Printed on paper containing at least 50% wastepaper, including 10% post consumer waste.iii Executive SummaryThe U.S. Department of Energy (DOE) promotes the production of ethanol and other liquid fuels from lignocellulosic biomass feedstocks by funding fundamental and applied research that advances the state of technology in biomass collection, conversion, and sustainability. As part of its involvement in the program, the National Renewable Energy Laboratory (NREL) investigates the production economics of these fuels.This report describes in detail one potential biochemical ethanol conversion process, conceptually based upon core conversion and process integration research at NREL. The overarching process design converts corn stover to ethanol by dilute-acid pretreatment, enzymatic saccharification, and co-fermentation. Ancillary areas-feed handling, product recovery, wastewater treatment, lignin combustion, and utilities-are also included in the design. Detailed material and energy balances and capital and operating costs were developed for the entire process, and they are documented in this report and accompanying process simulation files, which are available to the public.As a benchmark case study, this so-called technoeconomic model provides an absolute production cost for ethanol that can be used to assess its competitiveness and market potential. It can also be used to quantify the economic impact of individual conversion performance targets and prioritize these in terms of their potential to reduce cost. Furthermore, by using the benchmark as a comparison, DOE can make more informed decisions about research proposals claiming to lower ethanol production costs.Building on design reports published in 2002 and 1999, NREL, together with the subcontractor Harris Group Inc., performed a complete review of the process design and economic model for the biomass-to-ethanol process. This update reflects NREL's current vision of the biochemical ethanol process and incorporates recent progress in the conversion areas (pretreatment, conditioning, saccharification, and fermentation), optimizations in product recovery, and an improved understanding of the ethanol plant's back end (wastewater and utilities). The major process updates in this design report are the following:• Feedstock composition is updated to a carbohydrate profile closer to the expected mean.• Pretreatment reactor configuration is revised with significant new detail.• Whole-slurry pH adjustment of the pretreated biomass with ammonia replaced the previous conditioning practice of overliming, eliminating a solid-liquid separation step.

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The dry basis elemental composition of the feedstock, shown in Table 2, is identical to previous NREL and PNNL design reports [20,21]. The composition was originally assumed to come from pulpwood. Recent feedstock logistics work at the Idaho National Laboratory (INL) suggests that the use of blended material may be required to meet a cost target of $80/dry U.S. ton while still meeting these specifications [22]. For the purpose of this report, it is assumed that any blended material provided to meet this feedstock elemental composition will not adversely affect fast pyrolysis conversion efficiencies. Ongoing studies being conducted jointly by INL, NREL, and PNNL will provide experimental evidence of the impact of blended feedstocks on fast pyrolysis and gasification processes. Future TEA will be modified to reflect conversion impacts inferred from such studies.This report is available at no cost from the National Renewable Energy Laboratory (NREL) at www.nrel.gov/publications. not considered in this design in order to focus on the core technology of in situ and ex situ fast pyrolysis vapor upgrading. Aspen Plus ModelAn Aspen Plus Version 7.2 simulation was used as the basis for this report. Since the products in pyrolysis are numerous and varied, only selected model compounds were used to represent the product slate. Additional hydrocarbon species were added to represent hydroprocessing products. Many of the desired molecular species in the desired boiling ranges for light and heavy fractions did not exist in Aspen Plus databanks and physical property parameters needed to be estimated. The biomass feedstock, ash, char, and coke were modeled as non-conventional components. Appendix F provides information about compounds selected to represent the process. The Peng-Robinson with Boston-Mathias modifications (PR-BM) equation of state was used throughout most of the process simulation. The ASME 1967 steam table correlations (STEAM-TA) were used for the steam cycle calculations. Combustor/Regenerator Temperature, °C (°F) 650 (1,202) 720 (1,328) 650 (1,202) Pressure, psia (bar) 117 (8.1) 117 (8.1) 113 (7.8) Excess air (%) 20 20 20 Solids temperature before transfer to reactor, °C (°F) 650 (1,202) 720 (1,328) 341 (645) No. of cyclones per combustor 2 2 2 Area 200 Equipment Cost EstimationsCapital costs for the equipment in this area were estimated by Harris Group. A previously developed spreadsheet tool for gasifier costs was leveraged for this exercise. Cost estimates from this tool were compared with order of magnitude estimates from technology vendors and documented in Appendix I of Worley et al.

