Simulation of the coordination of protective devices in low voltage circuits
Bibliographic record
Abstract
The coordination of surge arresters, used to protect electric power circuit networks, has always created difficulty for designers; the difficulty being that when two or more arresters are present, a smaller one may improperly protect a larger one, potentially leading to a failure of the combination of these devices to protect the circuit from the surge.In this particular document, the case of a model of a simple two-branch building circuit network is examined, with an aim to produce a general method of examining the performance of these circuits using PSCAD/EMTDC software, developed by the Manitoba HVDC Research Centre Inc.Once developed and compared to existing experimental results, the model is then applied to a variety of branch circuit and service entrance arrester configurations, and then finally exposed to a model of a surge passed through a typical single phase distribution transformer.The results of all model runs are compared to their appropriate counterparts.The studies comprising this thesis have revealed that a satisfactory model has been produced, with results within those expected of the variability of arrester component tolerances, but that there is also room for further experimental verification, especially to advance the model for studying a greater variety of circumstances and circuits.The developed model is such that, with proper packaging and preparation, it may serve as a surge coordination teaching aid.
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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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".