The Use of Selective Bunkering to Optimise PRB Utilisation at Nanticoke Generating Station
Bibliographic record
Abstract
Many stations are currently blending Powder River Basin (PRB) coals with bituminous coals to various blend ratios. However, this blending is almost always accomplished at the port, coal yard or a dedicated blend facility — i.e. prior to introducing the coal to the unit. As a result, the pulverizers and burners are forced to deal with two (or more) disparate coals, compromising the performance of these systems. Research originating in Europe confirms the negative repercussions of grinding and firing dissimilar blends. This paper will describe the “Selective Bunkering” system in place at Ontario Power Generations Nanticoke GS which involves feeding the pure parent coals to individual mills and conducting blending in the furnace. This innovation has increased the maximum PRB blend ratio from 50% to 70% at full load and also allows for a seamless transition to 100% PRB firing at lower loads. The techniques employed to coordinate and optimize the combustion system will be discussed.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".