product costs that decrease with plant capacity. For example, a 0.7 scale factor suggests that every 1% increase in capacity incurs a smaller 0.7% increase in capital costs. Biorefineries are unique in the fuel industry for having large p scale factors (in the order of 1.5), meaning that feedstock costs increase with plant capacity. Figure 2.4 shows unit capital costs of corn ethanol biorefineries versus plant capacity.

Economies of scale are strong incentive to build large biorefineries. However, beyond an optimal capacity, feedstock transportation costs increase at a faster rate than reductions in capital costs. Engineers are evaluating distributed processing strategies to alleviate transport costs.

Distributed processing is the notion that small-scale facilities pretreat biomass prior to shipping to a large, upgrading facility. This concept yields several economic benefits: reduced storage space requirement, slower biomass degradation rates, and improved energy densities. Pretreatment intensity varies from simple drying and grinding to torrefaction or even pyrolysis.

Biomass drying and grinding removes moisture, which can otherwise increase biomass degradation rates by encouraging microbial activity. Grinding increases the feedstock bulk density and allows for pelletization, which is the mechanical compression of loose material into dense pellets. Torrefaction increases the energy density by further lowering the moisture content, releasing low energy value compounds, and slightly modifying biomass structure. Torrefied biomass is hydrophobic, which makes it

ideal for long-term storage. Torrefaction allows for efficient biomass pulverization, which increases the energy density. Finally, biomass pyrolysis, or liquefaction techniques, convert biomass into a liquid form with high material density. Pyrolysis oil, combined with biomass char materials, is an energy dense material that could be shipped at low cost, but corrosion remains a challenge.

Distributed processing in specialized, small-scale facilities or depots will play an important role in a large-scale biorefinery industry (Wright and Brown, 2007b). Without pretreatment, biomass transportation will be expensive and increase the number of trucks delivering material to central facilities. Unfortunately, distributed processing faces the classical ‘chicken or egg’ problem: without large-scale facilities there is a limited market for pretreated biomass feedstock, and without distributed processing facilities may find it difficult to achieve large-scale capacities. Pretreatment technologies may initially feed into the existing fossil fuel infrastructure by delivering torrefied biomass to coal plants or bio-oils to oil refineries. However, some technical and economic hurdles for this alternative remain unsolved.