The supply system model incorporates a combination of values and relationships obtained from other national laboratories, publications, consultation with academia and staff from the U.S. Department of Agriculture and the U.S. Forest Service, and published and unpublished INL data. Further details on the model are provided in Appendix F. Equipment lists for the feed handling and drying area, as well as other pertinent information, are provided in Appendix A and Appendix B. All purchased and installed equipment costs for this area are shown as zero for the plant economics because all of these capital costs are included in the delivered feedstock cost. 3.2 Area 200: Gasification The following section presents an overview, basis for design, and cost estimates for construction of the gasification facilities.

Logistics cost, the cost of moving feedstock or products, is a key component of the overall cost of recovering energy from biomass. In this study, we calculate for small- and large-project sizes, the relative cost of transportation by truck, rail, ship, and pipeline for three biomass feedstocks, by truck and pipeline for ethanol, and by transmission line for electrical power. Distance fixed costs (loading and unloading) and distance variable costs (transport, including power losses during transmission), are calculated for each biomass type and mode of transportation. Costs are normalized to a common basis of a giga Joules of biomass. The relative cost of moving products vs feedstock is an approximate measure of the incentive for location of biomass processing at the source of biomass, rather than at the point of ultimate consumption of produced energy. In general, the cost of transporting biomass is more than the cost of transporting its energy products. The gap in cost for transporting biomass vs power is significantly higher than the incremental cost of building and operating a power plant remote from a transmission grid. The cost of power transmission and ethanol transport by pipeline is highly dependent on scale of project. Transport of ethanol by truck has a lower cost than by pipeline up to capacities of 1800 t/d. The high cost of transshipment to a ship precludes shipping from being an economical mode of transport for distances less than 800 km (woodchips) and 1500 km (baled agricultural residues).

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Pioneer cellulosic biorefi neries across the United States rely on a conventional feedstock supply system based on one-year contracts with local growers, who harvest, locally store, and deliver feedstock in low-density format to the conversion facility. While the conventional system is designed for high biomass yield areas, pilot scale operations have experienced feedstock supply shortages and price volatilities due to reduced harvests and competition from other industries. Regional supply dependency and the inability to actively manage feedstock stability and quality, provide operational risks to the biorefi nery, which translate into higher investment risk. The advanced feedstock supply system based on a network of depots can mitigate many of these risks and enable wider supply system benefi ts. This paper compares the two concepts from a system-level perspective beyond mere logistic costs. It shows that while processing operations at the depot increase feedstock supply costs initially, they enable wider system benefi ts including supply risk reduction (leading to lower interest rates on loans), industry scale-up, conversion yield improvements, and reduced handling equipment and storage costs at the biorefi nery. When translating these benefi ts into cost reductions per liter of gasoline equivalent (LGE), we fi nd that total cost reductions between -$0.46 to -$0.21 per LGE for biochemical and -$0.32 to -$0.12 per LGE for thermochemical conversion pathways are possible. Naturally, these system level benefi ts will differ between individual actors along the feedstock supply chain. Further research is required with respect to depot sizing, location, and ownership structures. Published 2015. This article is a U.S. Government work and is in the public domain in the USA. Biofuels, Bioproducts and Biorefi ning published by Society of Industrial Chemistry and John Wiley & Sons Ltd. Supporting information may be found in the online version of this article.Keywords: biorefi nery; feedstock logistics; depot; bioeconomy; biofuel; advanced feedstock supply system 3 Targets are generally iterated between advancements in feedstock logistics and the development of more robust conversion systems. But it remains unclear if a conventional system will allow for the current goal to be met. Diff erent analyses 4-7 have shown that the conventional system fails to meet this supply cost target outside of highly productive regions and could encounter issues even in highly productive regions in some years due to inclement weather (e.g., drought, fl ood, heavy moisture during harvest, etc.). Th ese supply uncertainties increase risks, which could limit the biorefi nery concept from being broadly implemented.

