Resilient Smart Power Grid Synchronization Estimation Method for System Resilience with Partial Missing Measurements
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Bibliographic record
Abstract
With the increasing demand for power system stability and resilience, effective real-time tracking plays a crucial role in smart grid synchronization.However, most studies have focused on measurement noise, while they seldom think about the problem of measurement data loss in smart power grid synchronization.To solve this problem, a resilient fault-tolerant extended Kalman filter (RFTEKF) is proposed to track voltage amplitude, voltage phase angle and frequency dynamically.First, a threephase unbalanced network's positive sequence fast estimation model is established.Then, the loss phenomenon of measurements occurs randomly, and the randomness of data loss's randomness is defined by discrete interval distribution [0, 1].Subsequently, a resilient fault-tolerant extended Kalman filter based on the real-time estimation framework is designed using the timestamp technique to acquire partial data loss information.Finally, extensive simulation results manifest the proposed RFTEKF can synchronize the smart grid more effectively than the traditional extended Kalman filter (EKF).
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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) | 0.000 | 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