Economic costs of managing of an electricity grid with increasing wind power penetration
Bibliographic record
Abstract
We examine the impact of policy choices, including a carbon tax, on the optimal allocation of power across different generation sources and on future investments in generating facilities. The main focus is on the Alberta power grid, as it is heavily dependent on fossil fuels and has only limited ties to other power grids, although the model could be extended to larger (and even multiple) grids. The results indicate that, as wind penetrates the extant generating mix characterizing the grid, cost savings and emission reductions do not decline linearly but at a decreasing rate. However, if flexibility is allowed, then, as the carbon tax increases to C$40/tCO2 or above, existing coal plants start to be replaced by newly constructed wind farms and natural gas plants. If coal can be completely eliminated from the energy mix and replaced by natural gas and wind, substantial savings of 31.03 Mt CO2 (58% of total emissions) can result. However, this only occurs for carbon taxes of over C$170/tCO2. The associated high capital costs of new generating facilities may thus not be an ideal use of funds for addressing climate change.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".