Impacts of Grounding Configurations on Responses of Ground Protective Relays for DFIG-Based WECSs-Part II: High-Impedance Ground Faults
Bibliographic record
Abstract
Ground faults are among the major causes of disrupting the safe, secure, stable, and profitable operation of doubly fed induction generator (DFIG) based wind energy conversion systems (WECSs). On one hand, minimizing the possible damage in a DFIG-based WESC, caused by ground faults, requires accurate detection and fast response of ground protective devices. On the other hand, the responses of ground protective devices are highly dependent on ground currents and potentials, especially during high-impedance ground faults. This paper investigates the influences of grounding configurations on the responses of ground protective devices used in DFIG-based WECSs during high-impedance ground faults. Investigated influences are observed through the ability of ground protective devices, used in DFIG-based WECSs, to quickly and accurately respond to high-impedance ground faults for different grounding configurations. In this paper, the solid, low-resistance, high-resistance, and open grounding configurations are tested for DFIG-based WECS in order to establish comprehensive investigations. The results of the investigations show that the responses of ground protective devices vary depending on ground fault currents, which can have different levels due to the grounding configuration. Moreover, the results of the investigations reveal that the frequency-selective grounding configuration can offer a minimum impact on the responses of ground protective devices used in DFIG-based WECSs.
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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 | 0.000 | 0.002 |
| 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 | 0.001 | 0.001 |
| Open science | 0.001 | 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".