A Dynamic Oligopolistic Electricity Market with Interdependent Market Segments
Bibliographic record
Abstract
We propose a deterministic, discrete-time, finite-horizon oligopoly model to investigate investment and production equilibrium strategies, in a setting where demand evolves over time and the two market-segment loads (peak- and baseload) are interdependent. The players (generators) compete a la Cournot, open-loop Nash equilibria are computed and numerical results are discussed. The model is calibrated with data from Ontario, Canada. We assess the impact on equilibrium strategies of a generation sector with more market power than what is actually the case. We also find a slight difference in the investment sequence when interdependent demand segments are considered. Finally, we analyze the impact of increasing demand elasticities over time, and varying the financial values of the production capacities that remain at the end of the planning horizon. We believe that such a tool is valuable for professionals and scholars interested in the dynamics of production capacity mix (portfolio of technologies) in the electricity sector. It is also of paramount importance for public decision makers who have to simultaneously deal with environmental issues and with price control, both of which are politically sensitive. doi: 10.5547/ISSN0195-6574-EJ-Vol32-No4-8
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 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".