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Lie Group-Based Control of Grid-Connected Solar Microinverters

2025· article· W4416964564 on OpenAlexaff
Arpan Laha, Abirami Kalathy, Praveen Jain, Majid Pahlevani

Bibliographic record

Venuenot available
Typearticle
Language
FieldEngineering
TopicMicrogrid Control and Optimization
Canadian institutionsQueen's University
Fundersnot available
KeywordsControl theory (sociology)TrajectoryController (irrigation)Synchronization (alternating current)GridFrame (networking)Stability (learning theory)HarmonicVoltageLie algebra

Abstract

fetched live from OpenAlex

This paper introduces differential geometric control based on the Lie group$\text{SO}(2)$and its corresponding Lie Algebra$\mathfrak{s} \mathfrak{o}$(2) for the synchronization and control of inverters. We frame the grid voltage and inverter output currents within the$S O(2)$group and effectively control the trajectory of the current's phase. The proposed controller functions as a phaselocked loop, ensuring seamless integration with the grid and enhancing stability during disturbances like harmonics, phase jumps, and voltage sags/swells. It also supports a harmonic estimation scheme for sinusoidal current injection under polluted grid conditions, improving power quality. Experimental results confirm the effectiveness of the proposed control scheme.

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)0.000
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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.003
GPT teacher head0.171
Teacher spread0.168 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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