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APPLICATION OF THE UNIFIED POWER QUALITY CONDITIONER FOR MITIGATING ELECTRIC ARC FURNACE DISTURBANCES

2008· article· en· W2524002669 on OpenAlexvenueno aff

Bibliographic record

VenueInternational Journal of Power and Energy Systems · 2008
Typearticle
Languageen
FieldEngineering
TopicPower Quality and Harmonics
Canadian institutionsnot available
Fundersnot available
KeywordsElectric arc furnacePower qualityElectric arcArc (geometry)Electric power qualityElectric powerQuality (philosophy)Environmental scienceAutomotive engineeringElectrical engineeringPower (physics)Waste managementMaterials scienceEngineeringMetallurgyMechanical engineeringVoltageElectrodePhysics

Abstract

fetched live from OpenAlex

This paper discusses the application of unified power quality conditioner (UPQC) for improving power quality of a system supplying an electric arc furnace (EAF). The UPQC includes combined series and shunt active filters sharing a common DC link. It is used to mitigate voltage disturbances and compensate for reactive power, harmonics and interharmonics. A novel control strategy for the UPQC is presented. As voltages at the point of common coupling contain low-frequency interharmonics, conventional methods cannot be used for extracting voltage reference signals. In the proposed method, voltage references are extracted using a phase-locked loop to generate sinusoidal waveforms. Current compensating signals are detected based on the current vector mapping on a rotating reference frame constituted by the instantaneous phase voltages. A real system is simulated using a three-phase EAF model. Simulation results are presented to verify the control strategy and to assess the performance of UPQC in improving power quality.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0010.000

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 head0.017
GPT teacher head0.254
Teacher spread0.238 · 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 source (direct Gemma or distilled Codex), 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

Citations8
Published2008
Admission routes1
Has abstractyes

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