This techno‐economic study investigates the production of ethanol and a higher alcohols coproduct by conversion of lignocelluosic biomass to syngas via indirect gasification followed by gas‐to‐liquids synthesis over a precommercial heterogeneous catalyst. The design specifies a processing capacity of 2,205 dry U.S. tons (2,000 dry metric tonnes) of woody biomass per day and incorporates 2012 research targets from NREL and other sources for technologies that will facilitate the future commercial production of cost‐competitive ethanol. Major processes include indirect steam gasification, syngas cleanup, and catalytic synthesis of mixed alcohols, and ancillary processes include feed handling and drying, alcohol separation, steam and power generation, cooling water, and other operations support utilities. The design and analysis is based on research at NREL, other national laboratories, and The Dow Chemical Company, and it incorporates commercial technologies, process modeling using Aspen Plus software, equipment cost estimation, and discounted cash flow analysis. The design considers the economics of ethanol production assuming successful achievement of internal research targets and nth‐plant costs and financing. The design yields 83.8 gallons of ethanol and 10.1 gallons of higher‐molecular‐weight alcohols per U.S. ton of biomass feedstock. A rigorous sensitivity analysis captures uncertainties in costs and plant performance. © 2012 American Institute of Chemical Engineers Environ Prog, 2012

The 2011 US Billion-Ton Update estimates that by 2030 there will be enough agricultural and forest resources to sustainably provide at least one billion dry tons of biomass annually, enough to displace approximately 30% of the country's current petroleum consumption. A portion of these resources are inaccessible at current cost targets with conventional feedstock supply systems because of their remoteness or low yields. Reliable analyses and projections of US biofuels production depend on assumptions about the supply system and biorefi nery capacity, which, in turn, depend upon economic value, feedstock logistics, and sustainability. A cross-functional team has examined combinations of advances in feedstock supply systems and biorefi nery capacities with rigorous design information, improved crop yield and agronomic practices, and improved estimates of sustainable Modeling and Analysis: Thermochemical conversion and refinery sizing Th e previous study did not consider woody biomass supply systems, account for variability in biomass ash content throughout the supply chain, or look at biorefi nery scale impacts for thermochemical conversion processes.In this paper, we analyze the infl uences of biorefi nery size, biomass supply system designs, and feedstock specifications on process economics and environmental sustainability metrics for southeastern (SE) US woody feedstocks converted into ethanol through a thermochemical process. Th e woody feedstocks include logging residues, which are low cost at the forest landing (i.e. roadside aft er harvest, chipping, and loading on a truck), but because of ash, may not be the least expensive for the conversion process. Because of this diff erence, this report also analyzes the impact of costs incurred between landing and the throat of the conversion system ('reactor throat'), including the costs of feedstock pre-processing. Th e analyses compared options of performing pre-processing operations at the landing or depot, such as ash removal, or letting the conversion process handle the upgrading of the material. Th e analyses support upgrading the material near the point of extraction rather than allowing the conversion facilities to handle the upgrades. Illustrative casesTh e SE USA is projected to be highly productive for the emerging biorefi nery industry. 4 One potential challenge with developing supply chains in the SE (Fig. 1) is that the resource base is made up of various types of herbaceous and woody biomass resources. Table 1 shows the primary biomass categories and potentially available quantities biomass availability. A previous report on biochemical refi nery capacity noted that under advanced feedstock logistic supply systems that include depots and pre-processing operations there are cost advantages that support larger biorefi neries up to 10 000 DMT/day facilities compared to the smaller 2000 DMT/day facilities. This report focuses on analyzing conventional versus advanced depot biomass supply systems for a thermochemical conversion and refi nery sizi...

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Biomass processing plants have a trade-off between two competing cost factors: as size increases, the economy of scale reduces per unit processing cost, while a longer biomass transportation distance increases the delivered cost of biomass. The competition between these cost factors leads to an optimum size at which the cost of energy produced from biomass is minimized. Four processing options are evaluated: power production via direct combustion and via biomass integrated gasification and combined cycle (BIGCC), ethanol production via fermentation, and syndiesel via Fischer Tropsch. The optimum size is calculated as a function of biomass gross yield (the biomass available to the processing plant from the total surrounding area) and processing cost (capital recovery and operating costs). Higher biomass gross yield and higher processing cost each lead to a higher optimum size. For most cases, a small relaxation in the objective of minimum cost, 3%, leads to a halving of plant size. Direct combustion and BIGCC each produce power, with BIGCC having a higher capital cost and conversion efficiency. When the delivered cost of biomass is high, BIGCC produces power at a lower cost than direct combustion. The crossover point at which this occurs is calculated as a function of the purchase cost of biomass and the biomass gross yield.