Integrating batteries with large-scale wind power: a Canadian case-study
Bibliographic record
Abstract
Canada is a country with a mostly fossil free electricity generation mix, with more than 80% of electricity being produced from hydropower, nuclear and other renewables. The province of Alberta, on the other hand, still has a long way to go in making its electricity less fossil-fuel based, and for that, it aims to invest in renewables in the coming years. This increased deployment of renewables, an intermittent energy source, could mean a good investment opportunity for batteries in the province as well. This thesis investigates the different revenue possibilities of a battery operating in Alberta’s real-time electricity market, reserve market and in a combination of both markets. To understand how wind energy would influence such an operation, these strategies are then analyzed taking into account the wind generation’s annual variability for the charging of the battery. All of these strategies were fixed, meaning the battery had a fixed operation schedule for every day of the year. Lastly, this thesis analyzed an optimal battery operation, with access to perfect information and possibility to optimize revenues between the aforementioned markets.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".