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Record W2162636717 · doi:10.1109/pes.2011.6039487

Load sharing of autonomous distribution-level microgrids

2011· article· en· W2162636717 on OpenAlexaff
Aboutaleb Haddadi, G. Joós

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicMicrogrid Control and Optimization
Canadian institutionsMcGill University
Fundersnot available
KeywordsVoltage droopMicrogridInterfacingInductanceControl theory (sociology)AC powerComputer sciencePower (physics)Resistive touchscreenElectrical impedanceInverterOutput impedanceVoltageControl (management)EngineeringVoltage sourceElectrical engineering

Abstract

fetched live from OpenAlex

This paper investigates the problem of appropriate load sharing in an autonomous distribution-level microgrid, where the considerable resistive component of the line impedance makes the conventional frequency and voltage droop controls impractical. To improve active and reactive power sharing, a power control strategy is proposed which contains a virtual inductor at the interfacing inverter output and a supplementary control loop around the conventional droop control of each DG converter. Specifically, the virtual inductance prevents the coupling between the real and reactive power control by introducing a predominantly inductive impedance, and the supplementary control loop stabilizes the system while using high droop gains which are needed for proper load sharing. The proposed control strategy is proven to ensure satisfactory load sharing while stabilizing the system for a range of operating conditions.

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)0.001
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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
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 head0.022
GPT teacher head0.182
Teacher spread0.161 · 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 designSimulation or modeling
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

Citations23
Published2011
Admission routes1
Has abstractyes

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