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Record W2888341068 · doi:10.1109/tdc.2018.8440349

Tertiary Voltage Unbalance Compensation for 500kV Single Phase Autotransformer Banks

2018· article· en· W2888341068 on OpenAlexaff
Lianxiang Tang, Pengcheng Zhao

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicRailway Systems and Energy Efficiency
Canadian institutionsHydro One (Canada)
Fundersnot available
KeywordsTransformerAutotransformerOvervoltageElectrical engineeringEngineeringCapacitive sensingVoltageEmtpEnergy efficient transformerDelta-wye transformerElectromagnetic coilCapacitanceGroundDistribution transformerPhysicsElectric power system

Abstract

fetched live from OpenAlex

In an ungrounded transformer tertiary system, most often the phase-to-ground voltages are slightly unbalanced. Therefore all equipment supplied by the tertiary must have extra insulation to withstand the expected phase-to-ground overvoltages that arise from such unbalance. However, in a recent 3 × 250MV A single phase transformer bank replacement project, it was found that the tertiary phase-to-ground overvoltages were abnormally high therefore the transformer bank could not be put back into service. After extensive investigation, it was found that the transformer inter-winding capacitances and tertiary phase-to-ground capacitances were unbalanced, resulting in excessive unbalance in the tertiary phase-to-ground voltages, which was directly responsible for the overvoltage. A mitigation plan was developed. The plan was to modify the tertiary phase-to-ground capacitances in such a way that the voltage unbalance due to the asymmetry in the inter-winding capacitances cancels the voltage unbalance due to the asymmetry in the phase-to-ground capacitances. Based on theoretical derivation and EMTP simulation, two CVTs (Capacitive Voltage Transformer) were selected from the warehouse and installed on the transformer tertiary. The voltage unbalance was successfully mitigated and the transformer bank was put back into service. The mitigation methodology developed in the project achieved significant cost saving and will have great value in future project development.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.678
Threshold uncertainty score0.407

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 head0.014
GPT teacher head0.239
Teacher spread0.225 · 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 designBench or experimental
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

Citations2
Published2018
Admission routes1
Has abstractyes

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