Biorefinery process development relies on techno-economic analysis (TEA) to identify primary cost drivers, prioritize research directions, and mitigate technical risk for scale-up through development of detailed process designs. Here, we conduct TEA of a model 2000 dry metric ton-per-day lignocellulosic biorefinery that employs a two-step pretreatment and enzymatic hydrolysis to produce biomass-derived sugars, followed by biological lipid production, lipid recovery, and catalytic hydrotreating to produce renewable diesel blendstock (RDB). On the basis of projected near-term technical feasibility of these steps, we predict that RDB could be produced at a minimum fuel selling price (MFSP) of USD $9.55/gasoline-gallon-equivalent (GGE), predicated on the need for improvements in the lipid productivity and yield beyond current benchmark performance. This cost is significant given the limitations in scale and high costs for aerobic cultivation of oleaginous microbes and subsequent lipid extraction/recovery. In light of this predicted cost, we developed an alternative pathway which demonstrates that RDB costs could be substantially reduced in the near term if upgradeable fractions of biomass, in this case hemicellulose-derived sugars, are diverted to coproducts of sufficient value and market size; here, we use succinic acid as an example coproduct. The coproduction model predicts an MFSP of USD $5.28/GGE when leaving conversion and yield parameters unchanged for the fuel production pathway, leading to a change in biorefinery RDB capacity from 24 to 15 MM GGE/year and 0.13 MM tons of succinic acid per year. Additional analysis demonstrates that beyond the near-term projections assumed in the models here, further reductions in the MFSP toward $2–3/GGE (which would be competitive with fossil-based hydrocarbon fuels) are possible with additional transformational improvements in the fuel and coproduct trains, especially in terms of carbon efficiency to both fuels and coproducts, recovery and purification of fuels and coproducts, and coproduct selection and price. Overall, this analysis documents potential economics for both a hydrocarbon fuel and bioproduct process pathway and highlights prioritized research directions beyond the current benchmark to enable hydrocarbon fuel production via an oleaginous microbial platform with simultaneous coproduct manufacturing from lignocellulosic biomass.

Ex situ catalytic fast pyrolysis of biomass is a promising route for the production of fungible liquid biofuels. There is significant ongoing research on the design and development of catalysts for this process. However, there are a limited number of studies investigating process configurations and their effects on biorefinery economics. Herein we present a conceptual process design with techno-economic assessment; it includes the production of upgraded bio-oil via fixed bed ex situ catalytic fast pyrolysis followed by final hydroprocessing to hydrocarbon fuel blendstocks. This study builds upon previous work using fluidized bed systems, as detailed in a recent design report led by the National Renewable Energy Laboratory (NREL/ TP-5100-62455); overall yields are assumed to be similar, and are based on enabling future feasibility. Assuming similar yields provides a basis for easy comparison and for studying the impacts of areas of focus in this study, namely, fixed bed reactor configurations and their catalyst development requirements, and the impacts of an inline hot gas filter. A comparison with the fluidized bed system shows that there is potential for higher capital costs and lower catalyst costs in the fixed bed system, leading to comparable overall costs. The key catalyst requirement is to enable the effective transformation of highly oxygenated biomass into hydrocarbons products with properties suitable for blending into current fuels. Potential catalyst materials are discussed, along with their suitability for deoxygenation, hydrogenation and C-C coupling chemistry. This chemistry is necessary during pyrolysis vapor upgrading for improved bio-oil quality, which enables efficient downstream hydroprocessing; C-C coupling helps increase the proportion of diesel/jet fuel range product. One potential benefit of fixed bed upgrading over fluidized bed upgrading is catalyst flexibility, providing greater control over chemistry and product composition. Since this study is based on future projections, the impacts of uncertainties in the underlying assumptions are quantified via sensitivity analysis. This analysis indicates that catalyst researchers should prioritize by: carbon efficiency [ catalyst cost [ catalyst lifetime, after initially testing for basic operational feasibility.

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A biomass fast pyrolysis reactor model with detailed reaction kinetics and one-dimensional fluid dynamics was implemented in an equationoriented modeling environment (Aspen Custom Modeler). Portions of this work were detailed in previous publications; further modifications have been made here to improve stability and reduce execution time of the model to make it compatible for use in large process flowsheets. The detailed reactor model was integrated into a larger process simulation in Aspen Plus and was stable for different feedstocks over a range of reactor temperatures. Sample results are presented that indicate general agreement with experimental results, but with higher gas losses caused by stripping of the bio-oil by the fluidizing gas in the simulated absorber/condenser. This integrated modeling approach can be extended to other well-defined, predictive reactor models for fast pyrolysis, catalytic fast pyrolysis, as well as other processes.