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Record W3007416633 · doi:10.1109/tie.2020.2975470

An Improved Hybrid Prefiltered Open-Loop Algorithm for Three-Phase Grid Synchronization

2020· article· en· W3007416633 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

VenueIEEE Transactions on Industrial Electronics · 2020
Typearticle
Languageen
FieldEngineering
TopicMicrogrid Control and Optimization
Canadian institutionsUniversité du Québec à Chicoutimi
FundersVillum Fonden
KeywordsPhase-locked loopControl theory (sociology)Computer scienceHarmonicsAlgorithmDemodulationGridFundamental frequencyPhase marginHarmonic analysisHarmonicInstantaneous phaseSynchronization (alternating current)DC biasLow-pass filterFilter (signal processing)Electronic engineeringVoltageEngineeringMathematicsBandwidth (computing)TelecommunicationsAmplifierArtificial intelligencePhysicsJitter

Abstract

fetched live from OpenAlex

In this article, a robust three-phase grid synchronization technique has been proposed for rapid detection of fundamental frequency, phase, and amplitude. The widely accepted phase locked-loop (PLL) algorithms possess complex architectures and require tedious tuning process for attaining a good stability margin. In order to surpass the shortfalls of PLL algorithms, a computationally efficient, stable, and open-loop scheme has been reported in this article. A novel two consecutive samples based frequency estimator is developed for fast detection of the fundamental frequency. Moreover, an efficient hybrid prefiltering approach is implemented based on the demodulation of the grid voltage signal. Additionally, the combination of a delayed signal cancellation operator and a band-pass filter allowed rapid rejection of dc-offset and harmonics, respectively. In the event of a grid voltage imbalance, the instantaneous symmetrical component method is a rescuer for the rejection of the fundamental negative sequence component without any delay. Subsequently, overall transient response time of the scheme is observed to be improved. On the other hand, the fundamental positive sequence component facilitates the estimation of amplitude and phase angle information. Importantly, the dynamic performance of the proposed scheme has been experimentally validated in presence of various grid disturbances.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.981
Threshold uncertainty score1.000

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 communication0.0000.001
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 head0.029
GPT teacher head0.254
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