Improving carbon efficiency and profitability of the biomass to liquid process with hydrogen from renewable power
Bibliographic record
Abstract
A process where power and biomass are converted to Fischer-Tropsch liquid fuels (PBtL) is compared to a conventional Biomass-to-Liquid (BtL) process concept. Based on detailed process models, it is demonstrated that the carbon efficiency of a conventional Biomass to Liquid process can be increased from 38 to more than 90% by adding hydrogen from renewable energy sources. This means that the amount of fuel can be increased by a factor of 2.4 with the same amount of biomass. Electrical power is applied to split water/steam at high temperature over solid oxide electrolysis cells (SOEC). This technology is selected because part of the required energy can be replaced by available heat. The required electrical power for the extra production is estimated to be 11.6 kWh per liter syncrude ( C 5 + ) . By operating the SOEC iso-thermally close to 850 °C the electric energy may be reduced to 9.5 kWh per liter, which is close to the energy density of jet fuel. A techno-economic analysis is performed where the total investments and operating costs are compared for the BtL and PBtL. With an electrical power price of 0.05 $/kWh and with SOEC investment cost of the 1000 $/kW(el), the levelized cost of producing advanced biofuel with the PBtL concept is 1.7 $/liter, which is approximately 30% lower than for the conventional BtL. Converting excess renewable electric power to advanced biofuel in a PBtL plant is a sensible way of storing energy as a fuel with a relatively high energy density.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".