Potential of a Hybrid Wind-Diesel-Compressed air system for Nordic Remote Canadian Areas
Bibliographic record
Abstract
In Canada, off-grid power production is significant, with more than 200,000 people living in about 300 remote communities scattered across Yukon, the Northwest Territories, Nunavut, and other islands. Most of these isolated sites rely on diesel to generate electricity. The operation of these remote isolated grids run on a deficit in the order of hundreds of millions of dollars yearly and must therefore be subsidized by the government. Low and high penetration wind–diesel hybrid systems (WDS) have been experimented to reduce diesel consumption. In a previous article, we explored the re-engineering of current diesel power plants with the introduction of high penetration wind systems using compressed air energy storage (CAES). This is a viable alternative to increase the overall percentage of renewable energy and reduce the cost of electricity, to increase the diesel engine lifetime and efficiency and to decrease their fuel consumption and GHG emissions. In this paper, we present the operative principle of this hybrid system, its economic benefits and advantages. Finally, we apply this concept in the case of a Canadian Nordic village to demonstrate the real energetic, ecological and economic potential of this system.
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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 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| 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".