Assessing the impact of weak and moderate geomagnetic storms on UK power station transformers
Bibliographic record
Abstract
It is well documented that space weather can impact electricity infrastructure, and several incidents have been observed in recent decades and directly linked to large geomagnetic storms (e.g. the Hydro Quebec incident in 1989). However, less is understood aboutthe impact of lower-level geomagnetically induced currents (GICs) on the health of transformers in the long term. In this study, the long term impact of geomagnetic activity on 13 power station transformers in the UK is investigated. Dissolved gas measurements from 2010–2015 were used to look for evidence of a link between degradation of the transformer and heightened levels of the global SYM-H index and dB as measured at Eskdalemuir magnetometer station in southern Scotland. First, case studies of the most significant storms in this time period were examined using dissolved gas analysis (DGA) methods, specifically the Low Energy Degradation Triangle (LEDT). These case studies were then augmented with a statistical survey, including Superposed Epoch Analysis (SEA) of multiple storm events. No evidence of a systematic space weather impact can be found during this time period, likely owing to the relatively quiet nature of the Sun during this epoch and the modernity of the transformers studied.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".