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Record W2135379734 · doi:10.1109/tpwrs.2008.922232

Control and Power Management of Converter Fed Microgrids

2008· article· en· W2135379734 on OpenAlexaff
Charles Sao, Peter W. Lehn

Bibliographic record

VenueIEEE Transactions on Power Systems · 2008
Typearticle
Languageen
FieldEngineering
TopicMicrogrid Control and Optimization
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMicrogridVoltage droopControl theory (sociology)AC powerConvertersVoltage sourceAutomatic frequency controlVoltage regulationController (irrigation)VoltagePower controlEngineeringVoltage optimisationComputer sciencePower (physics)Control (management)Electrical engineeringPhysics

Abstract

fetched live from OpenAlex

This paper presents a voltage-power droop/frequency-reactive power boost (VPD/FQB) control scheme that allows multiple voltage source converters (VSCs) to operate in parallel in a VSC fed microgrid. Each current controlled VSC in such a microgrid has its own VPD/FQB controller that sets its current references to regulate the voltage and frequency of a common microgrid bus. By drooping the voltage reference of each controller against its real power output, multiple VPD/FQB controllers jointly regulate the microgrid voltage while sharing a common load power in proportion to a predetermined ratio. Similarly, by boosting the frequency reference of each controller against its reactive power output, multiple VPD/FQB controllers jointly regulate the microgrid frequency while sharing the reactive load in proportion to a predetermined ratio. The proposed control scheme can also operate in grid connected mode. Experimental results are provided to validate the VPD/FQB 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: Simulation or modeling · Consensus signal: Simulation or modeling
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 studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
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 head0.005
GPT teacher head0.171
Teacher spread0.166 · 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

Citations485
Published2008
Admission routes1
Has abstractyes

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