Techno-economic analysis of biomass-to-liquids production based on gasification

Swanson, Richard A.; Platon, Alexandru; Satrio, Justinus A.; Brown, Robert C.

doi:10.1016/j.fuel.2010.07.027

Cited by 349 publications

(168 citation statements)

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“…FT diesel is much more costly in 2020, but becomes competitive in 2050, because of assumed technology improvements. Algal fuels are projected to be more expensive in both 2020 and 2050, Humbird et al 2011, Jones et al 2009, Swanson et al 2010, Tao and Aden 2009, Tao and Aden 2011, DOE 2011a, DOE 2011b Figure 4.4. LCOE breakdown for diesel, jet, and bunker-market fuels in 2050 (Sources: Humbird et al 2011, Jones et al 2009, Swanson et al 2010, Tao and Aden 2009, Tao and Aden 2011, DOE 2011a, DOE 2011b LCOEs for electricity are shown in Figures 4.5 and 4.6.…”

Section: Levelized Cost Of Energy Resultsmentioning

confidence: 99%

“…This has been an active area of research for over two decades. The data provided for the BASE model was derived from a recent collaboration between NREL, ConocoPhillips, and Iowa State University (Swanson et al 2010). In this collaborative project, comparative techno-economic analysis was conducted for several fuels pathways, including FT diesel.…”

Section: F4 Fischer-tropsch Dieselmentioning

confidence: 99%

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Transportation Energy Futures Series. Projected Biomass Utilization for Fuels and Power in a Mature Market

Ruth

Mai

Newes

et al. 2013

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This is one of a series of reports produced as a result of the Transportation Energy Futures (TEF) project, a U.S. Department of Energy (DOE)-sponsored multi-agency project initiated to identify underexplored strategies for abating greenhouse gases and reducing petroleum dependence related to transportation. The project was designed to consolidate existing transportation energy knowledge, advance analytic capacity-building, and uncover opportunities for sound strategic action.Transportation currently accounts for 71% of total U.S. petroleum use and 33% of the nation's total carbon emissions. The TEF project explores how combining multiple strategies could reduce GHG emissions and petroleum use by 80%. Researchers examined four key areas -lightduty vehicles, non-light-duty vehicles, fuels, and transportation demand -in the context of the marketplace, consumer behavior, industry capabilities, technology and the energy and transportation infrastructure. The TEF reports support DOE long-term planning. The reports provide analysis to inform decisions about transportation energy research investments, as well as the role of advanced transportation energy technologies and systems in the development of new physical, strategic, and policy alternatives.In addition to the DOE and its Office of Energy Efficiency and Renewable Energy, TEF benefitted from the collaboration of experts from the National Renewable Energy Laboratory and Argonne National Laboratory, along with steering committee members from the Environmental Protection Agency, the Department of Transportation, academic institutions and industry associations. More detail on the project, as well as the full series of reports, can be found at http://www.eere.energy.gov/analysis/transportationenergyfutures. ............................................................................................ Contract EXECUTIVE SUMMARYThe U.S. biomass resource can be used several ways that provide domestic, renewable energy to users. Understanding the capacity of the biomass resource, its potential in energy markets, and the most economic utilization of biomass is important in policy development and project selection. This study analyzed the potential for biomass within markets and the competition between them. The study found that biomass has the potential to compete well in the jet fuel and gasoline markets, penetration of biomass in markets is likely to be limited by the size of the resource, and that biomass is most cost effectively used for fuels instead of power in mature markets unless carbon capture and sequestration is available and the cost of carbon is around $80/metric ton CO 2 e. Biomass Utilization IssuesBiomass is a limited resource with many competing uses. Its allocation for fuel, power, and products depends upon characteristics of each of these markets, their interactions, and policies affecting these markets. In order to better understand competition for biomass among markets and the potential for biofuel as a market-scale alternative to petroleum-bas...

