Marginal Pricing for Intertie Transactions Summary
Bibliographic record
Abstract
The subject IESO proposal to implement locational marginal pricing (LMP) for intertie transactions (the Proposal) represents an attempt to split the Ontario into two classes of market participants, with different rules for those within Ontario, and with different rules for those outside of Ontario. These two classes of market participants should, in theory, be competing with each other. However, the Proposal creates a situation that due to a transmission constraint within Ontario, a generator or load within Ontario would see a different price (the uniform Market Clearing Price) than a similar load or generator located just outside of Ontario (who receives the interface locational marginal price). Thus, the Proposal is highly discriminatory with respect to the way that it treats external market participants with respect to transmission constraints within Ontario. There is no technical or cost causation justification for this discriminatory treatment, and in fact the primary justification given for the Proposal relates to “inefficient net exports to New York 1 ” that may create a very slight upward pressure on the Ontario HOEP. The Proposal creates new significant gaming opportunities for generators within Ontario in relation to newly created Transmission Rights from the intertie zone to the reference bus. Elimination of this gaming opportunity requires a full day ahead market (not just a unit commitment process), and more thorough monitoring of the generation offers, including prohibiting the
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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 | 0.005 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.005 | 0.003 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.031 | 0.003 |
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".