A New Half-Cycle Phasor Estimation Algorithm
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Bibliographic record
Abstract
Phasor estimation algorithms for protective relaying are required to filter out unwanted components from the input signals and retain only the components of interest. The components to be removed include harmonics and the decaying-exponential transient (dc offset) component. They affect the accuracy and the speed of convergence of the phasor estimation algorithms to a great extent. This paper presents a new technique, which effectively removes the harmonics and the decaying dc component present in the input signals, within half a cycle of the power system frequency. This is achieved by means of a simple computational procedure using three off-line look-up tables. The proposed algorithm has been tested for a wide variety of signals to assess its performance. The performance is also compared with the two most popular half-cycle phasor estimation algorithms; the half-cycle least error squares algorithms and the mimic plus half-cycle Fourier algorithm. The test results show that the proposed relaying algorithm has a faster convergence and better accuracy compared to these previously proposed algorithms. The results also indicate that the proposed algorithm converges to its final value within half a cycle of the power system frequency as compared to the other two algorithms, which take more than half a cycle to converge, when a decaying dc component is present in the input.
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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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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