Modeling and Simulation of a Metal Oxide Lightning Surge Arrester for 132kV Overhead Transmission Lines
Bibliographic record
Abstract
This paper demonstrated the design of a Metal Oxide Surge Arrester for a 132 kV system with a rated voltage of 120 kV according to specifications. The study model was chosen to be Pinceti model which is a derivation of the IEEE standard model of Lightning arrester design. The design specifications for the lab tests on 120kV rated arrester for ZnO material were obtained from the catalogue of Ohio Brass Pvt. Ltd. The parameters for the lumped components were derived from the manufacturer’s data sheet while the non-linear characteristic was derived from curve fitting based on the Pinceti provided curves in literature, using Matlab Curve Fitting Tool. The design was simulated on EMTP-RV commercial software and the results before optimization as well as after optimization are presented. A cross comparison with the manufacturers data results in 1.113% relative error, which is in competition with similar designs for different rated and system voltages in literature. The study presents an improved model of a metal oxide arrester for 132kV system, with its lumped and exponential parameters presented in detail.
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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 | 0.000 |
| 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 | 0.001 | 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".