ELFORSPOT: an equilibrium model of the combined forward market and spot market for electricity, using complementarity programming
Bibliographic record
Abstract
In restructured electricity markets, participants have the option of trading financial forward contracts prior to the spot market. To evaluate the interactions between the forward and spot market, we have created ELFORSPOT, a Complementarity Programming model. It is a deterministic model of multiple suppliers and customers that resembles a potential future Ontario-like electricity market for a period of one year. There are three formulations of ELFORSPOT. The first focuses on suppliers' knowledge of the effect of the forward contracts on the spot equilibrium. The second simulates a market under various competition assumptions for strategic suppliers. The third extends the formulation of the second to include strategic customers which, similar to suppliers, anticipate the effect of their bids on the market prices. To illustrate the usefulness of these models, we focus on the behaviour of a new entrant which has higher variable cost and annual capital charges than the existing generation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".