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Record W4381328142 · doi:10.1109/tia.2023.3287471

Investigating Harmonic Distortion in Power Transformers Due to Geomagnetically Induced Current Flows

2023· article· en· W4381328142 on OpenAlexafffund
S. A. Saleh, E. W. Zundel, G. Young-Morris, D. Jewett, Scott Brown, E. F .S. Hill, Julian Meng

Bibliographic record

VenueIEEE Transactions on Industry Applications · 2023
Typearticle
Languageen
FieldPhysics and Astronomy
TopicLightning and Electromagnetic Phenomena
Canadian institutionsEnergie NB Power (Canada)University of New Brunswick
FundersAtlantic Canada Opportunities Agency
KeywordsGeomagnetically induced currentTransformerNotationElectrical engineeringTotal harmonic distortionTopology (electrical circuits)Computer scienceMathematicsVoltagePhysicsEngineeringEarth's magnetic fieldGeomagnetic stormQuantum mechanicsArithmeticMagnetic field

Abstract

fetched live from OpenAlex

Geomagnetically induced currents (GICs) flow through grounding circuits into power systems, when triggered by geomagnetic disturbances. Power transformers (with grounding connections) are the primary path for GIC flows into power systems. The flow of GICs through a power transformer can create adverse impacts on its operation, including large increases in its reactive power demands and significant harmonic distortions in the primary side currents. This article presents case studies and analyses of the adverse impacts of GIC flows on power transformers. Presented case studies are conducted on two power transformers with different core types, power ratings, and voltage ratings. Each of these power transformers is tested for various levels of GIC flows with its loading being kept unchanged. Results of conducted case studies conclude that the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\text{2}$</tex-math></inline-formula> nd harmonic is the dominant in primary and side currents at all levels of GIC flows. Other harmonic components such as the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\text{3}$</tex-math></inline-formula> rd, <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\text{4}$</tex-math></inline-formula> th, <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$ \text{5th},\ \text{6th},\ \text{7th}\ \text{and}\ \text{8}$</tex-math></inline-formula> th harmonic components, can be observed with lower magnitudes than the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\text{2}$</tex-math></inline-formula> nd harmonic component.

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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.871
Threshold uncertainty score0.930

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.021
GPT teacher head0.274
Teacher spread0.253 · 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 designOther design
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

Citations30
Published2023
Admission routes2
Has abstractyes

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