Effects of neutral point reactors and series capacitors on geomagnetically induced currents in a high‐voltage electric power transmission system
Bibliographic record
Abstract
Geomagnetically induced currents (GIC) are DC‐like currents compared to power transmission frequencies. Consequently, it may be possible to reduce the magnitudes of GIC by installing resistive components or series capacitors into a power grid. We simulate the effects of neutral point reactors and series capacitors on GIC in the Finnish 400 kV network. Reactors add an additional resistance to earthing leads of transformers, and series capacitors block the flow of GIC in transmission lines. The geoelectric field impacting the system is considered to be uniform. The use of reactors does not necessarily reduce the GIC risk. Although the installation of reactors tends to decrease GIC on the average, maximum GIC may even increase. Assuming a reactor at all stations results in a 50% reduction of the maximum GIC compared to the situation with no reactors. With up to four series capacitors, the maximum GIC is reduced by 40% when they are optimally located. However, even small changes in the topology of the grid can cause large changes in GIC. A combination of reactors and series capacitors could in principle provide a way to diminish the GIC risk. This study also emphasizes the difficulty of preventing GIC problems by these means.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".