Influence of Transient Overvoltage in a High-Voltage System During Shunt Reactor De-Energization
Bibliographic record
Abstract
This study investigates transients resulting from switching a three-phase 400 kV shunt reactor.The main concern is the occurrence of current chopping during the de-energization of the shunt reactor, which can lead to overvoltages and stress on circuit breakers and the shunt reactor itself.When clearing a ground arcing fault, a neutral Earthing reactor aids in interrupting the current.Switching a grounded shunt reactor via a neutral reactor may stress circuit breakers more than switching a solidly grounded shunt reactor.This study proposes a novel circuit modification to suppress excessive transient overvoltages due to current chopping during shunt reactor de-energization.The proposed modification involves integrating an additional circuit breaker and its inherent resistance into the existing circuit.Utilizing ATP-Draw software, the study models and analyzes transient behavior specifically for a 50 MVAR reactive power rating.Different mitigation techniques, including controlled switching, surge arresters, disconnecting switches, and a novel circuit modification model, are compared based on simulation results.A new model for de-energizing shunt reactors is presented in this study, achieving significant reductions in transient voltages on both the reactor and circuit breaker compared to traditional models.This model focuses on optimized synchronization between circuit breakers, leading to an 84% voltage drop, highlighting the significant advantages of this approach.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".