Geomagnetic Storms and Long-Term Impacts on Power Systems
Bibliographic record
Abstract
Pacific Northwest National Laboratory was commissioned to study the potential impact of a severe GIC event on the western U.S.-Canada power grid (referred to as the Western Interconnection). The study identified long transmission lines (length exceeding 150 miles) that did not include series capacitors. The basic assumption for the study is that a GIC is more likely to couple to long transmission lines, and that series capacitors would block the flow of the induced DC GIC. Power system simulations were conducted to evaluate impacts to the bulk power system if transformers on either end of these lines failed. The study results indicated that the Western Interconnection was not substantially at risk to GIC because of the relatively small number of transmission lines that met this criterion. This report also provides a summary of the Hydro-Québec blackout on March 13, 1989, which was caused by a GIC. This case study delves into the failure mechanisms of that event, lessons learned, and preventive measures that have been implemented to minimize the likelihood of its reoccurrence. Finally, the report recommends that the electric power industry consider the adoption of new protective relaying approaches that will prevent severe GIC events from catastrophically damaging transformers. The resulting changes may increase the likelihood of smaller disruptions but should prevent an unlikely yet catastrophic national-level event.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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".