Power System Dynamic State Estimation Using Smooth Variable Structure Filter
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Bibliographic record
Abstract
With the integration of distributed energy resources (DER) traditional power systems evolved toward modernized smart grids. Although smart grids open up the possibility for more reliable and secure energy management, they impose new challenges on real-time monitoring and control of the power grid. State estimation is a key function which plays a vital role in reliable system control. In this paper, the smooth variable structure filter (SVSF) is used for power system dynamic state estimation (DSE). SVSF is a predictor-corrector based approach which can be applied to both linear and nonlinear system with the ability to deal with the system uncertainties. The simulation results on a single machine with infinite bus power network shows the superiority of the proposed SVSF compared to extended Kalman filter (EKF) and unscented Kalman filter (UKF). The results of the proposed method show a significant smoothness and accuracy in its performance compared to those obtained from EKF and UKF approaches; in particular, in the presence of measurement outliers.
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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) | 0.001 | 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