Development of Graphical User Interface for the PT relays
Bibliographic record
Abstract
Computer relaying has played an important role in power system protection as technology advances. Due to the great flexibility of computer-based relays, it will be applicable to design a general user programmable relay to meet the various relaying applications in the utilities. The power group in University of Manitoba has successfully implemented such kind of distance relay prototype based on Digital Signal Processor (DSP), in which different applications adopted a generic piece of hardware capable of implementing all of the relaying functions but with a capability to expand as the need arises. However, the configuration/modification of custom relay algorithms still remain difficult for the relay engineers since a thorough understanding of C/Assembly language and hardware knowledge is required. In this thesis, a Graphical User Interface (GUI) for the DSP-based distance relay was developed, which would assist the relay engineer to design a suitable algorithm for the application and then configure a general purpose relay hardware to run algorithms. The key part of the developed Graphical User Interface is a graphical block library of basic functions for distance relaying. Based on the developed GUI, a Graphical DSP-based Distance Relay (GDDR) was implemented. In addition, evaluation of the GDDR relay performance was carried out using laboratory tests, and the effects of System Impedance Ratio (SIR), fault types, and fault location on the fault pick-up time were investigated.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.046 | 0.019 |
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".