Assessment of the Performance of Phasor-Based and Transients-Based Faulted Phase Identification Techniques in the Presence of Inverter Interfaced Resources
Bibliographic record
Abstract
Faulted phase identification is one of the segments of conventional system protection that is severely vulnerable in the presence of inverter-based resources (IBR) such as Type IV wind and solar PV power plants. The work presented in this paper investigates the effect of IBRs on the conventional phasor-based faulted phase identification methods widely implemented in contemporary commercial protection relays using theoretical analysis and simulation results. Moreover, this premise is further validated by testing commercial line protection relays using hardware-in-the-loop simulations. This paper also evaluates the applicability of recently proposed transients/incremental quantities-based techniques to overcome the deficiencies of conventional methods to correctly identify the faulted phase in systems with IBRs through real-time and control hardware-in-the-loop simulations. Comparisons with commercial relays show that transient/incremental quantities-based methods are more suitable for systems with a high penetration of IBRs.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".