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Record W2302541268 · doi:10.2172/1059627

Geomagnetic Storms and Long-Term Impacts on Power Systems

2011· report· en· W2302541268 on OpenAlexaboutno aff
Harold Kirkham, Yuri V. Makarov, Jeff Dagle, John G. DeSteese, Marcelo Elizondo, Ruisheng Diao

Bibliographic record

Venuenot available
Typereport
Languageen
FieldPhysics and Astronomy
TopicLightning and Electromagnetic Phenomena
Canadian institutionsnot available
FundersBattelleU.S. Department of Homeland SecurityU.S. Department of Energy
KeywordsBlackoutElectric power transmissionGeomagnetically induced currentElectric power systemInterconnectionTransformerCapacitorElectricityGeomagnetic stormPower transmissionEngineeringElectrical engineeringTelecommunicationsPower (physics)VoltageEarth's magnetic fieldPhysics

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.592
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.018
GPT teacher head0.248
Teacher spread0.230 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations10
Published2011
Admission routes1
Has abstractyes

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