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Record W2011341245 · doi:10.1109/icpst.2006.321952

HVDC Power System Harmonic Analysis in the Time and Frequency Domains

2006· article· en· W2011341245 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicHigh-Voltage Power Transmission Systems
Canadian institutionsResearch Manitoba
Fundersnot available
KeywordsHarmonicsElectric power systemHarmonicFrequency domainHarmonic analysisElectronic engineeringPower (physics)Computer scienceTime domainControl theory (sociology)EngineeringElectrical engineeringControl (management)VoltagePhysicsAcoustics

Abstract

fetched live from OpenAlex

Harmonics in HVDC power systems caused by highly non-linear devices affect its performance. Controlling and eliminating such harmonics have been a great concern of power engineers in power system design and operation. The HVDC power system harmonic analysis is, therefore, essential in power system planning, control, and operation. The two main mathematical approaches in power system harmonic study are the time-domain analysis and the frequency-domain solution. The former is suitable for studying phenomena including non- linearity, switching operations, long-time simulations, and control systems. The latter, on the other hand, is appropriate for studying phenomena such as frequency dependence, system equivalents, and frequency response. This paper discusses the time and frequency domain methods in the HVDC power system harmonic analysis. It reviews the sources of HVDC system harmonics. The paper also reveals the advantages and disadvantages of the methods and points out their suitable applications in power network harmonic computations.

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.

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 score0.488
Threshold uncertainty score0.404

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.004
GPT teacher head0.185
Teacher spread0.181 · 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

Quick stats

Citations13
Published2006
Admission routes1
Has abstractyes

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