Electromagnetic Transients Simulation-Based Surrogate Models for Tolerance Analysis of FACTS Apparatus
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Bibliographic record
Abstract
This paper introduces a computationally efficient surrogate model-based approach for tolerance analysis of power systems. Surrogate models are heuristic, simple representations of complex systems that are obtained through an automated sensitivity analysis of electromagnetic transient simulations results. These simpler models are shown in this paper to be significantly faster than full-detail simulation models to obtain accurate statistical tolerance information about complex power networks. Usefulness of the proposed approach is demonstrated by two application examples. In the first example, surrogate models are used for determining the statistical distribution of undesired remnant harmonics produced by a voltage-source converter, given the uncertainty in the firing angles. In the second example, the impact of variations in the system parameters around the nominal values on the transient behavior of a static compensator is analyzed.
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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