Valuing Electricity Transmission: The Case of Alberta
Bibliographic record
Abstract
Transmission economics remains a difficult area. Market forces alone are generally felt to be insufficient for signaling investment due to appropriability problems and the challenges of “parallel (loop) flow.” Further, there is no generally recognized method of estimating the value of transmission expansion. Here we extend the approach of Kleit and Reitzes (2008) to the nearly isolated electricity grid of Alberta, essentially eliminating the problems of parallel flow. With this model, we are able to determine the value of electricity flows to and from Alberta, as well as the transactions costs associated with those flows. We are also able to value the impact of transmission expansion in Alberta. We apply this model to a project currently being developed, the Montana–Alberta Tie Line (MATL). Depending on the relevant elasticity of supply, we find that the MATL owners will be able to appropriate between 80% and 96% of the societal value of their new transmission capacity. This high level of appropriability is in contrast to the conclusions of most of the literature in this area, suggesting that market forces may in some instances be effective in providing incentives for optimal transmission investment.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".