Determination of Network Rental Components in a Competitive Electricity Market
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Bibliographic record
Abstract
The locational marginal pricing (LMP)-based settlement results in a surplus collected by the system operator from the consumers. The nonlinear transmission losses and the constrained operation of the power system due to operating limits, such as power flow limits on transmission lines, cause the accumulation of this surplus. This accumulated revenue, referred to as the network rental in this paper, has two main components: loss rental and constraint rental. This paper develops a method to calculate these different rental components paid by each consumer, by combining the power flow tracing and KKT optimality conditions. This yields quantitative determination of how each consumer has overpaid in the form of loss rental and constraint rental, which in turn can be used to get a better insight of how the rental is accumulated. Simple three- and four-bus systems are used to demonstrate the proposed method.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 it