Performance Evaluation of Surge Arrester Counters in Energy Transmission Lines During Switching: Simulation and Practical Results
Bibliographic record
Abstract
ABSTRACT Switching operations in power transmission lines can cause travelling waves on the lines, generating transient overvoltages. The magnitude of these overvoltages depends on the power system voltage magnitude at the closing time and the trapped charge on the line. Surge arresters protect the energy equipment inside substations against the line overvoltages. The number of surge arrester operations is counted by the surge arrester counter. This article focuses on evaluating surge arrester performance in the transmission line switching. For this purpose, a 400 kV power transmission line in Iran is simulated using EMTP‐RV software. Then, the probability of operation of the surge arrester counter is obtained using statistical switching. Comparing the recorded practical results by the surge arrester counter with the simulation results demonstrated that accurate simulation of the surge arrester performance requires modelling the corona in transmission lines. In addition, the impact of the transmission line structure on the performance of surge arresters is investigated. The simulation results indicate that if corona is taken into account in the modelling, the probability of counting by the surge arrester counter decreases from 98.6% to 4%. This result aligns with what has been observed in practice.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".