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Section: Levelized Cost Of Energy Resultsmentioning

confidence: 99%

Section: F4 Fischer-tropsch Dieselmentioning

confidence: 99%

Transportation Energy Futures Series. Projected Biomass Utilization for Fuels and Power in a Mature Market

Ruth

Mai

Newes

et al. 2013

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“…[22]. By contrast, biodiesel obtained from other crops is less expensive such as soybean biodiesel (USD 0.57 / L -USD 0.67 / L), Fischer-Tropsch biofuels from corn fiber (USD 1.13 / L -USD 1.28 / L) and rapid pyrolysis biodiesel from wood chips (USD 0.58 / L) [22,23].…”

Section: Biofuelsmentioning

confidence: 99%

Microalgae biorefineries: applications and emerging technologies

Giraldo

Romo-Buchelly

Arbeláez-Pérez

et al. 2018

DYNA

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Microalgae transform CO2 into a broad portfolio of biomolecules, and thus should be considered as a valuable biotechnological platform. Despite several research programs and global efforts to establish a sustainable microalgae-based industry, most applications have not transcended academic boundaries. This limitation raises from the high transformation costs when target products are biofuels or fertilizers. Microalgae biorefinery emerges as an alternative to improve economic competitiveness, as Under such a model scope, the process inputs come from industrial waste, while biomass exploitation prioritizes the highest value molecules followed by extraction of less valuable compounds. This review describes a wide range of microalgae exploitation schemes focused on new uses of its constituents, while discussing emerging technologies designed to improve production and efficiencies as well.Keywords: microalgae; biorefinery; biofuels; fertilizers; active biomolecules. Biorefinerías de microalgas: aplicaciones actuales y nuevas tecnologías en desarrolloResumen Las microalgas transforman el CO2 en un amplio portafolio de biomoléculas, por lo cual, son consideradas una valiosa plataforma biotecnológica. A pesar de múltiples programas de investigación y esfuerzos globales para establecer una industria sostenible basada en microalgas, la mayoría de las aplicaciones potenciales no han trascendido las fronteras académicas. Esta limitación se debe a los altos costos en la transformación del producto principalmente cuando se obtiene compuestos económicos como biocombustibles y fertilizantes. La biorefinería de microalgas surge como alternativa para incrementar la competitividad económica. En este modelo, los insumos del proceso provienen de residuos industriales, mientras que la explotación de la biomasa inicia con las moléculas de alto valor y finaliza con los compuestos menos valiosos. En esta revisión se describe un amplio abanico de esquemas de explotación de microalgas enfocado en nuevos usos de sus constituyentes. Además, se exploran las tecnologías emergentes destinadas a aprovechar esta biomasa de una manera más versátil y eficiente.

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“…This has been analyzed for different types of supply chains or facilities technologies. (Swanson et al 2010) compare capital and production costs of two biomass-to-liquid production plants. Three scenarios that represent the range of estimates for cost growth and plant performance were considered: most probable, optimistic, and pessimistic.…”

Section: Capital and Operational Costsmentioning

confidence: 99%

Design of Experiments for Sensitivity Analysis of a Hydrogen Supply Chain Design Model

Robles

Almaraz

Azzaro‐Pantel

2017

Process Integr Optim Sustain

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Hydrogen is one of the most promising energy carriers in the quest for a more sustainable energy mix. In this paper, a model of the hydrogen supply chain (HSC) based on energy sources, production, storage, transportation, and market has been developed through a MILP formulation (Mixed Integer Linear Programming). Previous studies have shown that the start-up of the HSC deployment may be strongly penalized from an economic point of view. The objective of this work is to perform a sensitivity analysis to identify the major parameters (factors) and their interaction affecting an economic criterion, i.e., the total daily cost (TDC) (response), encompassing capital and operational expenditures. An adapted methodology for this SA is the design of experiments through the Factorial Design and Response Surface methods. Six key parameters are chosen (demand, capital change factor (CCF), storage and production capital costs (SCC, PCC), learning rate (LR), and unit production cost (UPC)). The demand is the factor that is by far the most significant parameter that strongly conditions the TDC optimization criterion, the second most significant parameter being the capital change factor. To a lesser extent, the other influencing factors are PCC and LR. The main interactions are found between demand, CCF, UPC, and SCC. The discussion has also shown that the calculation of UPC has to be improved taking into account the contribution of the fixed, electricity, and feedstock costs instead of being considered as a fixed parameter only depending on the size of the production unit. As any change that could occur relative to demand or CCF could strongly affect the response variable, more effort is also needed to find the more consistent way to model demand uncertainty in HSC design, especially since a long horizon time is considered for hydrogen deployment.

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Techno-economic analysis of biomass-to-liquids production based on gasification

Cited by 349 publications

References 10 publications

Transportation Energy Futures Series. Projected Biomass Utilization for Fuels and Power in a Mature Market

Transportation Energy Futures Series. Projected Biomass Utilization for Fuels and Power in a Mature Market

Microalgae biorefineries: applications and emerging technologies

Design of Experiments for Sensitivity Analysis of a Hydrogen Supply Chain Design Model

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