Wind Integration into Various Generation Mixtures
Bibliographic record
Abstract
A load balance model is used to quantify the economic and environmental effects of integrating wind power into three typical generation mixtures. System operating costs over a specified period are minimized by controlling the operating schedule of existing power generating facilities for a range of wind penetrations. Unlike other studies, variable generator efficiencies, and thus variable fuel costs, are taken into account, as are the ramping constraints on thermal generators. Results indicate that system operating cost will increase by 15% to 110% (pending generation mixture) at a wind penetration of 100% of peak demand. Results also show that some mixtures will exhibit cost reductions on the order of 13% for moderate wind penetrations and high wind farm capacity factors. System emissions also decrease by 13% to 32% (depending on generation mixture) at a wind penetration of 100%. This leads to emission abatement costs in the range of $65 per tonne-CO2e for coal dominated mixtures, but $450 per tonne-CO2e for hydro dominated mixtures. For natural gas dominated mixtures, the introduction of wind power may well be beneficial overall.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".