Bibliographic record
Abstract
Biomass fuels have long been accepted as useful renewable energy sources, especially in mitigating greenhouse gases (GHG) emissions. Fossil fuel-based power plants make up over 30% of the GHG emissions in Alberta, Canada. Displacement of fossil fuel-based power through biomass co-firing has been proposed as a near-term option to reduce these emissions. In this research, co-firing of three biomass feedstocks (i.e., whole forest, agricultural residues and forest residues) at varying proportions with coal as well as with natural gas in existing plants was studied to investigate different co-firing technologies. Whole forest biomass refers to live or dead trees (spruce and mixed hardwood) not considered merchantable for pulp and timber production; agricultural residues are straws obtained as the by-product of threshing crops such as wheat, barley, and flax; and forest residues refer to the limbs and tops of the trees left on the roadside to rot after logging operations by pulp and timber companies. Data-intensive models were developed to carry out detailed techno-economic and environmental assessments to comparatively evaluate sixty co-firing scenarios involving different levels of the biomass feedstock co-fired with coal in existing 500 MW subcritical pulverized coal (PC) plants and with natural gas in existing 500 MW natural gas combined cycle (NGCC) plants. Minimum electricity production costs were determined for the co-fired plants for the same three biomass feedstocks and base fuels. Environmental assessments, from the point of harvesting to delivering electricity to the customers, was evaluated and compared to the various co-fired configurations to determine the most economically viable and environmental friendly options of biomass co-firing configuration for western Canada. The results obtained from these analyses shows that the fully paid-off coal-fired power plant co-fired with forest residues is the most attractive option and has levelized cost of electricity (LCOE) ranging from $53.12 to $54.50/MWh; and CO2 abatement costs ranging from $27.41 to $31.15/tCO2. Similarly, the LCOE and CO2 abatement costs for whole forest chips range from $54.68 to $56.41/MWh and $35.60 to $41.78/tCO2 respectively. When straw is co-fired with coal in a fully paid-off plant, the LCOE and CO2 abatement costs range from $54.62 to $57.35/MWh and $35.07 to $38.48/tCO2 respectively. This is of high interest considering the likely increase of the carbon levy to about $30/tCO2 in the Province of Alberta by 2017.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".