Imperfect Competition in Electricity Markets with Renewable Generation: The Role of Renewable Compensation Policies
Bibliographic record
Abstract
We analyze the effects of commonly employed renewable compensation policies on firm behavior in an imperfectly competitive market. We consider a model where firms compete for renewable capacity in an auction prior to choosing their forward positions and competing in wholesale markets. We focus on fixed and premium-priced feed-in tariff (FIT) compensation policies. We demonstrate that compensation policies impact both the types of resources that win the auction and subsequent competition. While firms have stronger incentives to exercise market power under a premium-priced FIT, they also have increased incentives to sign pro-competitive forward contracts. In net firms have stronger incentives to exercise market power under the premium-priced policy. We find conditions under which renewable resources that are more correlated with market demand are procured under a premium-priced design, while the opposite occurs under a fixed-priced policy. If the cost efficiencies associated with the “more valuable” renewable resources are sufficiently large, then welfare is higher under the premium-priced policy despite the stronger market power incentives in the wholesale market.
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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 | 0.003 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".