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Record W2333222281 · doi:10.2514/6.2001-238

Impact of space weather on electric power systems

2001· article· en· W2333222281 on OpenAlexaboutno aff
John G. Kappenman

Bibliographic record

Venue39th Aerospace Sciences Meeting and Exhibit · 2001
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGeomagnetism and Paleomagnetism Studies
Canadian institutionsnot available
Fundersnot available
KeywordsSpace weatherSpace (punctuation)Power (physics)MeteorologyElectric power systemComputer scienceEnvironmental scienceElectrical engineeringAerospace engineeringPhysicsEngineering

Abstract

fetched live from OpenAlex

Geomagnetic disturbances may impact the operational reliability of electric power systems. Solar Cycle 22 (the most recent solar cycle extending from 1986-1996) demonstrated to the power industry the need to take into consideration the potential impacts of geomagnetic storms. Experience gained from the unprecedented scale of these recent storm events provides compelling evidence of a general increase in electric power system susceptibility. Important infrastructure advances have recently been put in place that provide solar wind data. This new data source along with numeric model advances allows the capability for predictive forecasts of severe storm conditions, which can be used by impacted power system operators to better prepare for and manage storm impacts. 1. POWER GRIDS AND SPACE WEATHER AN OVERVIEW Society reliance on electricity for meeting essential needs has steadily increased for many years. This unique energy service requires coordination of electrical supply, demand, and delivery—all occurring at the same instant. Geomagnetic storms can disrupt these complex power grids. The interaction of local geomagnetic field disturbances with terrestrial systems can result in the flow of induced currents on these systems. Geomagnetically-induced currents (GIC) can flow through the power system, entering and exiting the many grounding points on a transmission network. GICs are produced when shocks resulting from sudden and severe magnetic storms subject portions of the Earth's surface to fluctuations in the planet's Figure 1. Exposed Regions of the Northern Hemisphere. The footprints of a superstorm can be extensive; the above diagram shows regions of the Northern Hemisphere that can be exposed to intense storm activity such as the Great Geomagnetic Storm of March 1989. For perspective, the level of storm severity that precipitated the Hydro Quebec collapse (—400 nT/min) was observed at locations as far south as Bay St Louis and would map along geomagnetic latitudes for different time onsets around the world, which would encompass most of North America and Europe. Much stronger intensities were observed at more northerly locations, these intensities are approximately 5 times more severe (2000 nT/min) than the levels that triggered the Hydro Quebec collapse. Levels at one-half the intensity of those that triggered the Hydro Quebec collapse (200 nT/min) have also shown capable of causing power reliability problems which for this storm extended to even lower latitudes. Copyright © 2000 by Metatech. Published by the American Institute of Aeronautics and Astronautics Inc. with permission.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.487
Threshold uncertainty score0.572

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0000.000

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 head0.010
GPT teacher head0.254
Teacher spread0.245 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations0
Published2001
Admission routes1
Has abstractyes

Explore more

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