Small Scale Renewable Energy Resources Assessment for Newfoundland
Bibliographic record
Abstract
This paper is intended as a preliminary review and analysis of the potential for small scale hydro and wind projects on the island of Newfoundland, Canada. Despite good wind and hydro resources the province uses thermal generation for about 20% of its energy requirements. Currently, Newfoundland is considering a multi billion dollar transmission line to bring hydro power from Labrador to the island and replace thermal generation. The alternative given by the province is to continue with one of various thermal generation options. This study is intended to determine whether small scale hydro and wind energy projects warrant consideration as another future generation option, and whether they could potentially replace thermal generation. To determine the total potential for small hydro and wind within the island power system several different areas are studied. Firstly, updated hydro resource potential is considered through RETScreen analysis of sites from a previous small hydro study. Wind resource potential is also analysed briefly using both island resource information and wind penetration research to gauge total potential. Finally, the ability of these projects to meet future energy demand is analysed through simplified island system simulations. It was found that there is a very large small hydro and wind resource potential available on the island and that these small projects merit consideration as a future generation option, with the potential to replace thermal generation.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".