Regional differences in the economic feasibility of advanced biorefineries: Fast pyrolysis and hydroprocessing

Abstract

This analysis identifies the sensitivity of the fast pyrolysis and hydroprocessing pathway to facility location. The economic feasibility of a 2000 metric ton per day fast pyrolysis and hydroprocessing biorefinery is quantified based on 30 different state-specific facility locations within the United States. We calculate the 20-year internal rate of return (IRR) and net present value (NPV) for each location scenario as a function of state-and region-specific factors. This analysis demonstrates that biorefinery IRR and NPV are very sensitive to bio-oil yield, feedstock cost, location capital cost factor, and transportation fuel market value. The IRRs and NPVs generated for each scenario vary widely as a result, ranging from a low of 7.4% and -$79.5 million in Illinois to a high of 17.2% and $165.5 million in Georgia. The results indicate that the economic feasibility of the fast pyrolysis and hydroprocessing pathway is strongly influenced by facility location within the United States. This result could have important implications for cellulosic biofuel commercialization under the revised Renewable Fuel Standard. Keywords fast pyrolysis, techno-economic analysis, regional sensitivity, Bioeconomy Institute, Mechanical Engineering Disciplines Industrial Engineering | Systems EngineeringComments NOTICE: This is the author's versions of a work that was accepted for publication in Energy Policy. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Energy Policy, 57, June (2013) AbstractThis analysis identifies the sensitivity of the fast pyrolysis and hydroprocessing pathway to facility location. The economic feasibility of a 2000 metric ton per day fast pyrolysis and hydroprocessing biorefinery is quantified based on 30 different state-specific facility locations within the United States. We calculate the 20-year internal rate of return (IRR) and net present value (NPV) for each location scenario as a function of state-and region-specific factors. This analysis demonstrates that biorefinery IRR and NPV are very sensitive to bio-oil yield, feedstock cost, location capital cost factor, and transportation fuel market value. The IRRs and NPVs generated for each scenario vary widely as a result, ranging from a low of 7.4% and -$79.5 million in Illinois to a high of 17.2% and $165.5 million in Georgia. The results indicate that the economic feasibility of the fast pyrolysis and hydroprocessing pathway is strongly influenced by facility

A techno-economic review of thermochemical cellulosic biofuel pathways

“…The TEA model by Brown et al (2013b) is adapted by Petter and Tyner (2014) to conduct an analysis of FPH uncertainty and private investment risk. The analysis with the adapted model finds that biofuel market value uncertainty results in a high risk to private investment, although the use of reverse auctions by governments could shift risk to the public sector and prove more effective at encouraging private investment than the capital subsidies that are currently employed in the U.S. Brown et al (2013c) also employs the Brown et al (2013b) model to identify those regional factors such as market conditions and tax rates that have the greatest impact on the economic competitiveness of the FPH pathway. The authors find that biorefinery location has a large impact on both IRR and NPV and conclude that these are most sensitive to feedstock type and regional market conditions.…”

Regional techno‐economic and life‐cycle analysis of the pyrolysis‐bioenergy‐biochar platform for carbon‐negative energy

“…Capital costs for biorefineries vary by locations and we use the Department of Defense's (DOD) area‐cost factors to account for the capital cost sensitivity to the facility location states . This DOD index covers all US states for both urban and rural areas, with consideration of the difference in labor jobs, construction materials, equipment types, and local climate conditions . The corporate tax rates differ among states but are not discussed in this study since Brown et al .…”

“…Brown et al . have compared the differences in the economic feasibility of 2000 metric ton day −1 fast pyrolysis and hydroprocessing in 30 states . They quantified the internal rate of return (IRR) and net present value (NPV) variances of the biorefinery and found values ranging from 7.4% and −$79.5 million in Illinois to 17.2% and $165.5 million in Georgia .…”

“…have compared the differences in the economic feasibility of 2000 metric ton day −1 fast pyrolysis and hydroprocessing in 30 states . They quantified the internal rate of return (IRR) and net present value (NPV) variances of the biorefinery and found values ranging from 7.4% and −$79.5 million in Illinois to 17.2% and $165.5 million in Georgia . Very few subsequent studies have further investigated the economic performance of pyrolysis bioenergy production technology considering regional differences; this study contributes to filling this knowledge gap.…”

A critical analysis of thermochemical cellulosic biorefinery capital cost estimates

“…Th e TEAs published in the open literature have also served as the basis for subsequent analyses of additional biofuel pathways [4][5][6][7][8][9][10] and in other fi elds examining cellulosic biofuels in the contexts of biorefi nery learning rates, 11,12 energy policy, [13][14][15] future competitiveness with fossil fuels, [15][16][17] supply chains, 19-22 and sustainability. 23,24 Th ese subsequent analyses incorporate and build on the results of the original TEAs, causing the assumptions and methodological choices used to calculate pathway capital costs, which commonly undergo no changes other than to account for price infl ation, to be refl ected throughout the results of the subsequent analyses.…”