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Record W2968071386 · doi:10.1109/tpel.2019.2933770

Multirate Harmonic Compensation Control for Low Switching Frequency Converters: Scheme, Modeling, and Analysis

2019· article· en· W2968071386 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueIEEE Transactions on Power Electronics · 2019
Typearticle
Languageen
FieldEngineering
TopicMicrogrid Control and Optimization
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of CanadaCanada First Research Excellence Fund
KeywordsConvertersControl theory (sociology)HarmonicsInterfacingHarmonicCompensation (psychology)Sampling (signal processing)Computer scienceAutomatic frequency controlDescribing functionHarmonic analysisElectronic engineeringEngineeringVoltageFilter (signal processing)Control (management)Nonlinear systemTelecommunicationsElectrical engineering

Abstract

fetched live from OpenAlex

Using the grid-interfacing voltage-source converters (VSCs) to perform harmonic control as a smart ancillary function is increasingly studied in recent years. Different from the traditional dedicated harmonic compensation converters, the main function of the high-power smart converters is still delivering real power at a low switching frequency (e.g., 2 kHz). It is challenging to compensate harmonics with low switching frequency VSCs due to the low sampling rate and large system delay. This article proposes a multirate control scheme and derives the accurate multirate model to improve harmonic control. The multirate control scheme consists of high-rate harmonic control and synchronous sampled fundamental control. With the proposed control scheme, the advantages of the conventional synchronous sampling method and the benefits of the high sampling rate are achieved simultaneously. To accurately model the low switching VSC with two different sampling rates, the lifting method is introduced to achieve the discrete-time system model for this linear periodic time-varying system. The frequency response and stability analysis are carried out based on the lifted model. The modeling method, as well as the enhanced harmonic control performance of the multirate control structure, is validated in the experiments.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.835
Threshold uncertainty score0.899

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 head0.005
GPT teacher head0.194
Teacher spread0.190 · 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