On the loadability sets of power systems — Part I: Characterization
Why this work is in the frame
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Bibliographic record
Abstract
This two-part paper presents a framework for the characterization and minimal representation of the feasibility regions of power systems in the demand space. These feasibility regions are called loadability sets, and they represent the projection of generation-demand-network space onto the demand space only. Loadability sets have been characterized previously for power systems with either no or a single active line flow constraint. In Part I of this two-part paper, we generalize this characterization to power systems with any number of active line flow constraints. The proposed characterization approach makes use of the Fourier-Motzkin elimination method which leads to the generation of a large number of constraints. We set course to address this shortcoming in the second part of the paper. The notion of umbrella set is revisited in Part II to identify and remove the redundant constraints produced in the loadability set characterization process. The outcome of the proposed framework is the minimal representation of the power system feasibility region in the demand space. We envision multiple applications for the proposed framework in power system planning, operations planning and real-time operation.
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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 | 0.000 |
| 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 it