On composite load modeling for voltage stability and under voltage load shedding
Why this work is in the frame
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Bibliographic record
Abstract
Undervoltage load shedding (UVLS) has been considered by some utilities as a cost-effective corrective tool to overcome voltage instability and abnormal voltage conditions. Load modeling is an important aspect for voltage stability studies and real time system controls pertinent to UVLS. At a given bus, a load would be an aggregate of load elements that would differ in their static and dynamic performance. Also at load centers, aggregate loads would encompass system components of particular characteristics such as load tap changers, SVC's and in-plant generation. Modeling aggregated loads should reflect the nature of load components and fit the applications of the model in studies and real time controls. In a tutorial style, This work discusses the evolution of static and dynamic load models for voltage stability and examines their applicability to UVLS. Load modeling approaches were listed as deterministic, generic and stochastic. Concerns and recommendations were given for adopting one approach or a combination of approaches in aggregate load modeling for UVLS. Load models validation and verification is emphasized especially when using generic or stochastic models.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| 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