Market Power and Renewables: The Effects of Ownership Transfers
Bibliographic record
Abstract
Adding renewable energy sources (RES) to an electricity market has an ambiguous effect on wholesale prices. The merit order effect (MoE) has a downward pressure on prices while, with market power, higher inframarginal rents will tend to increase prices. We quantify the interaction of the two effects in the Ontario electricity market. We identify the market power effect by simulating transfers of RES capacity from the fringe to larger firms: these transfers increase prices by up to 24%. We then add RES capacity and allocate it to players with varying levels of market power. Following a net expansion of RES capacity of 5% relative to total capacity, prices decrease by 30% when new capacity is assigned to the fringe, but only by 7% when assigned to the largest firm. Our findings show that the MoE is largely mitigated by market power, hence the importance of the market structure in the design of uniform incentives for RES adoption.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".