Algebraic Tracking Network Topology Processor for Modern Power Systems
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Bibliographic record
Abstract
With the growing deployment of Phasor Measurement Units (PMUs) in Electric Power Systems (EPSs), status measurements from switchable devices are transmitted at high sampling rates, enabling rapid detection of switching events and continuous topology updates. Fast topology processing is therefore essential for reliable operation and decision-making in modern, dynamic EPSs. In this context, this paper proposes an Algebraic Tracking Network Topology Processor (AT-NTP), developed from algebraic formulations and a new islanding identification method. Using status measurements from PMUs and other sources, the AT-NTP determines and updates network topology through matrix factorization and refactorization, avoiding graph search algorithms and artificial intelligence techniques commonly used in existing topology processors. The AT-NTP is simple to implement, avoids combinatorial explosion, and does not require training stages. It efficiently detects switching events, island formation, bus merging or splitting, and measurement configuration changes without recomputing the topology from scratch. Its formulation applies to arbitrary substation configurations without requiring adaptations, making it flexible and suitable for various systems. Simulation results on benchmark and large-scale real networks demonstrate the AT-NTP’s computational efficiency and confirm its suitability for PMU-based state estimation and advanced energy management applications.
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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) | 0.000 | 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